Struct opencv::core::Ptr

pub struct Ptr<T: ?Sized>
where
    Self: PtrExtern,
{ /* private fields */ }

This is similar to Rust Arc, but handled by the C++. Some OpenCV functions insist on accepting Ptr instead of a heap allocated object, so we need to satisfy those.

docs.opencv.org 3.x docs.opencv.org 4.x

Implementations

impl<T: ?Sized> Ptr<T>

where Self: PtrExtern,

pub fn new(val: T) -> Self

where T: OpenCVTypeExternContainerMove + Sized, Self: PtrExternCtor<T>,

Create a new Ptr from the object

pub fn inner_as_raw(&self) -> *const c_void

Get raw pointer to the inner object

pub fn inner_as_raw_mut(&mut self) -> *mut c_void

Get mutable raw pointer to the inner object

impl Ptr<EstimateParameters>

pub fn as_raw_PtrOfEstimateParameters( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfEstimateParameters( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BackgroundSubtractorCNT>

pub fn as_raw_PtrOfBackgroundSubtractorCNT( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBackgroundSubtractorCNT( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BackgroundSubtractorGMG>

pub fn as_raw_PtrOfBackgroundSubtractorGMG( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBackgroundSubtractorGMG( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BackgroundSubtractorGSOC>

pub fn as_raw_PtrOfBackgroundSubtractorGSOC( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBackgroundSubtractorGSOC( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BackgroundSubtractorLSBP>

pub fn as_raw_PtrOfBackgroundSubtractorLSBP( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBackgroundSubtractorLSBP( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BackgroundSubtractorMOG>

pub fn as_raw_PtrOfBackgroundSubtractorMOG( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBackgroundSubtractorMOG( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SyntheticSequenceGenerator>

pub fn as_raw_PtrOfSyntheticSequenceGenerator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSyntheticSequenceGenerator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Retina>

pub fn as_raw_PtrOfRetina( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRetina( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RetinaFastToneMapping>

pub fn as_raw_PtrOfRetinaFastToneMapping( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRetinaFastToneMapping( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TransientAreasSegmentationModule>

pub fn as_raw_PtrOfTransientAreasSegmentationModule( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTransientAreasSegmentationModule( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LMSolver>

pub fn as_raw_PtrOfLMSolver( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLMSolver( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LMSolver_Callback>

pub fn as_raw_PtrOfLMSolver_Callback( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLMSolver_Callback( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<StereoBM>

pub fn as_raw_PtrOfStereoBM( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfStereoBM( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<StereoMatcher>

pub fn as_raw_PtrOfStereoMatcher( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfStereoMatcher( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<StereoSGBM>

pub fn as_raw_PtrOfStereoSGBM( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfStereoSGBM( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CustomPattern>

pub fn as_raw_PtrOfCustomPattern( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCustomPattern( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Algorithm>

pub fn as_raw_PtrOfAlgorithm( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAlgorithm( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ConjGradSolver>

pub fn as_raw_PtrOfConjGradSolver( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfConjGradSolver( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DownhillSolver>

pub fn as_raw_PtrOfDownhillSolver( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDownhillSolver( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FileStorage>

pub fn as_raw_PtrOfFileStorage( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFileStorage( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Formatted>

pub fn as_raw_PtrOfFormatted( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFormatted( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Formatter>

pub fn as_raw_PtrOfFormatter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFormatter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GpuMat_Allocator>

pub fn as_raw_PtrOfGpuMat_Allocator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGpuMat_Allocator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MinProblemSolver>

pub fn as_raw_PtrOfMinProblemSolver( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMinProblemSolver( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MinProblemSolver_Function>

pub fn as_raw_PtrOfMinProblemSolver_Function( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMinProblemSolver_Function( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<OriginalClassName>

pub fn as_raw_PtrOfOriginalClassName( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfOriginalClassName( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<f32>

pub fn as_raw_PtrOff32(&self) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOff32( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Convolution>

pub fn as_raw_PtrOfConvolution( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfConvolution( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DFT>

pub fn as_raw_PtrOfDFT(&self) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDFT( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LookUpTable>

pub fn as_raw_PtrOfLookUpTable( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLookUpTable( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_BackgroundSubtractorMOG>

pub fn as_raw_PtrOfCUDA_BackgroundSubtractorMOG( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_BackgroundSubtractorMOG( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_BackgroundSubtractorMOG2>

pub fn as_raw_PtrOfCUDA_BackgroundSubtractorMOG2( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_BackgroundSubtractorMOG2( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_EncoderCallback>

pub fn as_raw_PtrOfCUDA_EncoderCallback( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_EncoderCallback( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_RawVideoSource>

pub fn as_raw_PtrOfCUDA_RawVideoSource( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_RawVideoSource( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_VideoReader>

pub fn as_raw_PtrOfCUDA_VideoReader( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_VideoReader( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_VideoWriter>

pub fn as_raw_PtrOfCUDA_VideoWriter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_VideoWriter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_DescriptorMatcher>

pub fn as_raw_PtrOfCUDA_DescriptorMatcher( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_DescriptorMatcher( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_FastFeatureDetector>

pub fn as_raw_PtrOfCUDA_FastFeatureDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_FastFeatureDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_Feature2DAsync>

pub fn as_raw_PtrOfCUDA_Feature2DAsync( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_Feature2DAsync( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_ORB>

pub fn as_raw_PtrOfCUDA_ORB( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_ORB( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Filter>

pub fn as_raw_PtrOfFilter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFilter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_CLAHE>

pub fn as_raw_PtrOfCUDA_CLAHE( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_CLAHE( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_CannyEdgeDetector>

pub fn as_raw_PtrOfCUDA_CannyEdgeDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_CannyEdgeDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_CornernessCriteria>

pub fn as_raw_PtrOfCUDA_CornernessCriteria( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_CornernessCriteria( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_CornersDetector>

pub fn as_raw_PtrOfCUDA_CornersDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_CornersDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_HoughCirclesDetector>

pub fn as_raw_PtrOfCUDA_HoughCirclesDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_HoughCirclesDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_HoughLinesDetector>

pub fn as_raw_PtrOfCUDA_HoughLinesDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_HoughLinesDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_HoughSegmentDetector>

pub fn as_raw_PtrOfCUDA_HoughSegmentDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_HoughSegmentDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_TemplateMatching>

pub fn as_raw_PtrOfCUDA_TemplateMatching( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_TemplateMatching( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_CascadeClassifier>

pub fn as_raw_PtrOfCUDA_CascadeClassifier( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_CascadeClassifier( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_HOG>

pub fn as_raw_PtrOfCUDA_HOG( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_HOG( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_BroxOpticalFlow>

pub fn as_raw_PtrOfCUDA_BroxOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_BroxOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_DenseOpticalFlow>

pub fn as_raw_PtrOfCUDA_DenseOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_DenseOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_DensePyrLKOpticalFlow>

pub fn as_raw_PtrOfCUDA_DensePyrLKOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_DensePyrLKOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_FarnebackOpticalFlow>

pub fn as_raw_PtrOfCUDA_FarnebackOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_FarnebackOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_NvidiaHWOpticalFlow>

pub fn as_raw_PtrOfCUDA_NvidiaHWOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_NvidiaHWOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_NvidiaOpticalFlow_1_0>

pub fn as_raw_PtrOfCUDA_NvidiaOpticalFlow_1_0( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_NvidiaOpticalFlow_1_0( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_NvidiaOpticalFlow_2_0>

pub fn as_raw_PtrOfCUDA_NvidiaOpticalFlow_2_0( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_NvidiaOpticalFlow_2_0( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_OpticalFlowDual_TVL1>

pub fn as_raw_PtrOfCUDA_OpticalFlowDual_TVL1( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_OpticalFlowDual_TVL1( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_SparseOpticalFlow>

pub fn as_raw_PtrOfCUDA_SparseOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_SparseOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_SparsePyrLKOpticalFlow>

pub fn as_raw_PtrOfCUDA_SparsePyrLKOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_SparsePyrLKOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_DisparityBilateralFilter>

pub fn as_raw_PtrOfCUDA_DisparityBilateralFilter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_DisparityBilateralFilter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_StereoBM>

pub fn as_raw_PtrOfCUDA_StereoBM( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_StereoBM( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_StereoBeliefPropagation>

pub fn as_raw_PtrOfCUDA_StereoBeliefPropagation( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_StereoBeliefPropagation( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_StereoConstantSpaceBP>

pub fn as_raw_PtrOfCUDA_StereoConstantSpaceBP( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_StereoConstantSpaceBP( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CUDA_StereoSGM>

pub fn as_raw_PtrOfCUDA_StereoSGM( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCUDA_StereoSGM( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AbsLayer>

pub fn as_raw_PtrOfAbsLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAbsLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AccumLayer>

pub fn as_raw_PtrOfAccumLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAccumLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AcosLayer>

pub fn as_raw_PtrOfAcosLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAcosLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AcoshLayer>

pub fn as_raw_PtrOfAcoshLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAcoshLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ActivationLayer>

pub fn as_raw_PtrOfActivationLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfActivationLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ActivationLayerInt8>

pub fn as_raw_PtrOfActivationLayerInt8( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfActivationLayerInt8( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ArgLayer>

pub fn as_raw_PtrOfArgLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfArgLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AsinLayer>

pub fn as_raw_PtrOfAsinLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAsinLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AsinhLayer>

pub fn as_raw_PtrOfAsinhLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAsinhLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AtanLayer>

pub fn as_raw_PtrOfAtanLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAtanLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AtanhLayer>

pub fn as_raw_PtrOfAtanhLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAtanhLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AttentionLayer>

pub fn as_raw_PtrOfAttentionLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAttentionLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BNLLLayer>

pub fn as_raw_PtrOfBNLLLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBNLLLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BackendNode>

pub fn as_raw_PtrOfBackendNode( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBackendNode( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BackendWrapper>

pub fn as_raw_PtrOfBackendWrapper( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBackendWrapper( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BaseConvolutionLayer>

pub fn as_raw_PtrOfBaseConvolutionLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBaseConvolutionLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BatchNormLayer>

pub fn as_raw_PtrOfBatchNormLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBatchNormLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BatchNormLayerInt8>

pub fn as_raw_PtrOfBatchNormLayerInt8( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBatchNormLayerInt8( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BlankLayer>

pub fn as_raw_PtrOfBlankLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBlankLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CeilLayer>

pub fn as_raw_PtrOfCeilLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCeilLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CeluLayer>

pub fn as_raw_PtrOfCeluLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCeluLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ChannelsPReLULayer>

pub fn as_raw_PtrOfChannelsPReLULayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfChannelsPReLULayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CompareLayer>

pub fn as_raw_PtrOfCompareLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCompareLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ConcatLayer>

pub fn as_raw_PtrOfConcatLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfConcatLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ConstLayer>

pub fn as_raw_PtrOfConstLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfConstLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ConvolutionLayer>

pub fn as_raw_PtrOfConvolutionLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfConvolutionLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ConvolutionLayerInt8>

pub fn as_raw_PtrOfConvolutionLayerInt8( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfConvolutionLayerInt8( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CorrelationLayer>

pub fn as_raw_PtrOfCorrelationLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCorrelationLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CosLayer>

pub fn as_raw_PtrOfCosLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCosLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CoshLayer>

pub fn as_raw_PtrOfCoshLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCoshLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CropAndResizeLayer>

pub fn as_raw_PtrOfCropAndResizeLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCropAndResizeLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CropLayer>

pub fn as_raw_PtrOfCropLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCropLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CumSumLayer>

pub fn as_raw_PtrOfCumSumLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCumSumLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DataAugmentationLayer>

pub fn as_raw_PtrOfDataAugmentationLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDataAugmentationLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DeconvolutionLayer>

pub fn as_raw_PtrOfDeconvolutionLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDeconvolutionLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DequantizeLayer>

pub fn as_raw_PtrOfDequantizeLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDequantizeLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DetectionOutputLayer>

pub fn as_raw_PtrOfDetectionOutputLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetectionOutputLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ELULayer>

pub fn as_raw_PtrOfELULayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfELULayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<EinsumLayer>

pub fn as_raw_PtrOfEinsumLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfEinsumLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<EltwiseLayer>

pub fn as_raw_PtrOfEltwiseLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfEltwiseLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<EltwiseLayerInt8>

pub fn as_raw_PtrOfEltwiseLayerInt8( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfEltwiseLayerInt8( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ErfLayer>

pub fn as_raw_PtrOfErfLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfErfLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ExpLayer>

pub fn as_raw_PtrOfExpLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfExpLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ExpandLayer>

pub fn as_raw_PtrOfExpandLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfExpandLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FlattenLayer>

pub fn as_raw_PtrOfFlattenLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFlattenLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FloorLayer>

pub fn as_raw_PtrOfFloorLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFloorLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FlowWarpLayer>

pub fn as_raw_PtrOfFlowWarpLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFlowWarpLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GRULayer>

pub fn as_raw_PtrOfGRULayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGRULayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GatherElementsLayer>

pub fn as_raw_PtrOfGatherElementsLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGatherElementsLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GatherLayer>

pub fn as_raw_PtrOfGatherLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGatherLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GeluApproximationLayer>

pub fn as_raw_PtrOfGeluApproximationLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGeluApproximationLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GeluLayer>

pub fn as_raw_PtrOfGeluLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGeluLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GemmLayer>

pub fn as_raw_PtrOfGemmLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGemmLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<HardSigmoidLayer>

pub fn as_raw_PtrOfHardSigmoidLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfHardSigmoidLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<HardSwishLayer>

pub fn as_raw_PtrOfHardSwishLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfHardSwishLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<InnerProductLayer>

pub fn as_raw_PtrOfInnerProductLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfInnerProductLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<InnerProductLayerInt8>

pub fn as_raw_PtrOfInnerProductLayerInt8( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfInnerProductLayerInt8( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<InstanceNormLayer>

pub fn as_raw_PtrOfInstanceNormLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfInstanceNormLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<InterpLayer>

pub fn as_raw_PtrOfInterpLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfInterpLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LRNLayer>

pub fn as_raw_PtrOfLRNLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLRNLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LSTMLayer>

pub fn as_raw_PtrOfLSTMLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLSTMLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Layer>

pub fn as_raw_PtrOfLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LayerNormLayer>

pub fn as_raw_PtrOfLayerNormLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLayerNormLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LogLayer>

pub fn as_raw_PtrOfLogLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLogLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MVNLayer>

pub fn as_raw_PtrOfMVNLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMVNLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MatMulLayer>

pub fn as_raw_PtrOfMatMulLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMatMulLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MaxUnpoolLayer>

pub fn as_raw_PtrOfMaxUnpoolLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMaxUnpoolLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MishLayer>

pub fn as_raw_PtrOfMishLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMishLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<NaryEltwiseLayer>

pub fn as_raw_PtrOfNaryEltwiseLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfNaryEltwiseLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<NormalizeBBoxLayer>

pub fn as_raw_PtrOfNormalizeBBoxLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfNormalizeBBoxLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<NotLayer>

pub fn as_raw_PtrOfNotLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfNotLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PaddingLayer>

pub fn as_raw_PtrOfPaddingLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPaddingLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PermuteLayer>

pub fn as_raw_PtrOfPermuteLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPermuteLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PoolingLayer>

pub fn as_raw_PtrOfPoolingLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPoolingLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PoolingLayerInt8>

pub fn as_raw_PtrOfPoolingLayerInt8( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPoolingLayerInt8( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PowerLayer>

pub fn as_raw_PtrOfPowerLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPowerLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PriorBoxLayer>

pub fn as_raw_PtrOfPriorBoxLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPriorBoxLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ProposalLayer>

pub fn as_raw_PtrOfProposalLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfProposalLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<QuantizeLayer>

pub fn as_raw_PtrOfQuantizeLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfQuantizeLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RNNLayer>

pub fn as_raw_PtrOfRNNLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRNNLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ReLU6Layer>

pub fn as_raw_PtrOfReLU6Layer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfReLU6Layer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ReLULayer>

pub fn as_raw_PtrOfReLULayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfReLULayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ReciprocalLayer>

pub fn as_raw_PtrOfReciprocalLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfReciprocalLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ReduceLayer>

pub fn as_raw_PtrOfReduceLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfReduceLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RegionLayer>

pub fn as_raw_PtrOfRegionLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRegionLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ReorgLayer>

pub fn as_raw_PtrOfReorgLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfReorgLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RequantizeLayer>

pub fn as_raw_PtrOfRequantizeLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRequantizeLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ReshapeLayer>

pub fn as_raw_PtrOfReshapeLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfReshapeLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ResizeLayer>

pub fn as_raw_PtrOfResizeLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfResizeLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RoundLayer>

pub fn as_raw_PtrOfRoundLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRoundLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ScaleLayer>

pub fn as_raw_PtrOfScaleLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfScaleLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ScaleLayerInt8>

pub fn as_raw_PtrOfScaleLayerInt8( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfScaleLayerInt8( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ScatterLayer>

pub fn as_raw_PtrOfScatterLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfScatterLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ScatterNDLayer>

pub fn as_raw_PtrOfScatterNDLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfScatterNDLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SeluLayer>

pub fn as_raw_PtrOfSeluLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSeluLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ShiftLayer>

pub fn as_raw_PtrOfShiftLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfShiftLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ShiftLayerInt8>

pub fn as_raw_PtrOfShiftLayerInt8( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfShiftLayerInt8( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ShrinkLayer>

pub fn as_raw_PtrOfShrinkLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfShrinkLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ShuffleChannelLayer>

pub fn as_raw_PtrOfShuffleChannelLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfShuffleChannelLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SigmoidLayer>

pub fn as_raw_PtrOfSigmoidLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSigmoidLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SignLayer>

pub fn as_raw_PtrOfSignLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSignLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SinLayer>

pub fn as_raw_PtrOfSinLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSinLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SinhLayer>

pub fn as_raw_PtrOfSinhLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSinhLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SliceLayer>

pub fn as_raw_PtrOfSliceLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSliceLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SoftmaxLayer>

pub fn as_raw_PtrOfSoftmaxLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSoftmaxLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SoftmaxLayerInt8>

pub fn as_raw_PtrOfSoftmaxLayerInt8( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSoftmaxLayerInt8( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SoftplusLayer>

pub fn as_raw_PtrOfSoftplusLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSoftplusLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SoftsignLayer>

pub fn as_raw_PtrOfSoftsignLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSoftsignLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SplitLayer>

pub fn as_raw_PtrOfSplitLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSplitLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SqrtLayer>

pub fn as_raw_PtrOfSqrtLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSqrtLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SwishLayer>

pub fn as_raw_PtrOfSwishLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSwishLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TanHLayer>

pub fn as_raw_PtrOfTanHLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTanHLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TanLayer>

pub fn as_raw_PtrOfTanLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTanLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ThresholdedReluLayer>

pub fn as_raw_PtrOfThresholdedReluLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfThresholdedReluLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TileLayer>

pub fn as_raw_PtrOfTileLayer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTileLayer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DnnSuperResImpl>

pub fn as_raw_PtrOfDnnSuperResImpl( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDnnSuperResImpl( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DPMDetector>

pub fn as_raw_PtrOfDPMDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDPMDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BIF>

pub fn as_raw_PtrOfBIF(&self) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBIF( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BasicFaceRecognizer>

pub fn as_raw_PtrOfBasicFaceRecognizer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBasicFaceRecognizer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<EigenFaceRecognizer>

pub fn as_raw_PtrOfEigenFaceRecognizer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfEigenFaceRecognizer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FaceRecognizer>

pub fn as_raw_PtrOfFaceRecognizer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFaceRecognizer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Facemark>

pub fn as_raw_PtrOfFacemark( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFacemark( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FacemarkAAM>

pub fn as_raw_PtrOfFacemarkAAM( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFacemarkAAM( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FacemarkKazemi>

pub fn as_raw_PtrOfFacemarkKazemi( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFacemarkKazemi( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FacemarkLBF>

pub fn as_raw_PtrOfFacemarkLBF( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFacemarkLBF( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FacemarkTrain>

pub fn as_raw_PtrOfFacemarkTrain( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFacemarkTrain( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FisherFaceRecognizer>

pub fn as_raw_PtrOfFisherFaceRecognizer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFisherFaceRecognizer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LBPHFaceRecognizer>

pub fn as_raw_PtrOfLBPHFaceRecognizer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLBPHFaceRecognizer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MACE>

pub fn as_raw_PtrOfMACE( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMACE( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PredictCollector>

pub fn as_raw_PtrOfPredictCollector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPredictCollector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<StandardCollector>

pub fn as_raw_PtrOfStandardCollector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfStandardCollector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AKAZE>

pub fn as_raw_PtrOfAKAZE( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAKAZE( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AffineFeature>

pub fn as_raw_PtrOfAffineFeature( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAffineFeature( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AgastFeatureDetector>

pub fn as_raw_PtrOfAgastFeatureDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAgastFeatureDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BFMatcher>

pub fn as_raw_PtrOfBFMatcher( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBFMatcher( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BRISK>

pub fn as_raw_PtrOfBRISK( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBRISK( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DescriptorMatcher>

pub fn as_raw_PtrOfDescriptorMatcher( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDescriptorMatcher( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FastFeatureDetector>

pub fn as_raw_PtrOfFastFeatureDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFastFeatureDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Feature2D>

pub fn as_raw_PtrOfFeature2D( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFeature2D( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FlannBasedMatcher>

pub fn as_raw_PtrOfFlannBasedMatcher( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFlannBasedMatcher( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GFTTDetector>

pub fn as_raw_PtrOfGFTTDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGFTTDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<KAZE>

pub fn as_raw_PtrOfKAZE( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfKAZE( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MSER>

pub fn as_raw_PtrOfMSER( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMSER( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ORB>

pub fn as_raw_PtrOfORB(&self) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfORB( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SIFT>

pub fn as_raw_PtrOfSIFT( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSIFT( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SimpleBlobDetector>

pub fn as_raw_PtrOfSimpleBlobDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSimpleBlobDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AutotunedIndexParams>

pub fn as_raw_PtrOfAutotunedIndexParams( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAutotunedIndexParams( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CompositeIndexParams>

pub fn as_raw_PtrOfCompositeIndexParams( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCompositeIndexParams( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<HierarchicalClusteringIndexParams>

pub fn as_raw_PtrOfHierarchicalClusteringIndexParams( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfHierarchicalClusteringIndexParams( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<IndexParams>

pub fn as_raw_PtrOfIndexParams( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfIndexParams( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<KDTreeIndexParams>

pub fn as_raw_PtrOfKDTreeIndexParams( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfKDTreeIndexParams( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<KMeansIndexParams>

pub fn as_raw_PtrOfKMeansIndexParams( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfKMeansIndexParams( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LinearIndexParams>

pub fn as_raw_PtrOfLinearIndexParams( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLinearIndexParams( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LshIndexParams>

pub fn as_raw_PtrOfLshIndexParams( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLshIndexParams( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SavedIndexParams>

pub fn as_raw_PtrOfSavedIndexParams( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSavedIndexParams( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SearchParams>

pub fn as_raw_PtrOfSearchParams( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSearchParams( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FreeType2>

pub fn as_raw_PtrOfFreeType2( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFreeType2( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<HDF5>

pub fn as_raw_PtrOfHDF5( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfHDF5( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<HfsSegment>

pub fn as_raw_PtrOfHfsSegment( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfHfsSegment( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AverageHash>

pub fn as_raw_PtrOfAverageHash( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAverageHash( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BlockMeanHash>

pub fn as_raw_PtrOfBlockMeanHash( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBlockMeanHash( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ColorMomentHash>

pub fn as_raw_PtrOfColorMomentHash( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfColorMomentHash( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ImgHashBase>

pub fn as_raw_PtrOfImgHashBase( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfImgHashBase( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MarrHildrethHash>

pub fn as_raw_PtrOfMarrHildrethHash( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMarrHildrethHash( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PHash>

pub fn as_raw_PtrOfPHash( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPHash( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RadialVarianceHash>

pub fn as_raw_PtrOfRadialVarianceHash( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRadialVarianceHash( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CLAHE>

pub fn as_raw_PtrOfCLAHE( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCLAHE( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GeneralizedHough>

pub fn as_raw_PtrOfGeneralizedHough( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGeneralizedHough( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GeneralizedHoughBallard>

pub fn as_raw_PtrOfGeneralizedHoughBallard( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGeneralizedHoughBallard( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GeneralizedHoughGuil>

pub fn as_raw_PtrOfGeneralizedHoughGuil( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGeneralizedHoughGuil( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LineSegmentDetector>

pub fn as_raw_PtrOfLineSegmentDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLineSegmentDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BinaryDescriptor>

pub fn as_raw_PtrOfBinaryDescriptor( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBinaryDescriptor( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BinaryDescriptorMatcher>

pub fn as_raw_PtrOfBinaryDescriptorMatcher( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBinaryDescriptorMatcher( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LSDDetector>

pub fn as_raw_PtrOfLSDDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLSDDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MCC_CChecker>

pub fn as_raw_PtrOfMCC_CChecker( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMCC_CChecker( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MCC_CCheckerDetector>

pub fn as_raw_PtrOfMCC_CCheckerDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMCC_CCheckerDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MCC_CCheckerDraw>

pub fn as_raw_PtrOfMCC_CCheckerDraw( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMCC_CCheckerDraw( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MCC_DetectorParameters>

pub fn as_raw_PtrOfMCC_DetectorParameters( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMCC_DetectorParameters( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ANN_MLP>

pub fn as_raw_PtrOfANN_MLP( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfANN_MLP( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Boost>

pub fn as_raw_PtrOfBoost( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBoost( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DTrees>

pub fn as_raw_PtrOfDTrees( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDTrees( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<EM>

pub fn as_raw_PtrOfEM(&self) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfEM( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<KNearest>

pub fn as_raw_PtrOfKNearest( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfKNearest( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LogisticRegression>

pub fn as_raw_PtrOfLogisticRegression( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLogisticRegression( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<NormalBayesClassifier>

pub fn as_raw_PtrOfNormalBayesClassifier( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfNormalBayesClassifier( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ParamGrid>

pub fn as_raw_PtrOfParamGrid( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfParamGrid( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RTrees>

pub fn as_raw_PtrOfRTrees( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRTrees( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SVM>

pub fn as_raw_PtrOfSVM(&self) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSVM( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SVMSGD>

pub fn as_raw_PtrOfSVMSGD( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSVMSGD( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SVM_Kernel>

pub fn as_raw_PtrOfSVM_Kernel( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSVM_Kernel( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<StatModel>

pub fn as_raw_PtrOfStatModel( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfStatModel( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TrainData>

pub fn as_raw_PtrOfTrainData( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTrainData( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ArucoDetector>

pub fn as_raw_PtrOfArucoDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfArucoDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BaseCascadeClassifier>

pub fn as_raw_PtrOfBaseCascadeClassifier( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBaseCascadeClassifier( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BaseCascadeClassifier_MaskGenerator>

pub fn as_raw_PtrOfBaseCascadeClassifier_MaskGenerator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBaseCascadeClassifier_MaskGenerator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Board>

pub fn as_raw_PtrOfBoard( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBoard( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CharucoBoard>

pub fn as_raw_PtrOfCharucoBoard( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCharucoBoard( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CharucoDetector>

pub fn as_raw_PtrOfCharucoDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCharucoDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DetectionBasedTracker_IDetector>

pub fn as_raw_PtrOfDetectionBasedTracker_IDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetectionBasedTracker_IDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DetectorParameters>

pub fn as_raw_PtrOfDetectorParameters( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetectorParameters( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Dictionary>

pub fn as_raw_PtrOfDictionary( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDictionary( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FaceDetectorYN>

pub fn as_raw_PtrOfFaceDetectorYN( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFaceDetectorYN( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FaceRecognizerSF>

pub fn as_raw_PtrOfFaceRecognizerSF( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFaceRecognizerSF( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GridBoard>

pub fn as_raw_PtrOfGridBoard( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGridBoard( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<QRCodeEncoder>

pub fn as_raw_PtrOfQRCodeEncoder( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfQRCodeEncoder( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DenseRLOFOpticalFlow>

pub fn as_raw_PtrOfDenseRLOFOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDenseRLOFOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DualTVL1OpticalFlow>

pub fn as_raw_PtrOfDualTVL1OpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDualTVL1OpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GPCTrainingSamples>

pub fn as_raw_PtrOfGPCTrainingSamples( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGPCTrainingSamples( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GPCTree>

pub fn as_raw_PtrOfGPCTree( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGPCTree( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<OpticalFlowPCAFlow>

pub fn as_raw_PtrOfOpticalFlowPCAFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfOpticalFlowPCAFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PCAPrior>

pub fn as_raw_PtrOfPCAPrior( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPCAPrior( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RLOFOpticalFlowParameter>

pub fn as_raw_PtrOfRLOFOpticalFlowParameter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRLOFOpticalFlowParameter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SparseRLOFOpticalFlow>

pub fn as_raw_PtrOfSparseRLOFOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSparseRLOFOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<WindowScene>

pub fn as_raw_PtrOfWindowScene( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfWindowScene( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<HistogramPhaseUnwrapping>

pub fn as_raw_PtrOfHistogramPhaseUnwrapping( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfHistogramPhaseUnwrapping( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PhaseUnwrapping>

pub fn as_raw_PtrOfPhaseUnwrapping( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPhaseUnwrapping( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AlignExposures>

pub fn as_raw_PtrOfAlignExposures( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAlignExposures( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AlignMTB>

pub fn as_raw_PtrOfAlignMTB( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAlignMTB( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CalibrateCRF>

pub fn as_raw_PtrOfCalibrateCRF( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCalibrateCRF( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CalibrateDebevec>

pub fn as_raw_PtrOfCalibrateDebevec( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCalibrateDebevec( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CalibrateRobertson>

pub fn as_raw_PtrOfCalibrateRobertson( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCalibrateRobertson( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MergeDebevec>

pub fn as_raw_PtrOfMergeDebevec( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMergeDebevec( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MergeExposures>

pub fn as_raw_PtrOfMergeExposures( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMergeExposures( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MergeMertens>

pub fn as_raw_PtrOfMergeMertens( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMergeMertens( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MergeRobertson>

pub fn as_raw_PtrOfMergeRobertson( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMergeRobertson( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Tonemap>

pub fn as_raw_PtrOfTonemap( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTonemap( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TonemapDrago>

pub fn as_raw_PtrOfTonemapDrago( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTonemapDrago( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TonemapMantiuk>

pub fn as_raw_PtrOfTonemapMantiuk( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTonemapMantiuk( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TonemapReinhard>

pub fn as_raw_PtrOfTonemapReinhard( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTonemapReinhard( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Plot2d>

pub fn as_raw_PtrOfPlot2d( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPlot2d( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<QualityBRISQUE>

pub fn as_raw_PtrOfQualityBRISQUE( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfQualityBRISQUE( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<QualityBase>

pub fn as_raw_PtrOfQualityBase( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfQualityBase( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<QualityGMSD>

pub fn as_raw_PtrOfQualityGMSD( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfQualityGMSD( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<QualityMSE>

pub fn as_raw_PtrOfQualityMSE( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfQualityMSE( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<QualityPSNR>

pub fn as_raw_PtrOfQualityPSNR( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfQualityPSNR( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<QualitySSIM>

pub fn as_raw_PtrOfQualitySSIM( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfQualitySSIM( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Rapid_GOSTracker>

pub fn as_raw_PtrOfRapid_GOSTracker( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRapid_GOSTracker( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Rapid_OLSTracker>

pub fn as_raw_PtrOfRapid_OLSTracker( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRapid_OLSTracker( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Rapid_Rapid>

pub fn as_raw_PtrOfRapid_Rapid( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRapid_Rapid( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Rapid_Tracker>

pub fn as_raw_PtrOfRapid_Tracker( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRapid_Tracker( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ColoredKinfu_ColoredKinFu>

pub fn as_raw_PtrOfColoredKinfu_ColoredKinFu( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfColoredKinfu_ColoredKinFu( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ColoredKinfu_Params>

pub fn as_raw_PtrOfColoredKinfu_Params( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfColoredKinfu_Params( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DepthCleaner>

pub fn as_raw_PtrOfDepthCleaner( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDepthCleaner( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Dynafu_DynaFu>

pub fn as_raw_PtrOfDynafu_DynaFu( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDynafu_DynaFu( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FastICPOdometry>

pub fn as_raw_PtrOfFastICPOdometry( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFastICPOdometry( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ICPOdometry>

pub fn as_raw_PtrOfICPOdometry( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfICPOdometry( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Kinfu_Detail_PoseGraph>

pub fn as_raw_PtrOfKinfu_Detail_PoseGraph( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfKinfu_Detail_PoseGraph( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Kinfu_KinFu>

pub fn as_raw_PtrOfKinfu_KinFu( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfKinfu_KinFu( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Kinfu_Params>

pub fn as_raw_PtrOfKinfu_Params( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfKinfu_Params( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Kinfu_Volume>

pub fn as_raw_PtrOfKinfu_Volume( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfKinfu_Volume( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Kinfu_VolumeParams>

pub fn as_raw_PtrOfKinfu_VolumeParams( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfKinfu_VolumeParams( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LargeKinfu>

pub fn as_raw_PtrOfLargeKinfu( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLargeKinfu( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LineMod_ColorGradient>

pub fn as_raw_PtrOfLineMod_ColorGradient( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLineMod_ColorGradient( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LineMod_DepthNormal>

pub fn as_raw_PtrOfLineMod_DepthNormal( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLineMod_DepthNormal( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LineMod_Detector>

pub fn as_raw_PtrOfLineMod_Detector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLineMod_Detector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LineMod_Modality>

pub fn as_raw_PtrOfLineMod_Modality( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLineMod_Modality( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LineMod_QuantizedPyramid>

pub fn as_raw_PtrOfLineMod_QuantizedPyramid( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLineMod_QuantizedPyramid( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Odometry>

pub fn as_raw_PtrOfOdometry( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfOdometry( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<OdometryFrame>

pub fn as_raw_PtrOfOdometryFrame( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfOdometryFrame( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Params>

pub fn as_raw_PtrOfParams( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfParams( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RgbdFrame>

pub fn as_raw_PtrOfRgbdFrame( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRgbdFrame( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RgbdICPOdometry>

pub fn as_raw_PtrOfRgbdICPOdometry( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRgbdICPOdometry( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RgbdNormals>

pub fn as_raw_PtrOfRgbdNormals( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRgbdNormals( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RgbdOdometry>

pub fn as_raw_PtrOfRgbdOdometry( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRgbdOdometry( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RgbdPlane>

pub fn as_raw_PtrOfRgbdPlane( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRgbdPlane( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MotionSaliency>

pub fn as_raw_PtrOfMotionSaliency( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMotionSaliency( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MotionSaliencyBinWangApr2014>

pub fn as_raw_PtrOfMotionSaliencyBinWangApr2014( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMotionSaliencyBinWangApr2014( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Objectness>

pub fn as_raw_PtrOfObjectness( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfObjectness( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ObjectnessBING>

pub fn as_raw_PtrOfObjectnessBING( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfObjectnessBING( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Saliency>

pub fn as_raw_PtrOfSaliency( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSaliency( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<StaticSaliency>

pub fn as_raw_PtrOfStaticSaliency( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfStaticSaliency( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<StaticSaliencyFineGrained>

pub fn as_raw_PtrOfStaticSaliencyFineGrained( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfStaticSaliencyFineGrained( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<StaticSaliencySpectralResidual>

pub fn as_raw_PtrOfStaticSaliencySpectralResidual( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfStaticSaliencySpectralResidual( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BaseSFM>

pub fn as_raw_PtrOfBaseSFM( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBaseSFM( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SFMLibmvEuclideanReconstruction>

pub fn as_raw_PtrOfSFMLibmvEuclideanReconstruction( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSFMLibmvEuclideanReconstruction( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AffineTransformer>

pub fn as_raw_PtrOfAffineTransformer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAffineTransformer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ChiHistogramCostExtractor>

pub fn as_raw_PtrOfChiHistogramCostExtractor( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfChiHistogramCostExtractor( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<EMDHistogramCostExtractor>

pub fn as_raw_PtrOfEMDHistogramCostExtractor( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfEMDHistogramCostExtractor( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<EMDL1HistogramCostExtractor>

pub fn as_raw_PtrOfEMDL1HistogramCostExtractor( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfEMDL1HistogramCostExtractor( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<HausdorffDistanceExtractor>

pub fn as_raw_PtrOfHausdorffDistanceExtractor( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfHausdorffDistanceExtractor( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<HistogramCostExtractor>

pub fn as_raw_PtrOfHistogramCostExtractor( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfHistogramCostExtractor( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<NormHistogramCostExtractor>

pub fn as_raw_PtrOfNormHistogramCostExtractor( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfNormHistogramCostExtractor( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ShapeContextDistanceExtractor>

pub fn as_raw_PtrOfShapeContextDistanceExtractor( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfShapeContextDistanceExtractor( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ShapeDistanceExtractor>

pub fn as_raw_PtrOfShapeDistanceExtractor( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfShapeDistanceExtractor( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ShapeTransformer>

pub fn as_raw_PtrOfShapeTransformer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfShapeTransformer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ThinPlateSplineShapeTransformer>

pub fn as_raw_PtrOfThinPlateSplineShapeTransformer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfThinPlateSplineShapeTransformer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<QuasiDenseStereo>

pub fn as_raw_PtrOfQuasiDenseStereo( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfQuasiDenseStereo( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AffineWarper>

pub fn as_raw_PtrOfAffineWarper( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAffineWarper( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CompressedRectilinearPortraitWarper>

pub fn as_raw_PtrOfCompressedRectilinearPortraitWarper( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCompressedRectilinearPortraitWarper( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CompressedRectilinearWarper>

pub fn as_raw_PtrOfCompressedRectilinearWarper( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCompressedRectilinearWarper( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CylindricalWarper>

pub fn as_raw_PtrOfCylindricalWarper( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCylindricalWarper( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<CylindricalWarperGpu>

pub fn as_raw_PtrOfCylindricalWarperGpu( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfCylindricalWarperGpu( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_AffineBasedEstimator>

pub fn as_raw_PtrOfDetail_AffineBasedEstimator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_AffineBasedEstimator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_AffineBestOf2NearestMatcher>

pub fn as_raw_PtrOfDetail_AffineBestOf2NearestMatcher( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_AffineBestOf2NearestMatcher( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_BestOf2NearestMatcher>

pub fn as_raw_PtrOfDetail_BestOf2NearestMatcher( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_BestOf2NearestMatcher( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_BestOf2NearestRangeMatcher>

pub fn as_raw_PtrOfDetail_BestOf2NearestRangeMatcher( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_BestOf2NearestRangeMatcher( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_Blender>

pub fn as_raw_PtrOfDetail_Blender( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_Blender( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_BlocksChannelsCompensator>

pub fn as_raw_PtrOfDetail_BlocksChannelsCompensator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_BlocksChannelsCompensator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_BlocksCompensator>

pub fn as_raw_PtrOfDetail_BlocksCompensator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_BlocksCompensator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_BlocksGainCompensator>

pub fn as_raw_PtrOfDetail_BlocksGainCompensator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_BlocksGainCompensator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_BundleAdjusterAffine>

pub fn as_raw_PtrOfDetail_BundleAdjusterAffine( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_BundleAdjusterAffine( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_BundleAdjusterAffinePartial>

pub fn as_raw_PtrOfDetail_BundleAdjusterAffinePartial( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_BundleAdjusterAffinePartial( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_BundleAdjusterBase>

pub fn as_raw_PtrOfDetail_BundleAdjusterBase( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_BundleAdjusterBase( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_BundleAdjusterRay>

pub fn as_raw_PtrOfDetail_BundleAdjusterRay( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_BundleAdjusterRay( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_BundleAdjusterReproj>

pub fn as_raw_PtrOfDetail_BundleAdjusterReproj( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_BundleAdjusterReproj( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_ChannelsCompensator>

pub fn as_raw_PtrOfDetail_ChannelsCompensator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_ChannelsCompensator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_DpSeamFinder>

pub fn as_raw_PtrOfDetail_DpSeamFinder( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_DpSeamFinder( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_Estimator>

pub fn as_raw_PtrOfDetail_Estimator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_Estimator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_ExposureCompensator>

pub fn as_raw_PtrOfDetail_ExposureCompensator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_ExposureCompensator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_FeatherBlender>

pub fn as_raw_PtrOfDetail_FeatherBlender( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_FeatherBlender( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_FeaturesMatcher>

pub fn as_raw_PtrOfDetail_FeaturesMatcher( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_FeaturesMatcher( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_GainCompensator>

pub fn as_raw_PtrOfDetail_GainCompensator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_GainCompensator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_GraphCutSeamFinder>

pub fn as_raw_PtrOfDetail_GraphCutSeamFinder( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_GraphCutSeamFinder( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_GraphCutSeamFinderBase>

pub fn as_raw_PtrOfDetail_GraphCutSeamFinderBase( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_GraphCutSeamFinderBase( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_GraphCutSeamFinderGpu>

pub fn as_raw_PtrOfDetail_GraphCutSeamFinderGpu( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_GraphCutSeamFinderGpu( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_HomographyBasedEstimator>

pub fn as_raw_PtrOfDetail_HomographyBasedEstimator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_HomographyBasedEstimator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_MultiBandBlender>

pub fn as_raw_PtrOfDetail_MultiBandBlender( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_MultiBandBlender( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_NoBundleAdjuster>

pub fn as_raw_PtrOfDetail_NoBundleAdjuster( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_NoBundleAdjuster( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_NoExposureCompensator>

pub fn as_raw_PtrOfDetail_NoExposureCompensator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_NoExposureCompensator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_NoSeamFinder>

pub fn as_raw_PtrOfDetail_NoSeamFinder( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_NoSeamFinder( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_PairwiseSeamFinder>

pub fn as_raw_PtrOfDetail_PairwiseSeamFinder( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_PairwiseSeamFinder( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_RotationWarper>

pub fn as_raw_PtrOfDetail_RotationWarper( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_RotationWarper( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_SeamFinder>

pub fn as_raw_PtrOfDetail_SeamFinder( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_SeamFinder( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Detail_VoronoiSeamFinder>

pub fn as_raw_PtrOfDetail_VoronoiSeamFinder( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDetail_VoronoiSeamFinder( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FisheyeWarper>

pub fn as_raw_PtrOfFisheyeWarper( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFisheyeWarper( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MercatorWarper>

pub fn as_raw_PtrOfMercatorWarper( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMercatorWarper( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PaniniPortraitWarper>

pub fn as_raw_PtrOfPaniniPortraitWarper( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPaniniPortraitWarper( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PaniniWarper>

pub fn as_raw_PtrOfPaniniWarper( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPaniniWarper( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PlaneWarper>

pub fn as_raw_PtrOfPlaneWarper( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPlaneWarper( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PlaneWarperGpu>

pub fn as_raw_PtrOfPlaneWarperGpu( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPlaneWarperGpu( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SphericalWarper>

pub fn as_raw_PtrOfSphericalWarper( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSphericalWarper( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SphericalWarperGpu>

pub fn as_raw_PtrOfSphericalWarperGpu( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSphericalWarperGpu( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<StereographicWarper>

pub fn as_raw_PtrOfStereographicWarper( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfStereographicWarper( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Stitcher>

pub fn as_raw_PtrOfStitcher( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfStitcher( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TransverseMercatorWarper>

pub fn as_raw_PtrOfTransverseMercatorWarper( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTransverseMercatorWarper( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<WarperCreator>

pub fn as_raw_PtrOfWarperCreator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfWarperCreator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GrayCodePattern>

pub fn as_raw_PtrOfGrayCodePattern( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGrayCodePattern( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SinusoidalPattern>

pub fn as_raw_PtrOfSinusoidalPattern( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSinusoidalPattern( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SinusoidalPattern_Params>

pub fn as_raw_PtrOfSinusoidalPattern_Params( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSinusoidalPattern_Params( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<StructuredLightPattern>

pub fn as_raw_PtrOfStructuredLightPattern( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfStructuredLightPattern( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SuperRes_BroxOpticalFlow>

pub fn as_raw_PtrOfSuperRes_BroxOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSuperRes_BroxOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SuperRes_DenseOpticalFlowExt>

pub fn as_raw_PtrOfSuperRes_DenseOpticalFlowExt( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSuperRes_DenseOpticalFlowExt( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SuperRes_DualTVL1OpticalFlow>

pub fn as_raw_PtrOfSuperRes_DualTVL1OpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSuperRes_DualTVL1OpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SuperRes_FarnebackOpticalFlow>

pub fn as_raw_PtrOfSuperRes_FarnebackOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSuperRes_FarnebackOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SuperRes_FrameSource>

pub fn as_raw_PtrOfSuperRes_FrameSource( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSuperRes_FrameSource( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SuperRes_PyrLKOpticalFlow>

pub fn as_raw_PtrOfSuperRes_PyrLKOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSuperRes_PyrLKOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SuperRes_SuperResolution>

pub fn as_raw_PtrOfSuperRes_SuperResolution( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSuperRes_SuperResolution( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Pose3D>

pub fn as_raw_PtrOfPose3D( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPose3D( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PoseCluster3D>

pub fn as_raw_PtrOfPoseCluster3D( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPoseCluster3D( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BaseOCR>

pub fn as_raw_PtrOfBaseOCR( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBaseOCR( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ERFilter>

pub fn as_raw_PtrOfERFilter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfERFilter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ERFilter_Callback>

pub fn as_raw_PtrOfERFilter_Callback( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfERFilter_Callback( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<OCRBeamSearchDecoder>

pub fn as_raw_PtrOfOCRBeamSearchDecoder( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfOCRBeamSearchDecoder( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<OCRBeamSearchDecoder_ClassifierCallback>

pub fn as_raw_PtrOfOCRBeamSearchDecoder_ClassifierCallback( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfOCRBeamSearchDecoder_ClassifierCallback( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<OCRHMMDecoder>

pub fn as_raw_PtrOfOCRHMMDecoder( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfOCRHMMDecoder( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<OCRHMMDecoder_ClassifierCallback>

pub fn as_raw_PtrOfOCRHMMDecoder_ClassifierCallback( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfOCRHMMDecoder_ClassifierCallback( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<OCRHolisticWordRecognizer>

pub fn as_raw_PtrOfOCRHolisticWordRecognizer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfOCRHolisticWordRecognizer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<OCRTesseract>

pub fn as_raw_PtrOfOCRTesseract( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfOCRTesseract( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TextDetector>

pub fn as_raw_PtrOfTextDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTextDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TextDetectorCNN>

pub fn as_raw_PtrOfTextDetectorCNN( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTextDetectorCNN( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TrackerCSRT>

pub fn as_raw_PtrOfTrackerCSRT( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTrackerCSRT( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TrackerKCF>

pub fn as_raw_PtrOfTrackerKCF( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTrackerKCF( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BackgroundSubtractor>

pub fn as_raw_PtrOfBackgroundSubtractor( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBackgroundSubtractor( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BackgroundSubtractorKNN>

pub fn as_raw_PtrOfBackgroundSubtractorKNN( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBackgroundSubtractorKNN( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BackgroundSubtractorMOG2>

pub fn as_raw_PtrOfBackgroundSubtractorMOG2( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBackgroundSubtractorMOG2( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DISOpticalFlow>

pub fn as_raw_PtrOfDISOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDISOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DenseOpticalFlow>

pub fn as_raw_PtrOfDenseOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDenseOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FarnebackOpticalFlow>

pub fn as_raw_PtrOfFarnebackOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFarnebackOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SparseOpticalFlow>

pub fn as_raw_PtrOfSparseOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSparseOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SparsePyrLKOpticalFlow>

pub fn as_raw_PtrOfSparsePyrLKOpticalFlow( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSparsePyrLKOpticalFlow( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<Tracker>

pub fn as_raw_PtrOfTracker( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTracker( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TrackerDaSiamRPN>

pub fn as_raw_PtrOfTrackerDaSiamRPN( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTrackerDaSiamRPN( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TrackerGOTURN>

pub fn as_raw_PtrOfTrackerGOTURN( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTrackerGOTURN( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TrackerMIL>

pub fn as_raw_PtrOfTrackerMIL( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTrackerMIL( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TrackerNano>

pub fn as_raw_PtrOfTrackerNano( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTrackerNano( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TrackerVit>

pub fn as_raw_PtrOfTrackerVit( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTrackerVit( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<VariationalRefinement>

pub fn as_raw_PtrOfVariationalRefinement( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfVariationalRefinement( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ColorAverageInpainter>

pub fn as_raw_PtrOfColorAverageInpainter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfColorAverageInpainter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ColorInpainter>

pub fn as_raw_PtrOfColorInpainter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfColorInpainter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ConsistentMosaicInpainter>

pub fn as_raw_PtrOfConsistentMosaicInpainter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfConsistentMosaicInpainter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DeblurerBase>

pub fn as_raw_PtrOfDeblurerBase( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDeblurerBase( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DensePyrLkOptFlowEstimatorGpu>

pub fn as_raw_PtrOfDensePyrLkOptFlowEstimatorGpu( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDensePyrLkOptFlowEstimatorGpu( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FromFileMotionReader>

pub fn as_raw_PtrOfFromFileMotionReader( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFromFileMotionReader( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GaussianMotionFilter>

pub fn as_raw_PtrOfGaussianMotionFilter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGaussianMotionFilter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<IDenseOptFlowEstimator>

pub fn as_raw_PtrOfIDenseOptFlowEstimator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfIDenseOptFlowEstimator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<IFrameSource>

pub fn as_raw_PtrOfIFrameSource( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfIFrameSource( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ILog>

pub fn as_raw_PtrOfILog( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfILog( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<IMotionStabilizer>

pub fn as_raw_PtrOfIMotionStabilizer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfIMotionStabilizer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<IOutlierRejector>

pub fn as_raw_PtrOfIOutlierRejector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfIOutlierRejector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ISparseOptFlowEstimator>

pub fn as_raw_PtrOfISparseOptFlowEstimator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfISparseOptFlowEstimator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ImageMotionEstimatorBase>

pub fn as_raw_PtrOfImageMotionEstimatorBase( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfImageMotionEstimatorBase( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<InpainterBase>

pub fn as_raw_PtrOfInpainterBase( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfInpainterBase( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<InpaintingPipeline>

pub fn as_raw_PtrOfInpaintingPipeline( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfInpaintingPipeline( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<KeypointBasedMotionEstimator>

pub fn as_raw_PtrOfKeypointBasedMotionEstimator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfKeypointBasedMotionEstimator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<KeypointBasedMotionEstimatorGpu>

pub fn as_raw_PtrOfKeypointBasedMotionEstimatorGpu( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfKeypointBasedMotionEstimatorGpu( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LogToStdout>

pub fn as_raw_PtrOfLogToStdout( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLogToStdout( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LpMotionStabilizer>

pub fn as_raw_PtrOfLpMotionStabilizer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLpMotionStabilizer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MaskFrameSource>

pub fn as_raw_PtrOfMaskFrameSource( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMaskFrameSource( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MoreAccurateMotionWobbleSuppressor>

pub fn as_raw_PtrOfMoreAccurateMotionWobbleSuppressor( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMoreAccurateMotionWobbleSuppressor( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MoreAccurateMotionWobbleSuppressorBase>

pub fn as_raw_PtrOfMoreAccurateMotionWobbleSuppressorBase( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMoreAccurateMotionWobbleSuppressorBase( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MoreAccurateMotionWobbleSuppressorGpu>

pub fn as_raw_PtrOfMoreAccurateMotionWobbleSuppressorGpu( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMoreAccurateMotionWobbleSuppressorGpu( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MotionEstimatorBase>

pub fn as_raw_PtrOfMotionEstimatorBase( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMotionEstimatorBase( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MotionEstimatorL1>

pub fn as_raw_PtrOfMotionEstimatorL1( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMotionEstimatorL1( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MotionEstimatorRansacL2>

pub fn as_raw_PtrOfMotionEstimatorRansacL2( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMotionEstimatorRansacL2( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MotionFilterBase>

pub fn as_raw_PtrOfMotionFilterBase( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMotionFilterBase( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MotionInpainter>

pub fn as_raw_PtrOfMotionInpainter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMotionInpainter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MotionStabilizationPipeline>

pub fn as_raw_PtrOfMotionStabilizationPipeline( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMotionStabilizationPipeline( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<NullDeblurer>

pub fn as_raw_PtrOfNullDeblurer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfNullDeblurer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<NullFrameSource>

pub fn as_raw_PtrOfNullFrameSource( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfNullFrameSource( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<NullInpainter>

pub fn as_raw_PtrOfNullInpainter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfNullInpainter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<NullLog>

pub fn as_raw_PtrOfNullLog( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfNullLog( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<NullOutlierRejector>

pub fn as_raw_PtrOfNullOutlierRejector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfNullOutlierRejector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<NullWobbleSuppressor>

pub fn as_raw_PtrOfNullWobbleSuppressor( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfNullWobbleSuppressor( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<OnePassStabilizer>

pub fn as_raw_PtrOfOnePassStabilizer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfOnePassStabilizer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PyrLkOptFlowEstimatorBase>

pub fn as_raw_PtrOfPyrLkOptFlowEstimatorBase( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPyrLkOptFlowEstimatorBase( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SparsePyrLkOptFlowEstimator>

pub fn as_raw_PtrOfSparsePyrLkOptFlowEstimator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSparsePyrLkOptFlowEstimator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SparsePyrLkOptFlowEstimatorGpu>

pub fn as_raw_PtrOfSparsePyrLkOptFlowEstimatorGpu( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSparsePyrLkOptFlowEstimatorGpu( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<StabilizerBase>

pub fn as_raw_PtrOfStabilizerBase( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfStabilizerBase( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ToFileMotionWriter>

pub fn as_raw_PtrOfToFileMotionWriter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfToFileMotionWriter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TranslationBasedLocalOutlierRejector>

pub fn as_raw_PtrOfTranslationBasedLocalOutlierRejector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTranslationBasedLocalOutlierRejector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TwoPassStabilizer>

pub fn as_raw_PtrOfTwoPassStabilizer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTwoPassStabilizer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<VideoFileSource>

pub fn as_raw_PtrOfVideoFileSource( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfVideoFileSource( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<WeightingDeblurer>

pub fn as_raw_PtrOfWeightingDeblurer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfWeightingDeblurer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<WobbleSuppressorBase>

pub fn as_raw_PtrOfWobbleSuppressorBase( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfWobbleSuppressorBase( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AffineFeature2D>

pub fn as_raw_PtrOfAffineFeature2D( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAffineFeature2D( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BEBLID>

pub fn as_raw_PtrOfBEBLID( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBEBLID( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BoostDesc>

pub fn as_raw_PtrOfBoostDesc( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBoostDesc( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<BriefDescriptorExtractor>

pub fn as_raw_PtrOfBriefDescriptorExtractor( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfBriefDescriptorExtractor( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DAISY>

pub fn as_raw_PtrOfDAISY( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDAISY( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FREAK>

pub fn as_raw_PtrOfFREAK( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFREAK( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<HarrisLaplaceFeatureDetector>

pub fn as_raw_PtrOfHarrisLaplaceFeatureDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfHarrisLaplaceFeatureDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LATCH>

pub fn as_raw_PtrOfLATCH( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLATCH( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LUCID>

pub fn as_raw_PtrOfLUCID( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLUCID( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<MSDDetector>

pub fn as_raw_PtrOfMSDDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfMSDDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PCTSignatures>

pub fn as_raw_PtrOfPCTSignatures( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPCTSignatures( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<PCTSignaturesSQFD>

pub fn as_raw_PtrOfPCTSignaturesSQFD( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfPCTSignaturesSQFD( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SURF>

pub fn as_raw_PtrOfSURF( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSURF( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SURF_CUDA>

pub fn as_raw_PtrOfSURF_CUDA( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSURF_CUDA( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<StarDetector>

pub fn as_raw_PtrOfStarDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfStarDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TBMR>

pub fn as_raw_PtrOfTBMR( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTBMR( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TEBLID>

pub fn as_raw_PtrOfTEBLID( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTEBLID( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<VGG>

pub fn as_raw_PtrOfVGG(&self) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfVGG( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<AdaptiveManifoldFilter>

pub fn as_raw_PtrOfAdaptiveManifoldFilter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfAdaptiveManifoldFilter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ContourFitting>

pub fn as_raw_PtrOfContourFitting( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfContourFitting( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DTFilter>

pub fn as_raw_PtrOfDTFilter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDTFilter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DisparityFilter>

pub fn as_raw_PtrOfDisparityFilter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDisparityFilter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<DisparityWLSFilter>

pub fn as_raw_PtrOfDisparityWLSFilter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfDisparityWLSFilter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<EdgeAwareInterpolator>

pub fn as_raw_PtrOfEdgeAwareInterpolator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfEdgeAwareInterpolator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<EdgeBoxes>

pub fn as_raw_PtrOfEdgeBoxes( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfEdgeBoxes( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<EdgeDrawing>

pub fn as_raw_PtrOfEdgeDrawing( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfEdgeDrawing( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FastBilateralSolverFilter>

pub fn as_raw_PtrOfFastBilateralSolverFilter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFastBilateralSolverFilter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FastGlobalSmootherFilter>

pub fn as_raw_PtrOfFastGlobalSmootherFilter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFastGlobalSmootherFilter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<FastLineDetector>

pub fn as_raw_PtrOfFastLineDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfFastLineDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GraphSegmentation>

pub fn as_raw_PtrOfGraphSegmentation( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGraphSegmentation( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GuidedFilter>

pub fn as_raw_PtrOfGuidedFilter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGuidedFilter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RFFeatureGetter>

pub fn as_raw_PtrOfRFFeatureGetter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRFFeatureGetter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RICInterpolator>

pub fn as_raw_PtrOfRICInterpolator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRICInterpolator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<RidgeDetectionFilter>

pub fn as_raw_PtrOfRidgeDetectionFilter( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfRidgeDetectionFilter( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<ScanSegment>

pub fn as_raw_PtrOfScanSegment( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfScanSegment( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SelectiveSearchSegmentation>

pub fn as_raw_PtrOfSelectiveSearchSegmentation( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSelectiveSearchSegmentation( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SelectiveSearchSegmentationStrategy>

pub fn as_raw_PtrOfSelectiveSearchSegmentationStrategy( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSelectiveSearchSegmentationStrategy( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SelectiveSearchSegmentationStrategyColor>

pub fn as_raw_PtrOfSelectiveSearchSegmentationStrategyColor( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSelectiveSearchSegmentationStrategyColor( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SelectiveSearchSegmentationStrategyFill>

pub fn as_raw_PtrOfSelectiveSearchSegmentationStrategyFill( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSelectiveSearchSegmentationStrategyFill( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SelectiveSearchSegmentationStrategyMultiple>

pub fn as_raw_PtrOfSelectiveSearchSegmentationStrategyMultiple( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSelectiveSearchSegmentationStrategyMultiple( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SelectiveSearchSegmentationStrategySize>

pub fn as_raw_PtrOfSelectiveSearchSegmentationStrategySize( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSelectiveSearchSegmentationStrategySize( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SelectiveSearchSegmentationStrategyTexture>

pub fn as_raw_PtrOfSelectiveSearchSegmentationStrategyTexture( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSelectiveSearchSegmentationStrategyTexture( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SparseMatchInterpolator>

pub fn as_raw_PtrOfSparseMatchInterpolator( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSparseMatchInterpolator( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<StructuredEdgeDetection>

pub fn as_raw_PtrOfStructuredEdgeDetection( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfStructuredEdgeDetection( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SuperpixelLSC>

pub fn as_raw_PtrOfSuperpixelLSC( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSuperpixelLSC( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SuperpixelSEEDS>

pub fn as_raw_PtrOfSuperpixelSEEDS( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSuperpixelSEEDS( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SuperpixelSLIC>

pub fn as_raw_PtrOfSuperpixelSLIC( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSuperpixelSLIC( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<WBDetector>

pub fn as_raw_PtrOfWBDetector( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfWBDetector( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<GrayworldWB>

pub fn as_raw_PtrOfGrayworldWB( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfGrayworldWB( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<LearningBasedWB>

pub fn as_raw_PtrOfLearningBasedWB( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfLearningBasedWB( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<SimpleWB>

pub fn as_raw_PtrOfSimpleWB( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfSimpleWB( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<TonemapDurand>

pub fn as_raw_PtrOfTonemapDurand( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfTonemapDurand( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

impl Ptr<WhiteBalancer>

pub fn as_raw_PtrOfWhiteBalancer( &self ) -> <Self as OpenCVTypeExternContainer>::ExternSend

pub fn as_raw_mut_PtrOfWhiteBalancer( &mut self ) -> <Self as OpenCVTypeExternContainer>::ExternSendMut

Methods from Deref<Target = f32>

pub const RADIX: u32 = 2u32

pub const MANTISSA_DIGITS: u32 = 24u32

pub const DIGITS: u32 = 6u32

pub const EPSILON: f32 = 1.1920929E-7f32

pub const MIN: f32 = -3.40282347E+38f32

pub const MIN_POSITIVE: f32 = 1.17549435E-38f32

pub const MAX: f32 = 3.40282347E+38f32

pub const MIN_EXP: i32 = -125i32

pub const MAX_EXP: i32 = 128i32

pub const MIN_10_EXP: i32 = -37i32

pub const MAX_10_EXP: i32 = 38i32

pub const NAN: f32 = NaN_f32

pub const INFINITY: f32 = +Inf_f32

pub const NEG_INFINITY: f32 = -Inf_f32

pub fn total_cmp(&self, other: &f32) -> Ordering

Return the ordering between self and other.

Unlike the standard partial comparison between floating point numbers, this comparison always produces an ordering in accordance to the totalOrder predicate as defined in the IEEE 754 (2008 revision) floating point standard. The values are ordered in the following sequence:

• negative quiet NaN
• negative signaling NaN
• negative infinity
• negative numbers
• negative subnormal numbers
• negative zero
• positive zero
• positive subnormal numbers
• positive numbers
• positive infinity
• positive signaling NaN
• positive quiet NaN.

The ordering established by this function does not always agree with the PartialOrd and PartialEq implementations of f32. For example, they consider negative and positive zero equal, while total_cmp doesn’t.

The interpretation of the signaling NaN bit follows the definition in the IEEE 754 standard, which may not match the interpretation by some of the older, non-conformant (e.g. MIPS) hardware implementations.

Example

struct GoodBoy {
    name: String,
    weight: f32,
}

let mut bois = vec![
    GoodBoy { name: "Pucci".to_owned(), weight: 0.1 },
    GoodBoy { name: "Woofer".to_owned(), weight: 99.0 },
    GoodBoy { name: "Yapper".to_owned(), weight: 10.0 },
    GoodBoy { name: "Chonk".to_owned(), weight: f32::INFINITY },
    GoodBoy { name: "Abs. Unit".to_owned(), weight: f32::NAN },
    GoodBoy { name: "Floaty".to_owned(), weight: -5.0 },
];

bois.sort_by(|a, b| a.weight.total_cmp(&b.weight));

// `f32::NAN` could be positive or negative, which will affect the sort order.
if f32::NAN.is_sign_negative() {
    assert!(bois.into_iter().map(|b| b.weight)
        .zip([f32::NAN, -5.0, 0.1, 10.0, 99.0, f32::INFINITY].iter())
        .all(|(a, b)| a.to_bits() == b.to_bits()))
} else {
    assert!(bois.into_iter().map(|b| b.weight)
        .zip([-5.0, 0.1, 10.0, 99.0, f32::INFINITY, f32::NAN].iter())
        .all(|(a, b)| a.to_bits() == b.to_bits()))
}

Trait Implementations

impl AKAZETrait for Ptr<AKAZE>

fn as_raw_mut_AKAZE(&mut self) -> *mut c_void

fn set_descriptor_type(&mut self, dtype: AKAZE_DescriptorType) -> Result<()>

fn set_descriptor_size(&mut self, dsize: i32) -> Result<()>

fn set_descriptor_channels(&mut self, dch: i32) -> Result<()>

fn set_threshold(&mut self, threshold: f64) -> Result<()>

fn set_n_octaves(&mut self, octaves: i32) -> Result<()>

fn set_n_octave_layers(&mut self, octave_layers: i32) -> Result<()>

fn set_diffusivity(&mut self, diff: KAZE_DiffusivityType) -> Result<()>

fn set_max_points(&mut self, max_points: i32) -> Result<()>

impl AKAZETraitConst for Ptr<AKAZE>

fn as_raw_AKAZE(&self) -> *const c_void

fn get_descriptor_type(&self) -> Result<AKAZE_DescriptorType>

fn get_descriptor_size(&self) -> Result<i32>

fn get_descriptor_channels(&self) -> Result<i32>

fn get_threshold(&self) -> Result<f64>

fn get_n_octaves(&self) -> Result<i32>

fn get_n_octave_layers(&self) -> Result<i32>

fn get_diffusivity(&self) -> Result<KAZE_DiffusivityType>

fn get_default_name(&self) -> Result<String>

fn get_max_points(&self) -> Result<i32>

impl ANN_MLPTrait for Ptr<ANN_MLP>

fn as_raw_mut_ANN_MLP(&mut self) -> *mut c_void

fn set_train_method( &mut self, method: i32, param1: f64, param2: f64 ) -> Result<()>

Sets training method and common parameters.

fn set_train_method_def(&mut self, method: i32) -> Result<()>

Sets training method and common parameters.

fn set_activation_function( &mut self, typ: i32, param1: f64, param2: f64 ) -> Result<()>

Initialize the activation function for each neuron. Currently the default and the only fully supported activation function is ANN_MLP::SIGMOID_SYM.

fn set_activation_function_def(&mut self, typ: i32) -> Result<()>

Initialize the activation function for each neuron. Currently the default and the only fully supported activation function is ANN_MLP::SIGMOID_SYM.

fn set_layer_sizes(&mut self, _layer_sizes: &impl ToInputArray) -> Result<()>

Integer vector specifying the number of neurons in each layer including the input and output layers. The very first element specifies the number of elements in the input layer. The last element - number of elements in the output layer. Default value is empty Mat.

fn set_term_criteria(&mut self, val: TermCriteria) -> Result<()>

Termination criteria of the training algorithm. You can specify the maximum number of iterations (maxCount) and/or how much the error could change between the iterations to make the algorithm continue (epsilon). Default value is TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 1000, 0.01).

fn set_backprop_weight_scale(&mut self, val: f64) -> Result<()>

BPROP: Strength of the weight gradient term. The recommended value is about 0.1. Default value is 0.1.

fn set_backprop_momentum_scale(&mut self, val: f64) -> Result<()>

BPROP: Strength of the momentum term (the difference between weights on the 2 previous iterations). This parameter provides some inertia to smooth the random fluctuations of the weights. It can vary from 0 (the feature is disabled) to 1 and beyond. The value 0.1 or so is good enough. Default value is 0.1.

fn set_rprop_dw0(&mut self, val: f64) -> Result<()>

RPROP: Initial value inline formula of update-values inline formula. Default value is 0.1.

fn set_rprop_dw_plus(&mut self, val: f64) -> Result<()>

RPROP: Increase factor inline formula. It must be >1. Default value is 1.2.

fn set_rprop_dw_minus(&mut self, val: f64) -> Result<()>

RPROP: Decrease factor inline formula. It must be <1. Default value is 0.5.

fn set_rprop_dw_min(&mut self, val: f64) -> Result<()>

RPROP: Update-values lower limit inline formula. It must be positive. Default value is FLT_EPSILON.

fn set_rprop_dw_max(&mut self, val: f64) -> Result<()>

RPROP: Update-values upper limit inline formula. It must be >1. Default value is 50.

fn set_anneal_initial_t(&mut self, val: f64) -> Result<()>

ANNEAL: Update initial temperature. It must be >=0. Default value is 10.

fn set_anneal_final_t(&mut self, val: f64) -> Result<()>

ANNEAL: Update final temperature. It must be >=0 and less than initialT. Default value is 0.1.

fn set_anneal_cooling_ratio(&mut self, val: f64) -> Result<()>

ANNEAL: Update cooling ratio. It must be >0 and less than 1. Default value is 0.95.

fn set_anneal_ite_per_step(&mut self, val: i32) -> Result<()>

ANNEAL: Update iteration per step. It must be >0 . Default value is 10.

fn set_anneal_energy_rng(&mut self, rng: &impl RNGTraitConst) -> Result<()>

Set/initialize anneal RNG

impl ANN_MLPTraitConst for Ptr<ANN_MLP>

fn as_raw_ANN_MLP(&self) -> *const c_void

fn get_train_method(&self) -> Result<i32>

Returns current training method

fn get_layer_sizes(&self) -> Result<Mat>

Integer vector specifying the number of neurons in each layer including the input and output layers. The very first element specifies the number of elements in the input layer. The last element - number of elements in the output layer.

fn get_term_criteria(&self) -> Result<TermCriteria>

Termination criteria of the training algorithm. You can specify the maximum number of iterations (maxCount) and/or how much the error could change between the iterations to make the algorithm continue (epsilon). Default value is TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 1000, 0.01).

fn get_backprop_weight_scale(&self) -> Result<f64>

BPROP: Strength of the weight gradient term. The recommended value is about 0.1. Default value is 0.1.

fn get_backprop_momentum_scale(&self) -> Result<f64>

BPROP: Strength of the momentum term (the difference between weights on the 2 previous iterations). This parameter provides some inertia to smooth the random fluctuations of the weights. It can vary from 0 (the feature is disabled) to 1 and beyond. The value 0.1 or so is good enough. Default value is 0.1.

fn get_rprop_dw0(&self) -> Result<f64>

RPROP: Initial value inline formula of update-values inline formula. Default value is 0.1.

fn get_rprop_dw_plus(&self) -> Result<f64>

RPROP: Increase factor inline formula. It must be >1. Default value is 1.2.

fn get_rprop_dw_minus(&self) -> Result<f64>

RPROP: Decrease factor inline formula. It must be <1. Default value is 0.5.

fn get_rprop_dw_min(&self) -> Result<f64>

RPROP: Update-values lower limit inline formula. It must be positive. Default value is FLT_EPSILON.

fn get_rprop_dw_max(&self) -> Result<f64>

RPROP: Update-values upper limit inline formula. It must be >1. Default value is 50.

fn get_anneal_initial_t(&self) -> Result<f64>

ANNEAL: Update initial temperature. It must be >=0. Default value is 10.

fn get_anneal_final_t(&self) -> Result<f64>

ANNEAL: Update final temperature. It must be >=0 and less than initialT. Default value is 0.1.

fn get_anneal_cooling_ratio(&self) -> Result<f64>

ANNEAL: Update cooling ratio. It must be >0 and less than 1. Default value is 0.95.

fn get_anneal_ite_per_step(&self) -> Result<i32>

ANNEAL: Update iteration per step. It must be >0 . Default value is 10.

fn get_weights(&self, layer_idx: i32) -> Result<Mat>

impl AbsLayerTrait for Ptr<AbsLayer>

fn as_raw_mut_AbsLayer(&mut self) -> *mut c_void

impl AbsLayerTraitConst for Ptr<AbsLayer>

fn as_raw_AbsLayer(&self) -> *const c_void

impl AccumLayerTrait for Ptr<AccumLayer>

fn as_raw_mut_AccumLayer(&mut self) -> *mut c_void

impl AccumLayerTraitConst for Ptr<AccumLayer>

fn as_raw_AccumLayer(&self) -> *const c_void

impl AcosLayerTrait for Ptr<AcosLayer>

fn as_raw_mut_AcosLayer(&mut self) -> *mut c_void

impl AcosLayerTraitConst for Ptr<AcosLayer>

fn as_raw_AcosLayer(&self) -> *const c_void

impl AcoshLayerTrait for Ptr<AcoshLayer>

fn as_raw_mut_AcoshLayer(&mut self) -> *mut c_void

impl AcoshLayerTraitConst for Ptr<AcoshLayer>

fn as_raw_AcoshLayer(&self) -> *const c_void

impl ActivationLayerInt8Trait for Ptr<ActivationLayerInt8>

fn as_raw_mut_ActivationLayerInt8(&mut self) -> *mut c_void

impl ActivationLayerInt8TraitConst for Ptr<ActivationLayerInt8>

fn as_raw_ActivationLayerInt8(&self) -> *const c_void

impl ActivationLayerTrait for Ptr<AbsLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<AcosLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<AcoshLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<ActivationLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<ActivationLayerInt8>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<AsinLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<AsinhLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<AtanLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<AtanhLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<BNLLLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<BatchNormLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<BatchNormLayerInt8>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<CeilLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<CeluLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<ChannelsPReLULayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<CosLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<CoshLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<ELULayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<ErfLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<ExpLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<FloorLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<GeluApproximationLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<GeluLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<HardSigmoidLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<HardSwishLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<LogLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<MishLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<NotLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<PowerLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<ReLU6Layer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<ReLULayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<ReciprocalLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<RoundLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<SeluLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<ShrinkLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<SigmoidLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<SignLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<SinLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<SinhLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<SoftplusLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<SoftsignLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<SqrtLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<SwishLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<TanHLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<TanLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTrait for Ptr<ThresholdedReluLayer>

fn as_raw_mut_ActivationLayer(&mut self) -> *mut c_void

impl ActivationLayerTraitConst for Ptr<AbsLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<AcosLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<AcoshLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<ActivationLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<ActivationLayerInt8>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<AsinLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<AsinhLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<AtanLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<AtanhLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<BNLLLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<BatchNormLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<BatchNormLayerInt8>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<CeilLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<CeluLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<ChannelsPReLULayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<CosLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<CoshLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<ELULayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<ErfLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<ExpLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<FloorLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<GeluApproximationLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<GeluLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<HardSigmoidLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<HardSwishLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<LogLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<MishLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<NotLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<PowerLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<ReLU6Layer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<ReLULayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<ReciprocalLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<RoundLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<SeluLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<ShrinkLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<SigmoidLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<SignLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<SinLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<SinhLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<SoftplusLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<SoftsignLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<SqrtLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<SwishLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<TanHLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<TanLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl ActivationLayerTraitConst for Ptr<ThresholdedReluLayer>

fn as_raw_ActivationLayer(&self) -> *const c_void

fn forward_slice( &self, src: &[f32], dst: &mut [f32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

fn forward_slice_1( &self, src: &[i32], lut: &[i32], dst: &mut [i32], out_plane_size: size_t, cn0: i32, cn1: i32 ) -> Result<()>

impl AdaptiveManifoldFilterTrait for Ptr<AdaptiveManifoldFilter>

fn as_raw_mut_AdaptiveManifoldFilter(&mut self) -> *mut c_void

fn filter( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, joint: &impl ToInputArray ) -> Result<()>

Apply high-dimensional filtering using adaptive manifolds.

fn filter_def( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Apply high-dimensional filtering using adaptive manifolds.

fn collect_garbage(&mut self) -> Result<()>

fn set_sigma_s(&mut self, val: f64) -> Result<()>

See also

fn set_sigma_r(&mut self, val: f64) -> Result<()>

See also

fn set_tree_height(&mut self, val: i32) -> Result<()>

See also

fn set_pca_iterations(&mut self, val: i32) -> Result<()>

See also

fn set_adjust_outliers(&mut self, val: bool) -> Result<()>

See also

fn set_use_rng(&mut self, val: bool) -> Result<()>

See also

impl AdaptiveManifoldFilterTraitConst for Ptr<AdaptiveManifoldFilter>

fn as_raw_AdaptiveManifoldFilter(&self) -> *const c_void

fn get_sigma_s(&self) -> Result<f64>

See also

fn get_sigma_r(&self) -> Result<f64>

See also

fn get_tree_height(&self) -> Result<i32>

See also

fn get_pca_iterations(&self) -> Result<i32>

See also

fn get_adjust_outliers(&self) -> Result<bool>

See also

fn get_use_rng(&self) -> Result<bool>

See also

impl AffineFeature2DTrait for Ptr<AffineFeature2D>

fn as_raw_mut_AffineFeature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<Elliptic_KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in the image using the wrapped detector and performs affine adaptation to augment them with their elliptic regions.

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<Elliptic_KeyPoint> ) -> Result<()>

Detects keypoints in the image using the wrapped detector and performs affine adaptation to augment them with their elliptic regions.

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<Elliptic_KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes descriptors for their surrounding regions, after warping them into circles.

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<Elliptic_KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes descriptors for their surrounding regions, after warping them into circles.

impl AffineFeature2DTrait for Ptr<TBMR>

fn as_raw_mut_AffineFeature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<Elliptic_KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in the image using the wrapped detector and performs affine adaptation to augment them with their elliptic regions.

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<Elliptic_KeyPoint> ) -> Result<()>

Detects keypoints in the image using the wrapped detector and performs affine adaptation to augment them with their elliptic regions.

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<Elliptic_KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes descriptors for their surrounding regions, after warping them into circles.

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<Elliptic_KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes descriptors for their surrounding regions, after warping them into circles.

impl AffineFeature2DTraitConst for Ptr<AffineFeature2D>

fn as_raw_AffineFeature2D(&self) -> *const c_void

impl AffineFeature2DTraitConst for Ptr<TBMR>

fn as_raw_AffineFeature2D(&self) -> *const c_void

impl AffineFeatureTrait for Ptr<AffineFeature>

fn as_raw_mut_AffineFeature(&mut self) -> *mut c_void

fn set_view_params( &mut self, tilts: &Vector<f32>, rolls: &Vector<f32> ) -> Result<()>

impl AffineFeatureTraitConst for Ptr<AffineFeature>

fn as_raw_AffineFeature(&self) -> *const c_void

fn get_view_params( &self, tilts: &mut Vector<f32>, rolls: &mut Vector<f32> ) -> Result<()>

fn get_default_name(&self) -> Result<String>

impl AffineTransformerTrait for Ptr<AffineTransformer>

fn as_raw_mut_AffineTransformer(&mut self) -> *mut c_void

fn set_full_affine(&mut self, full_affine: bool) -> Result<()>

impl AffineTransformerTraitConst for Ptr<AffineTransformer>

fn as_raw_AffineTransformer(&self) -> *const c_void

fn get_full_affine(&self) -> Result<bool>

impl AffineWarperTrait for Ptr<AffineWarper>

fn as_raw_mut_AffineWarper(&mut self) -> *mut c_void

impl AffineWarperTraitConst for Ptr<AffineWarper>

fn as_raw_AffineWarper(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl AgastFeatureDetectorTrait for Ptr<AgastFeatureDetector>

fn as_raw_mut_AgastFeatureDetector(&mut self) -> *mut c_void

fn set_threshold(&mut self, threshold: i32) -> Result<()>

fn set_nonmax_suppression(&mut self, f: bool) -> Result<()>

fn set_type(&mut self, typ: AgastFeatureDetector_DetectorType) -> Result<()>

impl AgastFeatureDetectorTraitConst for Ptr<AgastFeatureDetector>

fn as_raw_AgastFeatureDetector(&self) -> *const c_void

fn get_threshold(&self) -> Result<i32>

fn get_nonmax_suppression(&self) -> Result<bool>

fn get_type(&self) -> Result<AgastFeatureDetector_DetectorType>

fn get_default_name(&self) -> Result<String>

impl AlgorithmTrait for Ptr<AKAZE>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ANN_MLP>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AbsLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AccumLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AcosLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AcoshLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ActivationLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ActivationLayerInt8>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AdaptiveManifoldFilter>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AffineFeature>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AffineFeature2D>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AffineTransformer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AgastFeatureDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Algorithm>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AlignExposures>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AlignMTB>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ArgLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ArucoDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AsinLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AsinhLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AtanLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AtanhLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AttentionLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<AverageHash>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BEBLID>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BFMatcher>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BIF>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BNLLLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BRISK>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BackgroundSubtractor>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BackgroundSubtractorCNT>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BackgroundSubtractorGMG>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BackgroundSubtractorGSOC>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BackgroundSubtractorKNN>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BackgroundSubtractorLSBP>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BackgroundSubtractorMOG>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BackgroundSubtractorMOG2>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BaseCascadeClassifier>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BaseConvolutionLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BasicFaceRecognizer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BatchNormLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BatchNormLayerInt8>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BinaryDescriptor>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BinaryDescriptorMatcher>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BlankLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BlockMeanHash>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Boost>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BoostDesc>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<BriefDescriptorExtractor>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CLAHE>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_BackgroundSubtractorMOG>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_BackgroundSubtractorMOG2>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_BroxOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_CLAHE>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_CannyEdgeDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_CascadeClassifier>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_CornernessCriteria>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_CornersDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_DenseOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_DensePyrLKOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_DescriptorMatcher>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_DisparityBilateralFilter>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_FarnebackOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_FastFeatureDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_Feature2DAsync>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_HOG>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_HoughCirclesDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_HoughLinesDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_HoughSegmentDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_NvidiaHWOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_NvidiaOpticalFlow_1_0>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_NvidiaOpticalFlow_2_0>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_ORB>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_OpticalFlowDual_TVL1>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_SparseOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_SparsePyrLKOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_StereoBM>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_StereoBeliefPropagation>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_StereoConstantSpaceBP>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_StereoSGM>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CUDA_TemplateMatching>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CalibrateCRF>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CalibrateDebevec>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CalibrateRobertson>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CeilLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CeluLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ChannelsPReLULayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CharucoDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ChiHistogramCostExtractor>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ColorMomentHash>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CompareLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ConcatLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ConjGradSolver>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ConstLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ContourFitting>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Convolution>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ConvolutionLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ConvolutionLayerInt8>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CorrelationLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CosLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CoshLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CropAndResizeLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CropLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CumSumLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<CustomPattern>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DAISY>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DFT>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DISOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DTFilter>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DTrees>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DataAugmentationLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DeconvolutionLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DenseOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DenseRLOFOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DepthCleaner>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DequantizeLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DescriptorMatcher>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DetectionOutputLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DisparityFilter>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DisparityWLSFilter>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DownhillSolver>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<DualTVL1OpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ELULayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<EM>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<EMDHistogramCostExtractor>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<EMDL1HistogramCostExtractor>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ERFilter>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<EdgeAwareInterpolator>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<EdgeBoxes>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<EdgeDrawing>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<EigenFaceRecognizer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<EinsumLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<EltwiseLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<EltwiseLayerInt8>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ErfLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ExpLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ExpandLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FREAK>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FaceRecognizer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Facemark>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FacemarkAAM>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FacemarkKazemi>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FacemarkLBF>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FacemarkTrain>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FarnebackOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FastBilateralSolverFilter>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FastFeatureDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FastGlobalSmootherFilter>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FastICPOdometry>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FastLineDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Feature2D>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Filter>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FisherFaceRecognizer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FlannBasedMatcher>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FlattenLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FloorLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FlowWarpLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<FreeType2>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<GFTTDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<GPCTree>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<GRULayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<GatherElementsLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<GatherLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<GeluApproximationLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<GeluLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<GemmLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<GeneralizedHough>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<GeneralizedHoughBallard>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<GeneralizedHoughGuil>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<GraphSegmentation>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<GrayCodePattern>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<GrayworldWB>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<GuidedFilter>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<HardSigmoidLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<HardSwishLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<HarrisLaplaceFeatureDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<HausdorffDistanceExtractor>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<HfsSegment>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<HistogramCostExtractor>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<HistogramPhaseUnwrapping>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ICPOdometry>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ImgHashBase>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<InnerProductLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<InnerProductLayerInt8>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<InstanceNormLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<InterpLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<KAZE>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<KNearest>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<LATCH>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<LBPHFaceRecognizer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<LMSolver>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<LRNLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<LSDDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<LSTMLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<LUCID>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Layer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<LayerNormLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<LearningBasedWB>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<LineSegmentDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<LogLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<LogisticRegression>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<LookUpTable>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MACE>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MCC_CCheckerDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MSDDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MSER>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MVNLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MarrHildrethHash>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MatMulLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MaxUnpoolLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MergeDebevec>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MergeExposures>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MergeMertens>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MergeRobertson>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MinProblemSolver>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MishLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MotionSaliency>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<MotionSaliencyBinWangApr2014>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<NaryEltwiseLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<NormHistogramCostExtractor>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<NormalBayesClassifier>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<NormalizeBBoxLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<NotLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ORB>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Objectness>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ObjectnessBING>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Odometry>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<OpticalFlowPCAFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<PCTSignatures>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<PCTSignaturesSQFD>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<PHash>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<PaddingLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<PermuteLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<PhaseUnwrapping>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Plot2d>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<PoolingLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<PoolingLayerInt8>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<PowerLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<PriorBoxLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ProposalLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<QualityBRISQUE>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<QualityBase>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<QualityGMSD>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<QualityMSE>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<QualityPSNR>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<QualitySSIM>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<QuantizeLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<RFFeatureGetter>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<RICInterpolator>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<RNNLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<RTrees>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<RadialVarianceHash>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Rapid_GOSTracker>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Rapid_OLSTracker>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Rapid_Rapid>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Rapid_Tracker>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ReLU6Layer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ReLULayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ReciprocalLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ReduceLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<RegionLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ReorgLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<RequantizeLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ReshapeLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ResizeLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Retina>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<RetinaFastToneMapping>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<RgbdICPOdometry>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<RgbdNormals>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<RgbdOdometry>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<RgbdPlane>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<RidgeDetectionFilter>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<RoundLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SIFT>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SURF>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SVM>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SVMSGD>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SVM_Kernel>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Saliency>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ScaleLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ScaleLayerInt8>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ScanSegment>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ScatterLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ScatterNDLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SelectiveSearchSegmentation>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SelectiveSearchSegmentationStrategy>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SelectiveSearchSegmentationStrategyColor>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SelectiveSearchSegmentationStrategyFill>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SelectiveSearchSegmentationStrategyMultiple>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SelectiveSearchSegmentationStrategySize>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SelectiveSearchSegmentationStrategyTexture>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SeluLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ShapeContextDistanceExtractor>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ShapeDistanceExtractor>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ShapeTransformer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ShiftLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ShiftLayerInt8>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ShrinkLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ShuffleChannelLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SigmoidLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SignLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SimpleBlobDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SimpleWB>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SinLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SinhLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SinusoidalPattern>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SliceLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SoftmaxLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SoftmaxLayerInt8>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SoftplusLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SoftsignLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SparseMatchInterpolator>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SparseOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SparsePyrLKOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SparseRLOFOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SplitLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SqrtLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<StarDetector>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<StatModel>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<StaticSaliency>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<StaticSaliencyFineGrained>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<StaticSaliencySpectralResidual>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<StereoBM>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<StereoMatcher>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<StereoSGBM>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<StructuredEdgeDetection>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<StructuredLightPattern>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SuperRes_BroxOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SuperRes_DenseOpticalFlowExt>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SuperRes_DualTVL1OpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SuperRes_FarnebackOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SuperRes_PyrLKOpticalFlow>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SuperRes_SuperResolution>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SuperpixelLSC>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SuperpixelSEEDS>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SuperpixelSLIC>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SwishLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<SyntheticSequenceGenerator>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<TBMR>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<TEBLID>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<TanHLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<TanLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ThinPlateSplineShapeTransformer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<ThresholdedReluLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<TileLayer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<Tonemap>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<TonemapDrago>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<TonemapDurand>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<TonemapMantiuk>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<TonemapReinhard>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<TransientAreasSegmentationModule>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<VGG>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<VariationalRefinement>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTrait for Ptr<WhiteBalancer>

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTraitConst for Ptr<AKAZE>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ANN_MLP>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AbsLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AccumLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AcosLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AcoshLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ActivationLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ActivationLayerInt8>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AdaptiveManifoldFilter>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AffineFeature>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AffineFeature2D>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AffineTransformer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AgastFeatureDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Algorithm>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AlignExposures>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AlignMTB>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ArgLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ArucoDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AsinLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AsinhLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AtanLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AtanhLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AttentionLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<AverageHash>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BEBLID>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BFMatcher>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BIF>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BNLLLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BRISK>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BackgroundSubtractor>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BackgroundSubtractorCNT>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BackgroundSubtractorGMG>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BackgroundSubtractorGSOC>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BackgroundSubtractorKNN>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BackgroundSubtractorLSBP>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BackgroundSubtractorMOG>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BackgroundSubtractorMOG2>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BaseCascadeClassifier>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BaseConvolutionLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BasicFaceRecognizer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BatchNormLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BatchNormLayerInt8>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BinaryDescriptor>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BinaryDescriptorMatcher>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BlankLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BlockMeanHash>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Boost>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BoostDesc>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<BriefDescriptorExtractor>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CLAHE>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_BackgroundSubtractorMOG>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_BackgroundSubtractorMOG2>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_BroxOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_CLAHE>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_CannyEdgeDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_CascadeClassifier>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_CornernessCriteria>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_CornersDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_DenseOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_DensePyrLKOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_DescriptorMatcher>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_DisparityBilateralFilter>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_FarnebackOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_FastFeatureDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_Feature2DAsync>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_HOG>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_HoughCirclesDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_HoughLinesDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_HoughSegmentDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_NvidiaHWOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_NvidiaOpticalFlow_1_0>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_NvidiaOpticalFlow_2_0>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_ORB>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_OpticalFlowDual_TVL1>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_SparseOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_SparsePyrLKOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_StereoBM>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_StereoBeliefPropagation>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_StereoConstantSpaceBP>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_StereoSGM>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CUDA_TemplateMatching>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CalibrateCRF>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CalibrateDebevec>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CalibrateRobertson>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CeilLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CeluLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ChannelsPReLULayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CharucoDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ChiHistogramCostExtractor>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ColorMomentHash>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CompareLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ConcatLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ConjGradSolver>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ConstLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ContourFitting>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Convolution>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ConvolutionLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ConvolutionLayerInt8>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CorrelationLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CosLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CoshLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CropAndResizeLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CropLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CumSumLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<CustomPattern>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DAISY>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DFT>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DISOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DTFilter>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DTrees>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DataAugmentationLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DeconvolutionLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DenseOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DenseRLOFOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DepthCleaner>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DequantizeLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DescriptorMatcher>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DetectionOutputLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DisparityFilter>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DisparityWLSFilter>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DownhillSolver>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<DualTVL1OpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ELULayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<EM>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<EMDHistogramCostExtractor>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<EMDL1HistogramCostExtractor>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ERFilter>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<EdgeAwareInterpolator>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<EdgeBoxes>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<EdgeDrawing>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<EigenFaceRecognizer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<EinsumLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<EltwiseLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<EltwiseLayerInt8>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ErfLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ExpLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ExpandLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FREAK>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FaceRecognizer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Facemark>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FacemarkAAM>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FacemarkKazemi>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FacemarkLBF>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FacemarkTrain>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FarnebackOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FastBilateralSolverFilter>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FastFeatureDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FastGlobalSmootherFilter>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FastICPOdometry>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FastLineDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Feature2D>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Filter>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FisherFaceRecognizer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FlannBasedMatcher>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FlattenLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FloorLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FlowWarpLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<FreeType2>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<GFTTDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<GPCTree>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<GRULayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<GatherElementsLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<GatherLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<GeluApproximationLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<GeluLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<GemmLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<GeneralizedHough>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<GeneralizedHoughBallard>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<GeneralizedHoughGuil>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<GraphSegmentation>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<GrayCodePattern>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<GrayworldWB>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<GuidedFilter>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<HardSigmoidLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<HardSwishLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<HarrisLaplaceFeatureDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<HausdorffDistanceExtractor>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<HfsSegment>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<HistogramCostExtractor>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<HistogramPhaseUnwrapping>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ICPOdometry>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ImgHashBase>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<InnerProductLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<InnerProductLayerInt8>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<InstanceNormLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<InterpLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<KAZE>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<KNearest>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<LATCH>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<LBPHFaceRecognizer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<LMSolver>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<LRNLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<LSDDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<LSTMLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<LUCID>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Layer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<LayerNormLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<LearningBasedWB>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<LineSegmentDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<LogLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<LogisticRegression>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<LookUpTable>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MACE>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MCC_CCheckerDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MSDDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MSER>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MVNLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MarrHildrethHash>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MatMulLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MaxUnpoolLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MergeDebevec>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MergeExposures>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MergeMertens>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MergeRobertson>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MinProblemSolver>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MishLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MotionSaliency>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<MotionSaliencyBinWangApr2014>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<NaryEltwiseLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<NormHistogramCostExtractor>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<NormalBayesClassifier>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<NormalizeBBoxLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<NotLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ORB>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Objectness>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ObjectnessBING>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Odometry>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<OpticalFlowPCAFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<PCTSignatures>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<PCTSignaturesSQFD>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<PHash>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<PaddingLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<PermuteLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<PhaseUnwrapping>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Plot2d>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<PoolingLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<PoolingLayerInt8>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<PowerLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<PriorBoxLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ProposalLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<QualityBRISQUE>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<QualityBase>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<QualityGMSD>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<QualityMSE>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<QualityPSNR>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<QualitySSIM>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<QuantizeLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<RFFeatureGetter>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<RICInterpolator>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<RNNLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<RTrees>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<RadialVarianceHash>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Rapid_GOSTracker>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Rapid_OLSTracker>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Rapid_Rapid>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Rapid_Tracker>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ReLU6Layer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ReLULayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ReciprocalLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ReduceLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<RegionLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ReorgLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<RequantizeLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ReshapeLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ResizeLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Retina>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<RetinaFastToneMapping>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<RgbdICPOdometry>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<RgbdNormals>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<RgbdOdometry>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<RgbdPlane>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<RidgeDetectionFilter>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<RoundLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SIFT>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SURF>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SVM>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SVMSGD>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SVM_Kernel>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Saliency>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ScaleLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ScaleLayerInt8>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ScanSegment>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ScatterLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ScatterNDLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SelectiveSearchSegmentation>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SelectiveSearchSegmentationStrategy>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SelectiveSearchSegmentationStrategyColor>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SelectiveSearchSegmentationStrategyFill>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SelectiveSearchSegmentationStrategyMultiple>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SelectiveSearchSegmentationStrategySize>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SelectiveSearchSegmentationStrategyTexture>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SeluLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ShapeContextDistanceExtractor>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ShapeDistanceExtractor>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ShapeTransformer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ShiftLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ShiftLayerInt8>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ShrinkLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ShuffleChannelLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SigmoidLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SignLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SimpleBlobDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SimpleWB>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SinLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SinhLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SinusoidalPattern>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SliceLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SoftmaxLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SoftmaxLayerInt8>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SoftplusLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SoftsignLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SparseMatchInterpolator>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SparseOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SparsePyrLKOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SparseRLOFOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SplitLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SqrtLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<StarDetector>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<StatModel>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<StaticSaliency>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<StaticSaliencyFineGrained>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<StaticSaliencySpectralResidual>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<StereoBM>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<StereoMatcher>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<StereoSGBM>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<StructuredEdgeDetection>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<StructuredLightPattern>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SuperRes_BroxOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SuperRes_DenseOpticalFlowExt>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SuperRes_DualTVL1OpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SuperRes_FarnebackOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SuperRes_PyrLKOpticalFlow>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SuperRes_SuperResolution>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SuperpixelLSC>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SuperpixelSEEDS>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SuperpixelSLIC>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SwishLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<SyntheticSequenceGenerator>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<TBMR>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<TEBLID>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<TanHLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<TanLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ThinPlateSplineShapeTransformer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<ThresholdedReluLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<TileLayer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<Tonemap>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<TonemapDrago>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<TonemapDurand>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<TonemapMantiuk>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<TonemapReinhard>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<TransientAreasSegmentationModule>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<VGG>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<VariationalRefinement>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlgorithmTraitConst for Ptr<WhiteBalancer>

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl AlignExposuresTrait for Ptr<AlignExposures>

fn as_raw_mut_AlignExposures(&mut self) -> *mut c_void

fn process( &mut self, src: &impl ToInputArray, dst: &mut Vector<Mat>, times: &impl ToInputArray, response: &impl ToInputArray ) -> Result<()>

Aligns images

impl AlignExposuresTrait for Ptr<AlignMTB>

fn as_raw_mut_AlignExposures(&mut self) -> *mut c_void

fn process( &mut self, src: &impl ToInputArray, dst: &mut Vector<Mat>, times: &impl ToInputArray, response: &impl ToInputArray ) -> Result<()>

Aligns images

impl AlignExposuresTraitConst for Ptr<AlignExposures>

fn as_raw_AlignExposures(&self) -> *const c_void

impl AlignExposuresTraitConst for Ptr<AlignMTB>

fn as_raw_AlignExposures(&self) -> *const c_void

impl AlignMTBTrait for Ptr<AlignMTB>

fn as_raw_mut_AlignMTB(&mut self) -> *mut c_void

fn process_with_response( &mut self, src: &impl ToInputArray, dst: &mut Vector<Mat>, times: &impl ToInputArray, response: &impl ToInputArray ) -> Result<()>

fn process( &mut self, src: &impl ToInputArray, dst: &mut Vector<Mat> ) -> Result<()>

Short version of process, that doesn’t take extra arguments.

fn calculate_shift( &mut self, img0: &impl ToInputArray, img1: &impl ToInputArray ) -> Result<Point>

Calculates shift between two images, i. e. how to shift the second image to correspond it with the first.

fn shift_mat( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, shift: Point ) -> Result<()>

Helper function, that shift Mat filling new regions with zeros.

fn compute_bitmaps( &mut self, img: &impl ToInputArray, tb: &mut impl ToOutputArray, eb: &mut impl ToOutputArray ) -> Result<()>

Computes median threshold and exclude bitmaps of given image.

fn set_max_bits(&mut self, max_bits: i32) -> Result<()>

fn set_exclude_range(&mut self, exclude_range: i32) -> Result<()>

fn set_cut(&mut self, value: bool) -> Result<()>

impl AlignMTBTraitConst for Ptr<AlignMTB>

fn as_raw_AlignMTB(&self) -> *const c_void

fn get_max_bits(&self) -> Result<i32>

fn get_exclude_range(&self) -> Result<i32>

fn get_cut(&self) -> Result<bool>

impl ArgLayerTrait for Ptr<ArgLayer>

fn as_raw_mut_ArgLayer(&mut self) -> *mut c_void

impl ArgLayerTraitConst for Ptr<ArgLayer>

fn as_raw_ArgLayer(&self) -> *const c_void

impl ArucoDetectorTrait for Ptr<ArucoDetector>

fn as_raw_mut_ArucoDetector(&mut self) -> *mut c_void

fn set_dictionary( &mut self, dictionary: &impl DictionaryTraitConst ) -> Result<()>

fn set_detector_parameters( &mut self, detector_parameters: &impl DetectorParametersTraitConst ) -> Result<()>

fn set_refine_parameters( &mut self, refine_parameters: RefineParameters ) -> Result<()>

fn write_1(&mut self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

simplified API for language bindings

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl ArucoDetectorTraitConst for Ptr<ArucoDetector>

fn as_raw_ArucoDetector(&self) -> *const c_void

fn detect_markers( &self, image: &impl ToInputArray, corners: &mut impl ToOutputArray, ids: &mut impl ToOutputArray, rejected_img_points: &mut impl ToOutputArray ) -> Result<()>

Basic marker detection

fn detect_markers_def( &self, image: &impl ToInputArray, corners: &mut impl ToOutputArray, ids: &mut impl ToOutputArray ) -> Result<()>

Basic marker detection

fn refine_detected_markers( &self, image: &impl ToInputArray, board: &impl BoardTraitConst, detected_corners: &mut impl ToInputOutputArray, detected_ids: &mut impl ToInputOutputArray, rejected_corners: &mut impl ToInputOutputArray, camera_matrix: &impl ToInputArray, dist_coeffs: &impl ToInputArray, recovered_idxs: &mut impl ToOutputArray ) -> Result<()>

Refine not detected markers based on the already detected and the board layout

fn refine_detected_markers_def( &self, image: &impl ToInputArray, board: &impl BoardTraitConst, detected_corners: &mut impl ToInputOutputArray, detected_ids: &mut impl ToInputOutputArray, rejected_corners: &mut impl ToInputOutputArray ) -> Result<()>

Refine not detected markers based on the already detected and the board layout

fn get_dictionary(&self) -> Result<Dictionary>

fn get_detector_parameters(&self) -> Result<DetectorParameters>

fn get_refine_parameters(&self) -> Result<RefineParameters>

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

impl AsinLayerTrait for Ptr<AsinLayer>

fn as_raw_mut_AsinLayer(&mut self) -> *mut c_void

impl AsinLayerTraitConst for Ptr<AsinLayer>

fn as_raw_AsinLayer(&self) -> *const c_void

impl AsinhLayerTrait for Ptr<AsinhLayer>

fn as_raw_mut_AsinhLayer(&mut self) -> *mut c_void

impl AsinhLayerTraitConst for Ptr<AsinhLayer>

fn as_raw_AsinhLayer(&self) -> *const c_void

impl AtanLayerTrait for Ptr<AtanLayer>

fn as_raw_mut_AtanLayer(&mut self) -> *mut c_void

impl AtanLayerTraitConst for Ptr<AtanLayer>

fn as_raw_AtanLayer(&self) -> *const c_void

impl AtanhLayerTrait for Ptr<AtanhLayer>

fn as_raw_mut_AtanhLayer(&mut self) -> *mut c_void

impl AtanhLayerTraitConst for Ptr<AtanhLayer>

fn as_raw_AtanhLayer(&self) -> *const c_void

impl AttentionLayerTrait for Ptr<AttentionLayer>

fn as_raw_mut_AttentionLayer(&mut self) -> *mut c_void

impl AttentionLayerTraitConst for Ptr<AttentionLayer>

fn as_raw_AttentionLayer(&self) -> *const c_void

impl AutotunedIndexParamsTrait for Ptr<AutotunedIndexParams>

fn as_raw_mut_AutotunedIndexParams(&mut self) -> *mut c_void

impl AutotunedIndexParamsTraitConst for Ptr<AutotunedIndexParams>

fn as_raw_AutotunedIndexParams(&self) -> *const c_void

impl AverageHashTrait for Ptr<AverageHash>

fn as_raw_mut_AverageHash(&mut self) -> *mut c_void

impl AverageHashTraitConst for Ptr<AverageHash>

fn as_raw_AverageHash(&self) -> *const c_void

impl BEBLIDTrait for Ptr<BEBLID>

fn as_raw_mut_BEBLID(&mut self) -> *mut c_void

fn set_scale_factor(&mut self, scale_factor: f32) -> Result<()>

impl BEBLIDTraitConst for Ptr<BEBLID>

fn as_raw_BEBLID(&self) -> *const c_void

fn get_scale_factor(&self) -> Result<f32>

fn get_default_name(&self) -> Result<String>

impl BFMatcherTrait for Ptr<BFMatcher>

fn as_raw_mut_BFMatcher(&mut self) -> *mut c_void

impl BFMatcherTraitConst for Ptr<BFMatcher>

fn as_raw_BFMatcher(&self) -> *const c_void

fn is_mask_supported(&self) -> Result<bool>

fn clone(&self, empty_train_data: bool) -> Result<Ptr<DescriptorMatcher>>

C++ default parameters

fn clone_def(&self) -> Result<Ptr<DescriptorMatcher>>

Note

impl BIFTrait for Ptr<BIF>

fn as_raw_mut_BIF(&mut self) -> *mut c_void

impl BIFTraitConst for Ptr<BIF>

fn as_raw_BIF(&self) -> *const c_void

fn get_num_bands(&self) -> Result<i32>

Returns

fn get_num_rotations(&self) -> Result<i32>

Returns

fn compute( &self, image: &impl ToInputArray, features: &mut impl ToOutputArray ) -> Result<()>

Computes features sby input image.

impl BNLLLayerTrait for Ptr<BNLLLayer>

fn as_raw_mut_BNLLLayer(&mut self) -> *mut c_void

impl BNLLLayerTraitConst for Ptr<BNLLLayer>

fn as_raw_BNLLLayer(&self) -> *const c_void

impl BRISKTrait for Ptr<BRISK>

fn as_raw_mut_BRISK(&mut self) -> *mut c_void

fn set_threshold(&mut self, threshold: i32) -> Result<()>

Set detection threshold.

fn set_octaves(&mut self, octaves: i32) -> Result<()>

Set detection octaves.

fn set_pattern_scale(&mut self, pattern_scale: f32) -> Result<()>

Set detection patternScale.

impl BRISKTraitConst for Ptr<BRISK>

fn as_raw_BRISK(&self) -> *const c_void

fn get_default_name(&self) -> Result<String>

fn get_threshold(&self) -> Result<i32>

fn get_octaves(&self) -> Result<i32>

fn get_pattern_scale(&self) -> Result<f32>

impl BackendNodeTrait for Ptr<BackendNode>

fn as_raw_mut_BackendNode(&mut self) -> *mut c_void

fn set_backend_id(&mut self, val: i32)

Backend identifier.

impl BackendNodeTraitConst for Ptr<BackendNode>

fn as_raw_BackendNode(&self) -> *const c_void

fn backend_id(&self) -> i32

Backend identifier.

impl BackendWrapperTrait for Ptr<BackendWrapper>

fn as_raw_mut_BackendWrapper(&mut self) -> *mut c_void

fn set_backend_id(&mut self, val: i32)

Backend identifier.

fn set_target_id(&mut self, val: i32)

Target identifier.

fn copy_to_host(&mut self) -> Result<()>

Transfer data to CPU host memory.

fn set_host_dirty(&mut self) -> Result<()>

Indicate that an actual data is on CPU.

impl BackendWrapperTraitConst for Ptr<BackendWrapper>

fn as_raw_BackendWrapper(&self) -> *const c_void

fn backend_id(&self) -> i32

Backend identifier.

fn target_id(&self) -> i32

Target identifier.

impl BackgroundSubtractorCNTTrait for Ptr<BackgroundSubtractorCNT>

fn as_raw_mut_BackgroundSubtractorCNT(&mut self) -> *mut c_void

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64 ) -> Result<()>

C++ default parameters

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray ) -> Result<()>

Note

fn set_min_pixel_stability(&mut self, value: i32) -> Result<()>

Sets the number of frames with same pixel color to consider stable.

fn set_max_pixel_stability(&mut self, value: i32) -> Result<()>

Sets the maximum allowed credit for a pixel in history.

fn set_use_history(&mut self, value: bool) -> Result<()>

Sets if we’re giving a pixel credit for being stable for a long time.

fn set_is_parallel(&mut self, value: bool) -> Result<()>

Sets if we’re parallelizing the algorithm.

impl BackgroundSubtractorCNTTraitConst for Ptr<BackgroundSubtractorCNT>

fn as_raw_BackgroundSubtractorCNT(&self) -> *const c_void

fn get_background_image( &self, background_image: &mut impl ToOutputArray ) -> Result<()>

fn get_min_pixel_stability(&self) -> Result<i32>

Returns number of frames with same pixel color to consider stable.

fn get_max_pixel_stability(&self) -> Result<i32>

Returns maximum allowed credit for a pixel in history.

fn get_use_history(&self) -> Result<bool>

Returns if we’re giving a pixel credit for being stable for a long time.

fn get_is_parallel(&self) -> Result<bool>

Returns if we’re parallelizing the algorithm.

impl BackgroundSubtractorGMGTrait for Ptr<BackgroundSubtractorGMG>

fn as_raw_mut_BackgroundSubtractorGMG(&mut self) -> *mut c_void

fn set_max_features(&mut self, max_features: i32) -> Result<()>

Sets total number of distinct colors to maintain in histogram.

fn set_default_learning_rate(&mut self, lr: f64) -> Result<()>

Sets the learning rate of the algorithm.

fn set_num_frames(&mut self, nframes: i32) -> Result<()>

Sets the number of frames used to initialize background model.

fn set_quantization_levels(&mut self, nlevels: i32) -> Result<()>

Sets the parameter used for quantization of color-space

fn set_background_prior(&mut self, bgprior: f64) -> Result<()>

Sets the prior probability that each individual pixel is a background pixel.

fn set_smoothing_radius(&mut self, radius: i32) -> Result<()>

Sets the kernel radius used for morphological operations

fn set_decision_threshold(&mut self, thresh: f64) -> Result<()>

Sets the value of decision threshold.

fn set_update_background_model(&mut self, update: bool) -> Result<()>

Sets the status of background model update

fn set_min_val(&mut self, val: f64) -> Result<()>

Sets the minimum value taken on by pixels in image sequence.

fn set_max_val(&mut self, val: f64) -> Result<()>

Sets the maximum value taken on by pixels in image sequence.

impl BackgroundSubtractorGMGTraitConst for Ptr<BackgroundSubtractorGMG>

fn as_raw_BackgroundSubtractorGMG(&self) -> *const c_void

fn get_max_features(&self) -> Result<i32>

Returns total number of distinct colors to maintain in histogram.

fn get_default_learning_rate(&self) -> Result<f64>

Returns the learning rate of the algorithm.

fn get_num_frames(&self) -> Result<i32>

Returns the number of frames used to initialize background model.

fn get_quantization_levels(&self) -> Result<i32>

Returns the parameter used for quantization of color-space.

fn get_background_prior(&self) -> Result<f64>

Returns the prior probability that each individual pixel is a background pixel.

fn get_smoothing_radius(&self) -> Result<i32>

Returns the kernel radius used for morphological operations

fn get_decision_threshold(&self) -> Result<f64>

Returns the value of decision threshold.

fn get_update_background_model(&self) -> Result<bool>

Returns the status of background model update

fn get_min_val(&self) -> Result<f64>

Returns the minimum value taken on by pixels in image sequence. Usually 0.

fn get_max_val(&self) -> Result<f64>

Returns the maximum value taken on by pixels in image sequence. e.g. 1.0 or 255.

impl BackgroundSubtractorGSOCTrait for Ptr<BackgroundSubtractorGSOC>

fn as_raw_mut_BackgroundSubtractorGSOC(&mut self) -> *mut c_void

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64 ) -> Result<()>

C++ default parameters

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray ) -> Result<()>

Note

impl BackgroundSubtractorGSOCTraitConst for Ptr<BackgroundSubtractorGSOC>

fn as_raw_BackgroundSubtractorGSOC(&self) -> *const c_void

fn get_background_image( &self, background_image: &mut impl ToOutputArray ) -> Result<()>

impl BackgroundSubtractorKNNTrait for Ptr<BackgroundSubtractorKNN>

fn as_raw_mut_BackgroundSubtractorKNN(&mut self) -> *mut c_void

fn set_history(&mut self, history: i32) -> Result<()>

Sets the number of last frames that affect the background model

fn set_n_samples(&mut self, _n_n: i32) -> Result<()>

Sets the number of data samples in the background model.

fn set_dist2_threshold(&mut self, _dist2_threshold: f64) -> Result<()>

Sets the threshold on the squared distance

fn setk_nn_samples(&mut self, _nk_nn: i32) -> Result<()>

Sets the k in the kNN. How many nearest neighbours need to match.

fn set_detect_shadows(&mut self, detect_shadows: bool) -> Result<()>

Enables or disables shadow detection

fn set_shadow_value(&mut self, value: i32) -> Result<()>

Sets the shadow value

fn set_shadow_threshold(&mut self, threshold: f64) -> Result<()>

Sets the shadow threshold

impl BackgroundSubtractorKNNTraitConst for Ptr<BackgroundSubtractorKNN>

fn as_raw_BackgroundSubtractorKNN(&self) -> *const c_void

fn get_history(&self) -> Result<i32>

Returns the number of last frames that affect the background model

fn get_n_samples(&self) -> Result<i32>

Returns the number of data samples in the background model

fn get_dist2_threshold(&self) -> Result<f64>

Returns the threshold on the squared distance between the pixel and the sample

fn getk_nn_samples(&self) -> Result<i32>

Returns the number of neighbours, the k in the kNN.

fn get_detect_shadows(&self) -> Result<bool>

Returns the shadow detection flag

fn get_shadow_value(&self) -> Result<i32>

Returns the shadow value

fn get_shadow_threshold(&self) -> Result<f64>

Returns the shadow threshold

impl BackgroundSubtractorLSBPTrait for Ptr<BackgroundSubtractorLSBP>

fn as_raw_mut_BackgroundSubtractorLSBP(&mut self) -> *mut c_void

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64 ) -> Result<()>

C++ default parameters

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray ) -> Result<()>

Note

impl BackgroundSubtractorLSBPTraitConst for Ptr<BackgroundSubtractorLSBP>

fn as_raw_BackgroundSubtractorLSBP(&self) -> *const c_void

fn get_background_image( &self, background_image: &mut impl ToOutputArray ) -> Result<()>

impl BackgroundSubtractorMOG2Trait for Ptr<BackgroundSubtractorMOG2>

fn as_raw_mut_BackgroundSubtractorMOG2(&mut self) -> *mut c_void

fn set_history(&mut self, history: i32) -> Result<()>

Sets the number of last frames that affect the background model

fn set_n_mixtures(&mut self, nmixtures: i32) -> Result<()>

Sets the number of gaussian components in the background model.

fn set_background_ratio(&mut self, ratio: f64) -> Result<()>

Sets the “background ratio” parameter of the algorithm

fn set_var_threshold(&mut self, var_threshold: f64) -> Result<()>

Sets the variance threshold for the pixel-model match

fn set_var_threshold_gen(&mut self, var_threshold_gen: f64) -> Result<()>

Sets the variance threshold for the pixel-model match used for new mixture component generation

fn set_var_init(&mut self, var_init: f64) -> Result<()>

Sets the initial variance of each gaussian component

fn set_var_min(&mut self, var_min: f64) -> Result<()>

fn set_var_max(&mut self, var_max: f64) -> Result<()>

fn set_complexity_reduction_threshold(&mut self, ct: f64) -> Result<()>

Sets the complexity reduction threshold

fn set_detect_shadows(&mut self, detect_shadows: bool) -> Result<()>

Enables or disables shadow detection

fn set_shadow_value(&mut self, value: i32) -> Result<()>

Sets the shadow value

fn set_shadow_threshold(&mut self, threshold: f64) -> Result<()>

Sets the shadow threshold

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64 ) -> Result<()>

Computes a foreground mask.

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray ) -> Result<()>

Computes a foreground mask.

impl BackgroundSubtractorMOG2Trait for Ptr<CUDA_BackgroundSubtractorMOG2>

fn as_raw_mut_BackgroundSubtractorMOG2(&mut self) -> *mut c_void

fn set_history(&mut self, history: i32) -> Result<()>

Sets the number of last frames that affect the background model

fn set_n_mixtures(&mut self, nmixtures: i32) -> Result<()>

Sets the number of gaussian components in the background model.

fn set_background_ratio(&mut self, ratio: f64) -> Result<()>

Sets the “background ratio” parameter of the algorithm

fn set_var_threshold(&mut self, var_threshold: f64) -> Result<()>

Sets the variance threshold for the pixel-model match

fn set_var_threshold_gen(&mut self, var_threshold_gen: f64) -> Result<()>

Sets the variance threshold for the pixel-model match used for new mixture component generation

fn set_var_init(&mut self, var_init: f64) -> Result<()>

Sets the initial variance of each gaussian component

fn set_var_min(&mut self, var_min: f64) -> Result<()>

fn set_var_max(&mut self, var_max: f64) -> Result<()>

fn set_complexity_reduction_threshold(&mut self, ct: f64) -> Result<()>

Sets the complexity reduction threshold

fn set_detect_shadows(&mut self, detect_shadows: bool) -> Result<()>

Enables or disables shadow detection

fn set_shadow_value(&mut self, value: i32) -> Result<()>

Sets the shadow value

fn set_shadow_threshold(&mut self, threshold: f64) -> Result<()>

Sets the shadow threshold

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64 ) -> Result<()>

Computes a foreground mask.

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray ) -> Result<()>

Computes a foreground mask.

impl BackgroundSubtractorMOG2TraitConst for Ptr<BackgroundSubtractorMOG2>

fn as_raw_BackgroundSubtractorMOG2(&self) -> *const c_void

fn get_history(&self) -> Result<i32>

Returns the number of last frames that affect the background model

fn get_n_mixtures(&self) -> Result<i32>

Returns the number of gaussian components in the background model

fn get_background_ratio(&self) -> Result<f64>

Returns the “background ratio” parameter of the algorithm

fn get_var_threshold(&self) -> Result<f64>

Returns the variance threshold for the pixel-model match

fn get_var_threshold_gen(&self) -> Result<f64>

Returns the variance threshold for the pixel-model match used for new mixture component generation

fn get_var_init(&self) -> Result<f64>

Returns the initial variance of each gaussian component

fn get_var_min(&self) -> Result<f64>

fn get_var_max(&self) -> Result<f64>

fn get_complexity_reduction_threshold(&self) -> Result<f64>

Returns the complexity reduction threshold

fn get_detect_shadows(&self) -> Result<bool>

Returns the shadow detection flag

fn get_shadow_value(&self) -> Result<i32>

Returns the shadow value

fn get_shadow_threshold(&self) -> Result<f64>

Returns the shadow threshold

impl BackgroundSubtractorMOG2TraitConst for Ptr<CUDA_BackgroundSubtractorMOG2>

fn as_raw_BackgroundSubtractorMOG2(&self) -> *const c_void

fn get_history(&self) -> Result<i32>

Returns the number of last frames that affect the background model

fn get_n_mixtures(&self) -> Result<i32>

Returns the number of gaussian components in the background model

fn get_background_ratio(&self) -> Result<f64>

Returns the “background ratio” parameter of the algorithm

fn get_var_threshold(&self) -> Result<f64>

Returns the variance threshold for the pixel-model match

fn get_var_threshold_gen(&self) -> Result<f64>

Returns the variance threshold for the pixel-model match used for new mixture component generation

fn get_var_init(&self) -> Result<f64>

Returns the initial variance of each gaussian component

fn get_var_min(&self) -> Result<f64>

fn get_var_max(&self) -> Result<f64>

fn get_complexity_reduction_threshold(&self) -> Result<f64>

Returns the complexity reduction threshold

fn get_detect_shadows(&self) -> Result<bool>

Returns the shadow detection flag

fn get_shadow_value(&self) -> Result<i32>

Returns the shadow value

fn get_shadow_threshold(&self) -> Result<f64>

Returns the shadow threshold

impl BackgroundSubtractorMOGTrait for Ptr<BackgroundSubtractorMOG>

fn as_raw_mut_BackgroundSubtractorMOG(&mut self) -> *mut c_void

fn set_history(&mut self, nframes: i32) -> Result<()>

fn set_n_mixtures(&mut self, nmix: i32) -> Result<()>

fn set_background_ratio(&mut self, background_ratio: f64) -> Result<()>

fn set_noise_sigma(&mut self, noise_sigma: f64) -> Result<()>

impl BackgroundSubtractorMOGTraitConst for Ptr<BackgroundSubtractorMOG>

fn as_raw_BackgroundSubtractorMOG(&self) -> *const c_void

fn get_history(&self) -> Result<i32>

fn get_n_mixtures(&self) -> Result<i32>

fn get_background_ratio(&self) -> Result<f64>

fn get_noise_sigma(&self) -> Result<f64>

impl BackgroundSubtractorTrait for Ptr<BackgroundSubtractor>

fn as_raw_mut_BackgroundSubtractor(&mut self) -> *mut c_void

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64 ) -> Result<()>

Computes a foreground mask.

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray ) -> Result<()>

Computes a foreground mask.

impl BackgroundSubtractorTrait for Ptr<BackgroundSubtractorCNT>

fn as_raw_mut_BackgroundSubtractor(&mut self) -> *mut c_void

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64 ) -> Result<()>

Computes a foreground mask.

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray ) -> Result<()>

Computes a foreground mask.

impl BackgroundSubtractorTrait for Ptr<BackgroundSubtractorGMG>

fn as_raw_mut_BackgroundSubtractor(&mut self) -> *mut c_void

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64 ) -> Result<()>

Computes a foreground mask.

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray ) -> Result<()>

Computes a foreground mask.

impl BackgroundSubtractorTrait for Ptr<BackgroundSubtractorGSOC>

fn as_raw_mut_BackgroundSubtractor(&mut self) -> *mut c_void

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64 ) -> Result<()>

Computes a foreground mask.

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray ) -> Result<()>

Computes a foreground mask.

impl BackgroundSubtractorTrait for Ptr<BackgroundSubtractorKNN>

fn as_raw_mut_BackgroundSubtractor(&mut self) -> *mut c_void

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64 ) -> Result<()>

Computes a foreground mask.

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray ) -> Result<()>

Computes a foreground mask.

impl BackgroundSubtractorTrait for Ptr<BackgroundSubtractorLSBP>

fn as_raw_mut_BackgroundSubtractor(&mut self) -> *mut c_void

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64 ) -> Result<()>

Computes a foreground mask.

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray ) -> Result<()>

Computes a foreground mask.

impl BackgroundSubtractorTrait for Ptr<BackgroundSubtractorMOG>

fn as_raw_mut_BackgroundSubtractor(&mut self) -> *mut c_void

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64 ) -> Result<()>

Computes a foreground mask.

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray ) -> Result<()>

Computes a foreground mask.

impl BackgroundSubtractorTrait for Ptr<BackgroundSubtractorMOG2>

fn as_raw_mut_BackgroundSubtractor(&mut self) -> *mut c_void

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64 ) -> Result<()>

Computes a foreground mask.

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray ) -> Result<()>

Computes a foreground mask.

impl BackgroundSubtractorTrait for Ptr<CUDA_BackgroundSubtractorMOG>

fn as_raw_mut_BackgroundSubtractor(&mut self) -> *mut c_void

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64 ) -> Result<()>

Computes a foreground mask.

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray ) -> Result<()>

Computes a foreground mask.

impl BackgroundSubtractorTrait for Ptr<CUDA_BackgroundSubtractorMOG2>

fn as_raw_mut_BackgroundSubtractor(&mut self) -> *mut c_void

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64 ) -> Result<()>

Computes a foreground mask.

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray ) -> Result<()>

Computes a foreground mask.

impl BackgroundSubtractorTraitConst for Ptr<BackgroundSubtractor>

fn as_raw_BackgroundSubtractor(&self) -> *const c_void

fn get_background_image( &self, background_image: &mut impl ToOutputArray ) -> Result<()>

Computes a background image.

impl BackgroundSubtractorTraitConst for Ptr<BackgroundSubtractorCNT>

fn as_raw_BackgroundSubtractor(&self) -> *const c_void

fn get_background_image( &self, background_image: &mut impl ToOutputArray ) -> Result<()>

Computes a background image.

impl BackgroundSubtractorTraitConst for Ptr<BackgroundSubtractorGMG>

fn as_raw_BackgroundSubtractor(&self) -> *const c_void

fn get_background_image( &self, background_image: &mut impl ToOutputArray ) -> Result<()>

Computes a background image.

impl BackgroundSubtractorTraitConst for Ptr<BackgroundSubtractorGSOC>

fn as_raw_BackgroundSubtractor(&self) -> *const c_void

fn get_background_image( &self, background_image: &mut impl ToOutputArray ) -> Result<()>

Computes a background image.

impl BackgroundSubtractorTraitConst for Ptr<BackgroundSubtractorKNN>

fn as_raw_BackgroundSubtractor(&self) -> *const c_void

fn get_background_image( &self, background_image: &mut impl ToOutputArray ) -> Result<()>

Computes a background image.

impl BackgroundSubtractorTraitConst for Ptr<BackgroundSubtractorLSBP>

fn as_raw_BackgroundSubtractor(&self) -> *const c_void

fn get_background_image( &self, background_image: &mut impl ToOutputArray ) -> Result<()>

Computes a background image.

impl BackgroundSubtractorTraitConst for Ptr<BackgroundSubtractorMOG>

fn as_raw_BackgroundSubtractor(&self) -> *const c_void

fn get_background_image( &self, background_image: &mut impl ToOutputArray ) -> Result<()>

Computes a background image.

impl BackgroundSubtractorTraitConst for Ptr<BackgroundSubtractorMOG2>

fn as_raw_BackgroundSubtractor(&self) -> *const c_void

fn get_background_image( &self, background_image: &mut impl ToOutputArray ) -> Result<()>

Computes a background image.

impl BackgroundSubtractorTraitConst for Ptr<CUDA_BackgroundSubtractorMOG>

fn as_raw_BackgroundSubtractor(&self) -> *const c_void

fn get_background_image( &self, background_image: &mut impl ToOutputArray ) -> Result<()>

Computes a background image.

impl BackgroundSubtractorTraitConst for Ptr<CUDA_BackgroundSubtractorMOG2>

fn as_raw_BackgroundSubtractor(&self) -> *const c_void

fn get_background_image( &self, background_image: &mut impl ToOutputArray ) -> Result<()>

Computes a background image.

impl BaseCascadeClassifierTrait for Ptr<BaseCascadeClassifier>

fn as_raw_mut_BaseCascadeClassifier(&mut self) -> *mut c_void

fn load(&mut self, filename: &str) -> Result<bool>

fn detect_multi_scale( &mut self, image: &impl ToInputArray, objects: &mut Vector<Rect>, scale_factor: f64, min_neighbors: i32, flags: i32, min_size: Size, max_size: Size ) -> Result<()>

fn detect_multi_scale_num( &mut self, image: &impl ToInputArray, objects: &mut Vector<Rect>, num_detections: &mut Vector<i32>, scale_factor: f64, min_neighbors: i32, flags: i32, min_size: Size, max_size: Size ) -> Result<()>

fn detect_multi_scale_levels( &mut self, image: &impl ToInputArray, objects: &mut Vector<Rect>, reject_levels: &mut Vector<i32>, level_weights: &mut Vector<f64>, scale_factor: f64, min_neighbors: i32, flags: i32, min_size: Size, max_size: Size, output_reject_levels: bool ) -> Result<()>

fn get_old_cascade(&mut self) -> Result<*mut c_void>

fn set_mask_generator( &mut self, mask_generator: &Ptr<BaseCascadeClassifier_MaskGenerator> ) -> Result<()>

fn get_mask_generator( &mut self ) -> Result<Ptr<BaseCascadeClassifier_MaskGenerator>>

impl BaseCascadeClassifierTraitConst for Ptr<BaseCascadeClassifier>

fn as_raw_BaseCascadeClassifier(&self) -> *const c_void

fn empty(&self) -> Result<bool>

fn is_old_format_cascade(&self) -> Result<bool>

fn get_original_window_size(&self) -> Result<Size>

fn get_feature_type(&self) -> Result<i32>

impl BaseCascadeClassifier_MaskGeneratorTrait for Ptr<BaseCascadeClassifier_MaskGenerator>

fn as_raw_mut_BaseCascadeClassifier_MaskGenerator(&mut self) -> *mut c_void

fn generate_mask(&mut self, src: &impl MatTraitConst) -> Result<Mat>

fn initialize_mask(&mut self, unnamed: &impl MatTraitConst) -> Result<()>

impl BaseCascadeClassifier_MaskGeneratorTraitConst for Ptr<BaseCascadeClassifier_MaskGenerator>

fn as_raw_BaseCascadeClassifier_MaskGenerator(&self) -> *const c_void

impl BaseConvolutionLayerTrait for Ptr<BaseConvolutionLayer>

fn as_raw_mut_BaseConvolutionLayer(&mut self) -> *mut c_void

fn set_kernel(&mut self, val: Size)

fn set_stride(&mut self, val: Size)

fn set_pad(&mut self, val: Size)

fn set_dilation(&mut self, val: Size)

fn set_adjust_pad(&mut self, val: Size)

fn set_adjust_pads(&mut self, val: Vector<size_t>)

fn set_kernel_size(&mut self, val: Vector<size_t>)

fn set_strides(&mut self, val: Vector<size_t>)

fn set_dilations(&mut self, val: Vector<size_t>)

fn set_pads_begin(&mut self, val: Vector<size_t>)

fn set_pads_end(&mut self, val: Vector<size_t>)

fn set_pad_mode(&mut self, val: &str)

fn set_num_output(&mut self, val: i32)

impl BaseConvolutionLayerTrait for Ptr<ConvolutionLayer>

fn as_raw_mut_BaseConvolutionLayer(&mut self) -> *mut c_void

fn set_kernel(&mut self, val: Size)

fn set_stride(&mut self, val: Size)

fn set_pad(&mut self, val: Size)

fn set_dilation(&mut self, val: Size)

fn set_adjust_pad(&mut self, val: Size)

fn set_adjust_pads(&mut self, val: Vector<size_t>)

fn set_kernel_size(&mut self, val: Vector<size_t>)

fn set_strides(&mut self, val: Vector<size_t>)

fn set_dilations(&mut self, val: Vector<size_t>)

fn set_pads_begin(&mut self, val: Vector<size_t>)

fn set_pads_end(&mut self, val: Vector<size_t>)

fn set_pad_mode(&mut self, val: &str)

fn set_num_output(&mut self, val: i32)

impl BaseConvolutionLayerTrait for Ptr<ConvolutionLayerInt8>

fn as_raw_mut_BaseConvolutionLayer(&mut self) -> *mut c_void

fn set_kernel(&mut self, val: Size)

fn set_stride(&mut self, val: Size)

fn set_pad(&mut self, val: Size)

fn set_dilation(&mut self, val: Size)

fn set_adjust_pad(&mut self, val: Size)

fn set_adjust_pads(&mut self, val: Vector<size_t>)

fn set_kernel_size(&mut self, val: Vector<size_t>)

fn set_strides(&mut self, val: Vector<size_t>)

fn set_dilations(&mut self, val: Vector<size_t>)

fn set_pads_begin(&mut self, val: Vector<size_t>)

fn set_pads_end(&mut self, val: Vector<size_t>)

fn set_pad_mode(&mut self, val: &str)

fn set_num_output(&mut self, val: i32)

impl BaseConvolutionLayerTrait for Ptr<DeconvolutionLayer>

fn as_raw_mut_BaseConvolutionLayer(&mut self) -> *mut c_void

fn set_kernel(&mut self, val: Size)

fn set_stride(&mut self, val: Size)

fn set_pad(&mut self, val: Size)

fn set_dilation(&mut self, val: Size)

fn set_adjust_pad(&mut self, val: Size)

fn set_adjust_pads(&mut self, val: Vector<size_t>)

fn set_kernel_size(&mut self, val: Vector<size_t>)

fn set_strides(&mut self, val: Vector<size_t>)

fn set_dilations(&mut self, val: Vector<size_t>)

fn set_pads_begin(&mut self, val: Vector<size_t>)

fn set_pads_end(&mut self, val: Vector<size_t>)

fn set_pad_mode(&mut self, val: &str)

fn set_num_output(&mut self, val: i32)

impl BaseConvolutionLayerTraitConst for Ptr<BaseConvolutionLayer>

fn as_raw_BaseConvolutionLayer(&self) -> *const c_void

fn kernel(&self) -> Size

fn stride(&self) -> Size

fn pad(&self) -> Size

fn dilation(&self) -> Size

fn adjust_pad(&self) -> Size

fn adjust_pads(&self) -> Vector<size_t>

fn kernel_size(&self) -> Vector<size_t>

fn strides(&self) -> Vector<size_t>

fn dilations(&self) -> Vector<size_t>

fn pads_begin(&self) -> Vector<size_t>

fn pads_end(&self) -> Vector<size_t>

fn pad_mode(&self) -> String

fn num_output(&self) -> i32

impl BaseConvolutionLayerTraitConst for Ptr<ConvolutionLayer>

fn as_raw_BaseConvolutionLayer(&self) -> *const c_void

fn kernel(&self) -> Size

fn stride(&self) -> Size

fn pad(&self) -> Size

fn dilation(&self) -> Size

fn adjust_pad(&self) -> Size

fn adjust_pads(&self) -> Vector<size_t>

fn kernel_size(&self) -> Vector<size_t>

fn strides(&self) -> Vector<size_t>

fn dilations(&self) -> Vector<size_t>

fn pads_begin(&self) -> Vector<size_t>

fn pads_end(&self) -> Vector<size_t>

fn pad_mode(&self) -> String

fn num_output(&self) -> i32

impl BaseConvolutionLayerTraitConst for Ptr<ConvolutionLayerInt8>

fn as_raw_BaseConvolutionLayer(&self) -> *const c_void

fn kernel(&self) -> Size

fn stride(&self) -> Size

fn pad(&self) -> Size

fn dilation(&self) -> Size

fn adjust_pad(&self) -> Size

fn adjust_pads(&self) -> Vector<size_t>

fn kernel_size(&self) -> Vector<size_t>

fn strides(&self) -> Vector<size_t>

fn dilations(&self) -> Vector<size_t>

fn pads_begin(&self) -> Vector<size_t>

fn pads_end(&self) -> Vector<size_t>

fn pad_mode(&self) -> String

fn num_output(&self) -> i32

impl BaseConvolutionLayerTraitConst for Ptr<DeconvolutionLayer>

fn as_raw_BaseConvolutionLayer(&self) -> *const c_void

fn kernel(&self) -> Size

fn stride(&self) -> Size

fn pad(&self) -> Size

fn dilation(&self) -> Size

fn adjust_pad(&self) -> Size

fn adjust_pads(&self) -> Vector<size_t>

fn kernel_size(&self) -> Vector<size_t>

fn strides(&self) -> Vector<size_t>

fn dilations(&self) -> Vector<size_t>

fn pads_begin(&self) -> Vector<size_t>

fn pads_end(&self) -> Vector<size_t>

fn pad_mode(&self) -> String

fn num_output(&self) -> i32

impl BaseOCRTrait for Ptr<BaseOCR>

fn as_raw_mut_BaseOCR(&mut self) -> *mut c_void

fn run( &mut self, image: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

C++ default parameters

fn run_def( &mut self, image: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Note

fn run_mask( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

C++ default parameters

fn run_mask_def( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Note

impl BaseOCRTrait for Ptr<OCRBeamSearchDecoder>

fn as_raw_mut_BaseOCR(&mut self) -> *mut c_void

fn run( &mut self, image: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

C++ default parameters

fn run_def( &mut self, image: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Note

fn run_mask( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

C++ default parameters

fn run_mask_def( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Note

impl BaseOCRTrait for Ptr<OCRHMMDecoder>

fn as_raw_mut_BaseOCR(&mut self) -> *mut c_void

fn run( &mut self, image: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

C++ default parameters

fn run_def( &mut self, image: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Note

fn run_mask( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

C++ default parameters

fn run_mask_def( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Note

impl BaseOCRTrait for Ptr<OCRHolisticWordRecognizer>

fn as_raw_mut_BaseOCR(&mut self) -> *mut c_void

fn run( &mut self, image: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

C++ default parameters

fn run_def( &mut self, image: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Note

fn run_mask( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

C++ default parameters

fn run_mask_def( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Note

impl BaseOCRTrait for Ptr<OCRTesseract>

fn as_raw_mut_BaseOCR(&mut self) -> *mut c_void

fn run( &mut self, image: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

C++ default parameters

fn run_def( &mut self, image: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Note

fn run_mask( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

C++ default parameters

fn run_mask_def( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Note

impl BaseOCRTraitConst for Ptr<BaseOCR>

fn as_raw_BaseOCR(&self) -> *const c_void

impl BaseOCRTraitConst for Ptr<OCRBeamSearchDecoder>

fn as_raw_BaseOCR(&self) -> *const c_void

impl BaseOCRTraitConst for Ptr<OCRHMMDecoder>

fn as_raw_BaseOCR(&self) -> *const c_void

impl BaseOCRTraitConst for Ptr<OCRHolisticWordRecognizer>

fn as_raw_BaseOCR(&self) -> *const c_void

impl BaseOCRTraitConst for Ptr<OCRTesseract>

fn as_raw_BaseOCR(&self) -> *const c_void

impl BaseSFMTrait for Ptr<BaseSFM>

fn as_raw_mut_BaseSFM(&mut self) -> *mut c_void

fn run(&mut self, points2d: &impl ToInputArray) -> Result<()>

fn run_1( &mut self, points2d: &impl ToInputArray, k: &mut impl ToInputOutputArray, rs: &mut impl ToOutputArray, ts: &mut impl ToOutputArray, points3d: &mut impl ToOutputArray ) -> Result<()>

fn run_2(&mut self, images: &Vector<String>) -> Result<()>

fn run_3( &mut self, images: &Vector<String>, k: &mut impl ToInputOutputArray, rs: &mut impl ToOutputArray, ts: &mut impl ToOutputArray, points3d: &mut impl ToOutputArray ) -> Result<()>

fn get_points(&mut self, points3d: &mut impl ToOutputArray) -> Result<()>

fn get_cameras( &mut self, rs: &mut impl ToOutputArray, ts: &mut impl ToOutputArray ) -> Result<()>

fn set_reconstruction_options( &mut self, libmv_reconstruction_options: libmv_ReconstructionOptions ) -> Result<()>

fn set_camera_intrinsic_options( &mut self, libmv_camera_intrinsics_options: libmv_CameraIntrinsicsOptions ) -> Result<()>

impl BaseSFMTrait for Ptr<SFMLibmvEuclideanReconstruction>

fn as_raw_mut_BaseSFM(&mut self) -> *mut c_void

fn run(&mut self, points2d: &impl ToInputArray) -> Result<()>

fn run_1( &mut self, points2d: &impl ToInputArray, k: &mut impl ToInputOutputArray, rs: &mut impl ToOutputArray, ts: &mut impl ToOutputArray, points3d: &mut impl ToOutputArray ) -> Result<()>

fn run_2(&mut self, images: &Vector<String>) -> Result<()>

fn run_3( &mut self, images: &Vector<String>, k: &mut impl ToInputOutputArray, rs: &mut impl ToOutputArray, ts: &mut impl ToOutputArray, points3d: &mut impl ToOutputArray ) -> Result<()>

fn get_points(&mut self, points3d: &mut impl ToOutputArray) -> Result<()>

fn get_cameras( &mut self, rs: &mut impl ToOutputArray, ts: &mut impl ToOutputArray ) -> Result<()>

fn set_reconstruction_options( &mut self, libmv_reconstruction_options: libmv_ReconstructionOptions ) -> Result<()>

fn set_camera_intrinsic_options( &mut self, libmv_camera_intrinsics_options: libmv_CameraIntrinsicsOptions ) -> Result<()>

impl BaseSFMTraitConst for Ptr<BaseSFM>

fn as_raw_BaseSFM(&self) -> *const c_void

fn get_error(&self) -> Result<f64>

fn get_intrinsics(&self) -> Result<Mat>

impl BaseSFMTraitConst for Ptr<SFMLibmvEuclideanReconstruction>

fn as_raw_BaseSFM(&self) -> *const c_void

fn get_error(&self) -> Result<f64>

fn get_intrinsics(&self) -> Result<Mat>

impl BasicFaceRecognizerTrait for Ptr<BasicFaceRecognizer>

fn as_raw_mut_BasicFaceRecognizer(&mut self) -> *mut c_void

fn set_num_components(&mut self, val: i32) -> Result<()>

See also

fn set_threshold(&mut self, val: f64) -> Result<()>

See also

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

impl BasicFaceRecognizerTrait for Ptr<EigenFaceRecognizer>

fn as_raw_mut_BasicFaceRecognizer(&mut self) -> *mut c_void

fn set_num_components(&mut self, val: i32) -> Result<()>

See also

fn set_threshold(&mut self, val: f64) -> Result<()>

See also

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

impl BasicFaceRecognizerTrait for Ptr<FisherFaceRecognizer>

fn as_raw_mut_BasicFaceRecognizer(&mut self) -> *mut c_void

fn set_num_components(&mut self, val: i32) -> Result<()>

See also

fn set_threshold(&mut self, val: f64) -> Result<()>

See also

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

impl BasicFaceRecognizerTraitConst for Ptr<BasicFaceRecognizer>

fn as_raw_BasicFaceRecognizer(&self) -> *const c_void

fn get_num_components(&self) -> Result<i32>

See also

fn get_threshold(&self) -> Result<f64>

See also

fn get_projections(&self) -> Result<Vector<Mat>>

fn get_labels(&self) -> Result<Mat>

fn get_eigen_values(&self) -> Result<Mat>

fn get_eigen_vectors(&self) -> Result<Mat>

fn get_mean(&self) -> Result<Mat>

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

impl BasicFaceRecognizerTraitConst for Ptr<EigenFaceRecognizer>

fn as_raw_BasicFaceRecognizer(&self) -> *const c_void

fn get_num_components(&self) -> Result<i32>

See also

fn get_threshold(&self) -> Result<f64>

See also

fn get_projections(&self) -> Result<Vector<Mat>>

fn get_labels(&self) -> Result<Mat>

fn get_eigen_values(&self) -> Result<Mat>

fn get_eigen_vectors(&self) -> Result<Mat>

fn get_mean(&self) -> Result<Mat>

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

impl BasicFaceRecognizerTraitConst for Ptr<FisherFaceRecognizer>

fn as_raw_BasicFaceRecognizer(&self) -> *const c_void

fn get_num_components(&self) -> Result<i32>

See also

fn get_threshold(&self) -> Result<f64>

See also

fn get_projections(&self) -> Result<Vector<Mat>>

fn get_labels(&self) -> Result<Mat>

fn get_eigen_values(&self) -> Result<Mat>

fn get_eigen_vectors(&self) -> Result<Mat>

fn get_mean(&self) -> Result<Mat>

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

impl BatchNormLayerInt8Trait for Ptr<BatchNormLayerInt8>

fn as_raw_mut_BatchNormLayerInt8(&mut self) -> *mut c_void

fn set_input_sc(&mut self, val: f32)

fn set_output_sc(&mut self, val: f32)

fn set_input_zp(&mut self, val: i32)

fn set_output_zp(&mut self, val: i32)

impl BatchNormLayerInt8TraitConst for Ptr<BatchNormLayerInt8>

fn as_raw_BatchNormLayerInt8(&self) -> *const c_void

fn input_sc(&self) -> f32

fn output_sc(&self) -> f32

fn input_zp(&self) -> i32

fn output_zp(&self) -> i32

impl BatchNormLayerTrait for Ptr<BatchNormLayer>

fn as_raw_mut_BatchNormLayer(&mut self) -> *mut c_void

fn set_has_weights(&mut self, val: bool)

fn set_has_bias(&mut self, val: bool)

fn set_epsilon(&mut self, val: f32)

impl BatchNormLayerTrait for Ptr<BatchNormLayerInt8>

fn as_raw_mut_BatchNormLayer(&mut self) -> *mut c_void

fn set_has_weights(&mut self, val: bool)

fn set_has_bias(&mut self, val: bool)

fn set_epsilon(&mut self, val: f32)

impl BatchNormLayerTraitConst for Ptr<BatchNormLayer>

fn as_raw_BatchNormLayer(&self) -> *const c_void

fn has_weights(&self) -> bool

fn has_bias(&self) -> bool

fn epsilon(&self) -> f32

impl BatchNormLayerTraitConst for Ptr<BatchNormLayerInt8>

fn as_raw_BatchNormLayer(&self) -> *const c_void

fn has_weights(&self) -> bool

fn has_bias(&self) -> bool

fn epsilon(&self) -> f32

impl BinaryDescriptorMatcherTrait for Ptr<BinaryDescriptorMatcher>

fn as_raw_mut_BinaryDescriptorMatcher(&mut self) -> *mut c_void

fn match_query( &mut self, query_descriptors: &impl MatTraitConst, matches: &mut Vector<DMatch>, masks: &Vector<Mat> ) -> Result<()>

For every input query descriptor, retrieve the best matching one from a dataset provided from user or from the one internal to class

fn match_query_def( &mut self, query_descriptors: &impl MatTraitConst, matches: &mut Vector<DMatch> ) -> Result<()>

@overload

fn knn_match_query( &mut self, query_descriptors: &impl MatTraitConst, matches: &mut Vector<Vector<DMatch>>, k: i32, masks: &Vector<Mat>, compact_result: bool ) -> Result<()>

For every input query descriptor, retrieve the best k matching ones from a dataset provided from user or from the one internal to class

fn knn_match_query_def( &mut self, query_descriptors: &impl MatTraitConst, matches: &mut Vector<Vector<DMatch>>, k: i32 ) -> Result<()>

@overload

fn radius_match_1( &mut self, query_descriptors: &impl MatTraitConst, matches: &mut Vector<Vector<DMatch>>, max_distance: f32, masks: &Vector<Mat>, compact_result: bool ) -> Result<()>

For every input query descriptor, retrieve, from a dataset provided from user or from the one internal to class, all the descriptors that are not further than maxDist from input query

fn radius_match_def_1( &mut self, query_descriptors: &impl MatTraitConst, matches: &mut Vector<Vector<DMatch>>, max_distance: f32 ) -> Result<()>

@overload

fn add(&mut self, descriptors: &Vector<Mat>) -> Result<()>

Store locally new descriptors to be inserted in dataset, without updating dataset.

fn train(&mut self) -> Result<()>

Update dataset by inserting into it all descriptors that were stored locally by add function.

fn clear(&mut self) -> Result<()>

Clear dataset and internal data

impl BinaryDescriptorMatcherTraitConst for Ptr<BinaryDescriptorMatcher>

fn as_raw_BinaryDescriptorMatcher(&self) -> *const c_void

fn match_( &self, query_descriptors: &impl MatTraitConst, train_descriptors: &impl MatTraitConst, matches: &mut Vector<DMatch>, mask: &impl MatTraitConst ) -> Result<()>

For every input query descriptor, retrieve the best matching one from a dataset provided from user or from the one internal to class

fn match__def( &self, query_descriptors: &impl MatTraitConst, train_descriptors: &impl MatTraitConst, matches: &mut Vector<DMatch> ) -> Result<()>

For every input query descriptor, retrieve the best matching one from a dataset provided from user or from the one internal to class

fn knn_match( &self, query_descriptors: &impl MatTraitConst, train_descriptors: &impl MatTraitConst, matches: &mut Vector<Vector<DMatch>>, k: i32, mask: &impl MatTraitConst, compact_result: bool ) -> Result<()>

For every input query descriptor, retrieve the best k matching ones from a dataset provided from user or from the one internal to class

fn knn_match_def( &self, query_descriptors: &impl MatTraitConst, train_descriptors: &impl MatTraitConst, matches: &mut Vector<Vector<DMatch>>, k: i32 ) -> Result<()>

For every input query descriptor, retrieve the best k matching ones from a dataset provided from user or from the one internal to class

fn radius_match( &self, query_descriptors: &impl MatTraitConst, train_descriptors: &impl MatTraitConst, matches: &mut Vector<Vector<DMatch>>, max_distance: f32, mask: &impl MatTraitConst, compact_result: bool ) -> Result<()>

For every input query descriptor, retrieve, from a dataset provided from user or from the one internal to class, all the descriptors that are not further than maxDist from input query

fn radius_match_def( &self, query_descriptors: &impl MatTraitConst, train_descriptors: &impl MatTraitConst, matches: &mut Vector<Vector<DMatch>>, max_distance: f32 ) -> Result<()>

For every input query descriptor, retrieve, from a dataset provided from user or from the one internal to class, all the descriptors that are not further than maxDist from input query

impl BinaryDescriptorTrait for Ptr<BinaryDescriptor>

fn as_raw_mut_BinaryDescriptor(&mut self) -> *mut c_void

fn get_num_of_octaves(&mut self) -> Result<i32>

Get current number of octaves

fn set_num_of_octaves(&mut self, octaves: i32) -> Result<()>

Set number of octaves

fn get_width_of_band(&mut self) -> Result<i32>

Get current width of bands

fn set_width_of_band(&mut self, width: i32) -> Result<()>

Set width of bands

fn get_reduction_ratio(&mut self) -> Result<i32>

Get current reduction ratio (used in Gaussian pyramids)

fn set_reduction_ratio(&mut self, r_ratio: i32) -> Result<()>

Set reduction ratio (used in Gaussian pyramids)

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Read parameters from a FileNode object and store them

fn detect_1( &mut self, image: &impl MatTraitConst, keypoints: &mut Vector<KeyLine>, mask: &impl MatTraitConst ) -> Result<()>

Requires line detection

fn detect_def_1( &mut self, image: &impl MatTraitConst, keypoints: &mut Vector<KeyLine> ) -> Result<()>

Requires line detection

impl BinaryDescriptorTraitConst for Ptr<BinaryDescriptor>

fn as_raw_BinaryDescriptor(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Store parameters to a FileStorage object

fn detect( &self, images: &Vector<Mat>, keylines: &mut Vector<Vector<KeyLine>>, masks: &Vector<Mat> ) -> Result<()>

Requires line detection

fn detect_def( &self, images: &Vector<Mat>, keylines: &mut Vector<Vector<KeyLine>> ) -> Result<()>

@overload

fn compute( &self, image: &impl MatTraitConst, keylines: &mut Vector<KeyLine>, descriptors: &mut impl MatTrait, return_float_descr: bool ) -> Result<()>

Requires descriptors computation

fn compute_def( &self, image: &impl MatTraitConst, keylines: &mut Vector<KeyLine>, descriptors: &mut impl MatTrait ) -> Result<()>

Requires descriptors computation

fn compute_1( &self, images: &Vector<Mat>, keylines: &mut Vector<Vector<KeyLine>>, descriptors: &mut Vector<Mat>, return_float_descr: bool ) -> Result<()>

Requires descriptors computation

fn compute_def_1( &self, images: &Vector<Mat>, keylines: &mut Vector<Vector<KeyLine>>, descriptors: &mut Vector<Mat> ) -> Result<()>

@overload

fn descriptor_size(&self) -> Result<i32>

Return descriptor size

fn descriptor_type(&self) -> Result<i32>

Return data type

fn default_norm(&self) -> Result<i32>

returns norm mode

fn apply( &self, image: &impl ToInputArray, mask: &impl ToInputArray, keylines: &mut Vector<KeyLine>, descriptors: &mut impl ToOutputArray, use_provided_key_lines: bool, return_float_descr: bool ) -> Result<()>

Define operator ‘()’ to perform detection of KeyLines and computation of descriptors in a row.

fn apply_def( &self, image: &impl ToInputArray, mask: &impl ToInputArray, keylines: &mut Vector<KeyLine>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Define operator ‘()’ to perform detection of KeyLines and computation of descriptors in a row.

impl BlankLayerTrait for Ptr<BlankLayer>

fn as_raw_mut_BlankLayer(&mut self) -> *mut c_void

impl BlankLayerTraitConst for Ptr<BlankLayer>

fn as_raw_BlankLayer(&self) -> *const c_void

impl BlockMeanHashTrait for Ptr<BlockMeanHash>

fn as_raw_mut_BlockMeanHash(&mut self) -> *mut c_void

fn set_mode(&mut self, mode: i32) -> Result<()>

Create BlockMeanHash object

impl BlockMeanHashTraitConst for Ptr<BlockMeanHash>

fn as_raw_BlockMeanHash(&self) -> *const c_void

fn get_mean(&self) -> Result<Vector<f64>>

impl BoardTrait for Ptr<Board>

fn as_raw_mut_Board(&mut self) -> *mut c_void

impl BoardTrait for Ptr<CharucoBoard>

fn as_raw_mut_Board(&mut self) -> *mut c_void

impl BoardTrait for Ptr<GridBoard>

fn as_raw_mut_Board(&mut self) -> *mut c_void

impl BoardTraitConst for Ptr<Board>

fn as_raw_Board(&self) -> *const c_void

fn get_dictionary(&self) -> Result<Dictionary>

return the Dictionary of markers employed for this board

fn get_obj_points(&self) -> Result<Vector<Vector<Point3f>>>

return array of object points of all the marker corners in the board.

fn get_ids(&self) -> Result<Vector<i32>>

vector of the identifiers of the markers in the board (should be the same size as objPoints)

fn get_right_bottom_corner(&self) -> Result<Point3f>

get coordinate of the bottom right corner of the board, is set when calling the function create()

fn match_image_points( &self, detected_corners: &impl ToInputArray, detected_ids: &impl ToInputArray, obj_points: &mut impl ToOutputArray, img_points: &mut impl ToOutputArray ) -> Result<()>

Given a board configuration and a set of detected markers, returns the corresponding image points and object points, can be used in solvePnP()

fn generate_image( &self, out_size: Size, img: &mut impl ToOutputArray, margin_size: i32, border_bits: i32 ) -> Result<()>

Draw a planar board

fn generate_image_def( &self, out_size: Size, img: &mut impl ToOutputArray ) -> Result<()>

Draw a planar board

impl BoardTraitConst for Ptr<CharucoBoard>

fn as_raw_Board(&self) -> *const c_void

fn get_dictionary(&self) -> Result<Dictionary>

return the Dictionary of markers employed for this board

fn get_obj_points(&self) -> Result<Vector<Vector<Point3f>>>

return array of object points of all the marker corners in the board.

fn get_ids(&self) -> Result<Vector<i32>>

vector of the identifiers of the markers in the board (should be the same size as objPoints)

fn get_right_bottom_corner(&self) -> Result<Point3f>

get coordinate of the bottom right corner of the board, is set when calling the function create()

fn match_image_points( &self, detected_corners: &impl ToInputArray, detected_ids: &impl ToInputArray, obj_points: &mut impl ToOutputArray, img_points: &mut impl ToOutputArray ) -> Result<()>

Given a board configuration and a set of detected markers, returns the corresponding image points and object points, can be used in solvePnP()

fn generate_image( &self, out_size: Size, img: &mut impl ToOutputArray, margin_size: i32, border_bits: i32 ) -> Result<()>

Draw a planar board

fn generate_image_def( &self, out_size: Size, img: &mut impl ToOutputArray ) -> Result<()>

Draw a planar board

impl BoardTraitConst for Ptr<GridBoard>

fn as_raw_Board(&self) -> *const c_void

fn get_dictionary(&self) -> Result<Dictionary>

return the Dictionary of markers employed for this board

fn get_obj_points(&self) -> Result<Vector<Vector<Point3f>>>

return array of object points of all the marker corners in the board.

fn get_ids(&self) -> Result<Vector<i32>>

vector of the identifiers of the markers in the board (should be the same size as objPoints)

fn get_right_bottom_corner(&self) -> Result<Point3f>

get coordinate of the bottom right corner of the board, is set when calling the function create()

fn match_image_points( &self, detected_corners: &impl ToInputArray, detected_ids: &impl ToInputArray, obj_points: &mut impl ToOutputArray, img_points: &mut impl ToOutputArray ) -> Result<()>

Given a board configuration and a set of detected markers, returns the corresponding image points and object points, can be used in solvePnP()

fn generate_image( &self, out_size: Size, img: &mut impl ToOutputArray, margin_size: i32, border_bits: i32 ) -> Result<()>

Draw a planar board

fn generate_image_def( &self, out_size: Size, img: &mut impl ToOutputArray ) -> Result<()>

Draw a planar board

impl BoostDescTrait for Ptr<BoostDesc>

fn as_raw_mut_BoostDesc(&mut self) -> *mut c_void

fn set_use_scale_orientation( &mut self, use_scale_orientation: bool ) -> Result<()>

fn set_scale_factor(&mut self, scale_factor: f32) -> Result<()>

impl BoostDescTraitConst for Ptr<BoostDesc>

fn as_raw_BoostDesc(&self) -> *const c_void

fn get_default_name(&self) -> Result<String>

fn get_use_scale_orientation(&self) -> Result<bool>

fn get_scale_factor(&self) -> Result<f32>

impl BoostTrait for Ptr<Boost>

fn as_raw_mut_Boost(&mut self) -> *mut c_void

fn set_boost_type(&mut self, val: i32) -> Result<()>

Type of the boosting algorithm. See Boost::Types. Default value is Boost::REAL.

fn set_weak_count(&mut self, val: i32) -> Result<()>

The number of weak classifiers. Default value is 100.

fn set_weight_trim_rate(&mut self, val: f64) -> Result<()>

A threshold between 0 and 1 used to save computational time. Samples with summary weight inline formula do not participate in the next iteration of training. Set this parameter to 0 to turn off this functionality. Default value is 0.95.

impl BoostTraitConst for Ptr<Boost>

fn as_raw_Boost(&self) -> *const c_void

fn get_boost_type(&self) -> Result<i32>

Type of the boosting algorithm. See Boost::Types. Default value is Boost::REAL.

fn get_weak_count(&self) -> Result<i32>

The number of weak classifiers. Default value is 100.

fn get_weight_trim_rate(&self) -> Result<f64>

A threshold between 0 and 1 used to save computational time. Samples with summary weight inline formula do not participate in the next iteration of training. Set this parameter to 0 to turn off this functionality. Default value is 0.95.

impl<T: ?Sized> Boxed for Ptr<T>

where Self: PtrExtern,

unsafe fn from_raw(ptr: *mut c_void) -> Self

Wrap the specified raw pointer

fn into_raw(self) -> *mut c_void

Return the underlying raw pointer while consuming this wrapper.

fn as_raw(&self) -> *const c_void

Return the underlying raw pointer.

fn as_raw_mut(&mut self) -> *mut c_void

Return the underlying mutable raw pointer

impl BriefDescriptorExtractorTrait for Ptr<BriefDescriptorExtractor>

fn as_raw_mut_BriefDescriptorExtractor(&mut self) -> *mut c_void

fn set_descriptor_size(&mut self, bytes: i32) -> Result<()>

fn set_use_orientation(&mut self, use_orientation: bool) -> Result<()>

impl BriefDescriptorExtractorTraitConst for Ptr<BriefDescriptorExtractor>

fn as_raw_BriefDescriptorExtractor(&self) -> *const c_void

fn get_descriptor_size(&self) -> Result<i32>

fn get_use_orientation(&self) -> Result<bool>

fn get_default_name(&self) -> Result<String>

impl CLAHETrait for Ptr<CLAHE>

fn as_raw_mut_CLAHE(&mut self) -> *mut c_void

fn apply( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Equalizes the histogram of a grayscale image using Contrast Limited Adaptive Histogram Equalization.

fn set_clip_limit(&mut self, clip_limit: f64) -> Result<()>

Sets threshold for contrast limiting.

fn set_tiles_grid_size(&mut self, tile_grid_size: Size) -> Result<()>

Sets size of grid for histogram equalization. Input image will be divided into equally sized rectangular tiles.

fn collect_garbage(&mut self) -> Result<()>

impl CLAHETrait for Ptr<CUDA_CLAHE>

fn as_raw_mut_CLAHE(&mut self) -> *mut c_void

fn apply( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Equalizes the histogram of a grayscale image using Contrast Limited Adaptive Histogram Equalization.

fn set_clip_limit(&mut self, clip_limit: f64) -> Result<()>

Sets threshold for contrast limiting.

fn set_tiles_grid_size(&mut self, tile_grid_size: Size) -> Result<()>

Sets size of grid for histogram equalization. Input image will be divided into equally sized rectangular tiles.

fn collect_garbage(&mut self) -> Result<()>

impl CLAHETraitConst for Ptr<CLAHE>

fn as_raw_CLAHE(&self) -> *const c_void

fn get_clip_limit(&self) -> Result<f64>

Returns threshold value for contrast limiting.

fn get_tiles_grid_size(&self) -> Result<Size>

Returns Size defines the number of tiles in row and column.

impl CLAHETraitConst for Ptr<CUDA_CLAHE>

fn as_raw_CLAHE(&self) -> *const c_void

fn get_clip_limit(&self) -> Result<f64>

Returns threshold value for contrast limiting.

fn get_tiles_grid_size(&self) -> Result<Size>

Returns Size defines the number of tiles in row and column.

impl CUDA_BackgroundSubtractorMOG2Trait for Ptr<CUDA_BackgroundSubtractorMOG2>

fn as_raw_mut_CUDA_BackgroundSubtractorMOG2(&mut self) -> *mut c_void

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64, stream: &mut impl StreamTrait ) -> Result<()>

fn get_background_image_1( &mut self, background_image: &mut impl GpuMatTrait, stream: &mut impl StreamTrait ) -> Result<()>

impl CUDA_BackgroundSubtractorMOG2TraitConst for Ptr<CUDA_BackgroundSubtractorMOG2>

fn as_raw_CUDA_BackgroundSubtractorMOG2(&self) -> *const c_void

fn get_background_image( &self, background_image: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

impl CUDA_BackgroundSubtractorMOGTrait for Ptr<CUDA_BackgroundSubtractorMOG>

fn as_raw_mut_CUDA_BackgroundSubtractorMOG(&mut self) -> *mut c_void

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64, stream: &mut impl StreamTrait ) -> Result<()>

fn get_background_image_1( &mut self, background_image: &mut impl GpuMatTrait, stream: &mut impl StreamTrait ) -> Result<()>

fn set_history(&mut self, nframes: i32) -> Result<()>

fn set_n_mixtures(&mut self, nmix: i32) -> Result<()>

fn set_background_ratio(&mut self, background_ratio: f64) -> Result<()>

fn set_noise_sigma(&mut self, noise_sigma: f64) -> Result<()>

impl CUDA_BackgroundSubtractorMOGTraitConst for Ptr<CUDA_BackgroundSubtractorMOG>

fn as_raw_CUDA_BackgroundSubtractorMOG(&self) -> *const c_void

fn get_background_image( &self, background_image: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

fn get_history(&self) -> Result<i32>

fn get_n_mixtures(&self) -> Result<i32>

fn get_background_ratio(&self) -> Result<f64>

fn get_noise_sigma(&self) -> Result<f64>

impl CUDA_BroxOpticalFlowTrait for Ptr<CUDA_BroxOpticalFlow>

fn as_raw_mut_CUDA_BroxOpticalFlow(&mut self) -> *mut c_void

fn set_flow_smoothness(&mut self, alpha: f64) -> Result<()>

fn set_gradient_constancy_importance(&mut self, gamma: f64) -> Result<()>

fn set_pyramid_scale_factor(&mut self, scale_factor: f64) -> Result<()>

fn set_inner_iterations(&mut self, inner_iterations: i32) -> Result<()>

fn set_outer_iterations(&mut self, outer_iterations: i32) -> Result<()>

fn set_solver_iterations(&mut self, solver_iterations: i32) -> Result<()>

impl CUDA_BroxOpticalFlowTraitConst for Ptr<CUDA_BroxOpticalFlow>

fn as_raw_CUDA_BroxOpticalFlow(&self) -> *const c_void

fn get_flow_smoothness(&self) -> Result<f64>

fn get_gradient_constancy_importance(&self) -> Result<f64>

fn get_pyramid_scale_factor(&self) -> Result<f64>

fn get_inner_iterations(&self) -> Result<i32>

number of lagged non-linearity iterations (inner loop)

fn get_outer_iterations(&self) -> Result<i32>

number of warping iterations (number of pyramid levels)

fn get_solver_iterations(&self) -> Result<i32>

number of linear system solver iterations

impl CUDA_CLAHETrait for Ptr<CUDA_CLAHE>

fn as_raw_mut_CUDA_CLAHE(&mut self) -> *mut c_void

fn apply( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Equalizes the histogram of a grayscale image using Contrast Limited Adaptive Histogram Equalization.

impl CUDA_CLAHETraitConst for Ptr<CUDA_CLAHE>

fn as_raw_CUDA_CLAHE(&self) -> *const c_void

impl CUDA_CannyEdgeDetectorTrait for Ptr<CUDA_CannyEdgeDetector>

fn as_raw_mut_CUDA_CannyEdgeDetector(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, edges: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Finds edges in an image using the Canny86 algorithm.

fn detect_def( &mut self, image: &impl ToInputArray, edges: &mut impl ToOutputArray ) -> Result<()>

Finds edges in an image using the Canny86 algorithm.

fn detect_1( &mut self, dx: &impl ToInputArray, dy: &impl ToInputArray, edges: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Finds edges in an image using the Canny86 algorithm.

fn detect_def_1( &mut self, dx: &impl ToInputArray, dy: &impl ToInputArray, edges: &mut impl ToOutputArray ) -> Result<()>

@overload

fn set_low_threshold(&mut self, low_thresh: f64) -> Result<()>

fn set_high_threshold(&mut self, high_thresh: f64) -> Result<()>

fn set_apperture_size(&mut self, apperture_size: i32) -> Result<()>

fn set_l2_gradient(&mut self, l2gradient: bool) -> Result<()>

impl CUDA_CannyEdgeDetectorTraitConst for Ptr<CUDA_CannyEdgeDetector>

fn as_raw_CUDA_CannyEdgeDetector(&self) -> *const c_void

fn get_low_threshold(&self) -> Result<f64>

fn get_high_threshold(&self) -> Result<f64>

fn get_apperture_size(&self) -> Result<i32>

fn get_l2_gradient(&self) -> Result<bool>

impl CUDA_CascadeClassifierTrait for Ptr<CUDA_CascadeClassifier>

fn as_raw_mut_CUDA_CascadeClassifier(&mut self) -> *mut c_void

fn set_max_object_size(&mut self, max_object_size: Size) -> Result<()>

Maximum possible object size. Objects larger than that are ignored. Used for second signature and supported only for LBP cascades.

fn set_min_object_size(&mut self, min_size: Size) -> Result<()>

Minimum possible object size. Objects smaller than that are ignored.

fn set_scale_factor(&mut self, scale_factor: f64) -> Result<()>

Parameter specifying how much the image size is reduced at each image scale.

fn set_min_neighbors(&mut self, min_neighbors: i32) -> Result<()>

Parameter specifying how many neighbors each candidate rectangle should have to retain it.

fn set_find_largest_object(&mut self, find_largest_object: bool) -> Result<()>

fn get_find_largest_object(&mut self) -> Result<bool>

fn set_max_num_objects(&mut self, max_num_objects: i32) -> Result<()>

fn detect_multi_scale( &mut self, image: &impl ToInputArray, objects: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Detects objects of different sizes in the input image.

fn detect_multi_scale_def( &mut self, image: &impl ToInputArray, objects: &mut impl ToOutputArray ) -> Result<()>

Detects objects of different sizes in the input image.

fn convert( &mut self, gpu_objects: &mut impl ToOutputArray, objects: &mut Vector<Rect> ) -> Result<()>

Converts objects array from internal representation to standard vector.

impl CUDA_CascadeClassifierTraitConst for Ptr<CUDA_CascadeClassifier>

fn as_raw_CUDA_CascadeClassifier(&self) -> *const c_void

fn get_max_object_size(&self) -> Result<Size>

fn get_min_object_size(&self) -> Result<Size>

fn get_scale_factor(&self) -> Result<f64>

fn get_min_neighbors(&self) -> Result<i32>

fn get_max_num_objects(&self) -> Result<i32>

fn get_classifier_size(&self) -> Result<Size>

impl CUDA_CornernessCriteriaTrait for Ptr<CUDA_CornernessCriteria>

fn as_raw_mut_CUDA_CornernessCriteria(&mut self) -> *mut c_void

fn compute( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Computes the cornerness criteria at each image pixel.

fn compute_def( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Computes the cornerness criteria at each image pixel.

impl CUDA_CornernessCriteriaTraitConst for Ptr<CUDA_CornernessCriteria>

fn as_raw_CUDA_CornernessCriteria(&self) -> *const c_void

impl CUDA_CornersDetectorTrait for Ptr<CUDA_CornersDetector>

fn as_raw_mut_CUDA_CornersDetector(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, corners: &mut impl ToOutputArray, mask: &impl ToInputArray, stream: &mut impl StreamTrait ) -> Result<()>

Determines strong corners on an image.

fn detect_def( &mut self, image: &impl ToInputArray, corners: &mut impl ToOutputArray ) -> Result<()>

Determines strong corners on an image.

impl CUDA_CornersDetectorTraitConst for Ptr<CUDA_CornersDetector>

fn as_raw_CUDA_CornersDetector(&self) -> *const c_void

impl CUDA_DenseOpticalFlowTrait for Ptr<CUDA_BroxOpticalFlow>

fn as_raw_mut_CUDA_DenseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Calculates a dense optical flow.

fn calc_def( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates a dense optical flow.

impl CUDA_DenseOpticalFlowTrait for Ptr<CUDA_DenseOpticalFlow>

fn as_raw_mut_CUDA_DenseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Calculates a dense optical flow.

fn calc_def( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates a dense optical flow.

impl CUDA_DenseOpticalFlowTrait for Ptr<CUDA_DensePyrLKOpticalFlow>

fn as_raw_mut_CUDA_DenseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Calculates a dense optical flow.

fn calc_def( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates a dense optical flow.

impl CUDA_DenseOpticalFlowTrait for Ptr<CUDA_FarnebackOpticalFlow>

fn as_raw_mut_CUDA_DenseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Calculates a dense optical flow.

fn calc_def( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates a dense optical flow.

impl CUDA_DenseOpticalFlowTrait for Ptr<CUDA_OpticalFlowDual_TVL1>

fn as_raw_mut_CUDA_DenseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Calculates a dense optical flow.

fn calc_def( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates a dense optical flow.

impl CUDA_DenseOpticalFlowTraitConst for Ptr<CUDA_BroxOpticalFlow>

fn as_raw_CUDA_DenseOpticalFlow(&self) -> *const c_void

impl CUDA_DenseOpticalFlowTraitConst for Ptr<CUDA_DenseOpticalFlow>

fn as_raw_CUDA_DenseOpticalFlow(&self) -> *const c_void

impl CUDA_DenseOpticalFlowTraitConst for Ptr<CUDA_DensePyrLKOpticalFlow>

fn as_raw_CUDA_DenseOpticalFlow(&self) -> *const c_void

impl CUDA_DenseOpticalFlowTraitConst for Ptr<CUDA_FarnebackOpticalFlow>

fn as_raw_CUDA_DenseOpticalFlow(&self) -> *const c_void

impl CUDA_DenseOpticalFlowTraitConst for Ptr<CUDA_OpticalFlowDual_TVL1>

fn as_raw_CUDA_DenseOpticalFlow(&self) -> *const c_void

impl CUDA_DensePyrLKOpticalFlowTrait for Ptr<CUDA_DensePyrLKOpticalFlow>

fn as_raw_mut_CUDA_DensePyrLKOpticalFlow(&mut self) -> *mut c_void

fn set_win_size(&mut self, win_size: Size) -> Result<()>

fn set_max_level(&mut self, max_level: i32) -> Result<()>

fn set_num_iters(&mut self, iters: i32) -> Result<()>

fn set_use_initial_flow(&mut self, use_initial_flow: bool) -> Result<()>

impl CUDA_DensePyrLKOpticalFlowTraitConst for Ptr<CUDA_DensePyrLKOpticalFlow>

fn as_raw_CUDA_DensePyrLKOpticalFlow(&self) -> *const c_void

fn get_win_size(&self) -> Result<Size>

fn get_max_level(&self) -> Result<i32>

fn get_num_iters(&self) -> Result<i32>

fn get_use_initial_flow(&self) -> Result<bool>

impl CUDA_DescriptorMatcherTrait for Ptr<CUDA_DescriptorMatcher>

fn as_raw_mut_CUDA_DescriptorMatcher(&mut self) -> *mut c_void

fn add(&mut self, descriptors: &Vector<GpuMat>) -> Result<()>

Adds descriptors to train a descriptor collection.

fn clear(&mut self) -> Result<()>

Clears the train descriptor collection.

fn train(&mut self) -> Result<()>

Trains a descriptor matcher.

fn match_( &mut self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch>, mask: &impl ToInputArray ) -> Result<()>

Finds the best match for each descriptor from a query set (blocking version).

fn match__def( &mut self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch> ) -> Result<()>

Finds the best match for each descriptor from a query set (blocking version).

fn match__1( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch>, masks: &Vector<GpuMat> ) -> Result<()>

Finds the best match for each descriptor from a query set (blocking version).

fn match__def_1( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch> ) -> Result<()>

@overload

fn match_async( &mut self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut impl ToOutputArray, mask: &impl ToInputArray, stream: &mut impl StreamTrait ) -> Result<()>

Finds the best match for each descriptor from a query set (asynchronous version).

fn match_async_def( &mut self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut impl ToOutputArray ) -> Result<()>

Finds the best match for each descriptor from a query set (asynchronous version).

fn match_async_1( &mut self, query_descriptors: &impl ToInputArray, matches: &mut impl ToOutputArray, masks: &Vector<GpuMat>, stream: &mut impl StreamTrait ) -> Result<()>

Finds the best match for each descriptor from a query set (asynchronous version).

fn match_async_def_1( &mut self, query_descriptors: &impl ToInputArray, matches: &mut impl ToOutputArray ) -> Result<()>

@overload

fn match_convert( &mut self, gpu_matches: &impl ToInputArray, matches: &mut Vector<DMatch> ) -> Result<()>

Converts matches array from internal representation to standard matches vector.

fn knn_match( &mut self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32, mask: &impl ToInputArray, compact_result: bool ) -> Result<()>

Finds the k best matches for each descriptor from a query set (blocking version).

fn knn_match_def( &mut self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32 ) -> Result<()>

Finds the k best matches for each descriptor from a query set (blocking version).

fn knn_match_1( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32, masks: &Vector<GpuMat>, compact_result: bool ) -> Result<()>

Finds the k best matches for each descriptor from a query set (blocking version).

fn knn_match_def_1( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32 ) -> Result<()>

@overload

fn knn_match_async( &mut self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut impl ToOutputArray, k: i32, mask: &impl ToInputArray, stream: &mut impl StreamTrait ) -> Result<()>

Finds the k best matches for each descriptor from a query set (asynchronous version).

fn knn_match_async_def( &mut self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut impl ToOutputArray, k: i32 ) -> Result<()>

Finds the k best matches for each descriptor from a query set (asynchronous version).

fn knn_match_async_1( &mut self, query_descriptors: &impl ToInputArray, matches: &mut impl ToOutputArray, k: i32, masks: &Vector<GpuMat>, stream: &mut impl StreamTrait ) -> Result<()>

Finds the k best matches for each descriptor from a query set (asynchronous version).

fn knn_match_async_def_1( &mut self, query_descriptors: &impl ToInputArray, matches: &mut impl ToOutputArray, k: i32 ) -> Result<()>

@overload

fn knn_match_convert( &mut self, gpu_matches: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, compact_result: bool ) -> Result<()>

Converts matches array from internal representation to standard matches vector.

fn knn_match_convert_def( &mut self, gpu_matches: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>> ) -> Result<()>

Converts matches array from internal representation to standard matches vector.

fn radius_match( &mut self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32, mask: &impl ToInputArray, compact_result: bool ) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance (blocking version).

fn radius_match_def( &mut self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32 ) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance (blocking version).

fn radius_match_1( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32, masks: &Vector<GpuMat>, compact_result: bool ) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance (blocking version).

fn radius_match_def_1( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32 ) -> Result<()>

@overload

fn radius_match_async( &mut self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut impl ToOutputArray, max_distance: f32, mask: &impl ToInputArray, stream: &mut impl StreamTrait ) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance (asynchronous version).

fn radius_match_async_def( &mut self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut impl ToOutputArray, max_distance: f32 ) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance (asynchronous version).

fn radius_match_async_1( &mut self, query_descriptors: &impl ToInputArray, matches: &mut impl ToOutputArray, max_distance: f32, masks: &Vector<GpuMat>, stream: &mut impl StreamTrait ) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance (asynchronous version).

fn radius_match_async_def_1( &mut self, query_descriptors: &impl ToInputArray, matches: &mut impl ToOutputArray, max_distance: f32 ) -> Result<()>

@overload

fn radius_match_convert( &mut self, gpu_matches: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, compact_result: bool ) -> Result<()>

Converts matches array from internal representation to standard matches vector.

fn radius_match_convert_def( &mut self, gpu_matches: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>> ) -> Result<()>

Converts matches array from internal representation to standard matches vector.

impl CUDA_DescriptorMatcherTraitConst for Ptr<CUDA_DescriptorMatcher>

fn as_raw_CUDA_DescriptorMatcher(&self) -> *const c_void

fn is_mask_supported(&self) -> Result<bool>

Returns true if the descriptor matcher supports masking permissible matches.

fn get_train_descriptors(&self) -> Result<Vector<GpuMat>>

Returns a constant link to the train descriptor collection.

fn empty(&self) -> Result<bool>

Returns true if there are no train descriptors in the collection.

impl CUDA_DisparityBilateralFilterTrait for Ptr<CUDA_DisparityBilateralFilter>

fn as_raw_mut_CUDA_DisparityBilateralFilter(&mut self) -> *mut c_void

fn apply( &mut self, disparity: &impl ToInputArray, image: &impl ToInputArray, dst: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Refines a disparity map using joint bilateral filtering.

fn apply_def( &mut self, disparity: &impl ToInputArray, image: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Refines a disparity map using joint bilateral filtering.

fn set_num_disparities(&mut self, num_disparities: i32) -> Result<()>

fn set_radius(&mut self, radius: i32) -> Result<()>

fn set_num_iters(&mut self, iters: i32) -> Result<()>

fn set_edge_threshold(&mut self, edge_threshold: f64) -> Result<()>

fn set_max_disc_threshold(&mut self, max_disc_threshold: f64) -> Result<()>

fn set_sigma_range(&mut self, sigma_range: f64) -> Result<()>

impl CUDA_DisparityBilateralFilterTraitConst for Ptr<CUDA_DisparityBilateralFilter>

fn as_raw_CUDA_DisparityBilateralFilter(&self) -> *const c_void

fn get_num_disparities(&self) -> Result<i32>

fn get_radius(&self) -> Result<i32>

fn get_num_iters(&self) -> Result<i32>

fn get_edge_threshold(&self) -> Result<f64>

truncation of data continuity

fn get_max_disc_threshold(&self) -> Result<f64>

truncation of disparity continuity

fn get_sigma_range(&self) -> Result<f64>

filter range sigma

impl CUDA_EncoderCallbackTrait for Ptr<CUDA_EncoderCallback>

fn as_raw_mut_CUDA_EncoderCallback(&mut self) -> *mut c_void

fn on_encoded(&mut self, v_packet: &Vector<Vector<u8>>) -> Result<()>

Callback function to signal that the encoded bitstream for one or more frames is ready.

fn on_encoding_finished(&mut self) -> Result<()>

Callback function to that the encoding has finished.

impl CUDA_EncoderCallbackTraitConst for Ptr<CUDA_EncoderCallback>

fn as_raw_CUDA_EncoderCallback(&self) -> *const c_void

impl CUDA_FarnebackOpticalFlowTrait for Ptr<CUDA_FarnebackOpticalFlow>

fn as_raw_mut_CUDA_FarnebackOpticalFlow(&mut self) -> *mut c_void

fn set_num_levels(&mut self, num_levels: i32) -> Result<()>

fn set_pyr_scale(&mut self, pyr_scale: f64) -> Result<()>

fn set_fast_pyramids(&mut self, fast_pyramids: bool) -> Result<()>

fn set_win_size(&mut self, win_size: i32) -> Result<()>

fn set_num_iters(&mut self, num_iters: i32) -> Result<()>

fn set_poly_n(&mut self, poly_n: i32) -> Result<()>

fn set_poly_sigma(&mut self, poly_sigma: f64) -> Result<()>

fn set_flags(&mut self, flags: i32) -> Result<()>

impl CUDA_FarnebackOpticalFlowTraitConst for Ptr<CUDA_FarnebackOpticalFlow>

fn as_raw_CUDA_FarnebackOpticalFlow(&self) -> *const c_void

fn get_num_levels(&self) -> Result<i32>

fn get_pyr_scale(&self) -> Result<f64>

fn get_fast_pyramids(&self) -> Result<bool>

fn get_win_size(&self) -> Result<i32>

fn get_num_iters(&self) -> Result<i32>

fn get_poly_n(&self) -> Result<i32>

fn get_poly_sigma(&self) -> Result<f64>

fn get_flags(&self) -> Result<i32>

impl CUDA_FastFeatureDetectorTrait for Ptr<CUDA_FastFeatureDetector>

fn as_raw_mut_CUDA_FastFeatureDetector(&mut self) -> *mut c_void

fn set_threshold(&mut self, threshold: i32) -> Result<()>

fn set_max_num_points(&mut self, max_npoints: i32) -> Result<()>

impl CUDA_FastFeatureDetectorTraitConst for Ptr<CUDA_FastFeatureDetector>

fn as_raw_CUDA_FastFeatureDetector(&self) -> *const c_void

fn get_max_num_points(&self) -> Result<i32>

impl CUDA_Feature2DAsyncTrait for Ptr<CUDA_FastFeatureDetector>

fn as_raw_mut_CUDA_Feature2DAsync(&mut self) -> *mut c_void

fn detect_async( &mut self, image: &impl ToInputArray, keypoints: &mut impl ToOutputArray, mask: &impl ToInputArray, stream: &mut impl StreamTrait ) -> Result<()>

Detects keypoints in an image.

fn detect_async_def( &mut self, image: &impl ToInputArray, keypoints: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints in an image.

fn compute_async( &mut self, image: &impl ToInputArray, keypoints: &mut impl ToOutputArray, descriptors: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image.

fn compute_async_def( &mut self, image: &impl ToInputArray, keypoints: &mut impl ToOutputArray, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image.

fn detect_and_compute_async( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut impl ToOutputArray, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool, stream: &mut impl StreamTrait ) -> Result<()>

Detects keypoints and computes the descriptors.

fn detect_and_compute_async_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut impl ToOutputArray, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors.

fn convert( &mut self, gpu_keypoints: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Converts keypoints array from internal representation to standard vector.

impl CUDA_Feature2DAsyncTrait for Ptr<CUDA_Feature2DAsync>

fn as_raw_mut_CUDA_Feature2DAsync(&mut self) -> *mut c_void

fn detect_async( &mut self, image: &impl ToInputArray, keypoints: &mut impl ToOutputArray, mask: &impl ToInputArray, stream: &mut impl StreamTrait ) -> Result<()>

Detects keypoints in an image.

fn detect_async_def( &mut self, image: &impl ToInputArray, keypoints: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints in an image.

fn compute_async( &mut self, image: &impl ToInputArray, keypoints: &mut impl ToOutputArray, descriptors: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image.

fn compute_async_def( &mut self, image: &impl ToInputArray, keypoints: &mut impl ToOutputArray, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image.

fn detect_and_compute_async( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut impl ToOutputArray, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool, stream: &mut impl StreamTrait ) -> Result<()>

Detects keypoints and computes the descriptors.

fn detect_and_compute_async_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut impl ToOutputArray, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors.

fn convert( &mut self, gpu_keypoints: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Converts keypoints array from internal representation to standard vector.

impl CUDA_Feature2DAsyncTrait for Ptr<CUDA_ORB>

fn as_raw_mut_CUDA_Feature2DAsync(&mut self) -> *mut c_void

fn detect_async( &mut self, image: &impl ToInputArray, keypoints: &mut impl ToOutputArray, mask: &impl ToInputArray, stream: &mut impl StreamTrait ) -> Result<()>

Detects keypoints in an image.

fn detect_async_def( &mut self, image: &impl ToInputArray, keypoints: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints in an image.

fn compute_async( &mut self, image: &impl ToInputArray, keypoints: &mut impl ToOutputArray, descriptors: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image.

fn compute_async_def( &mut self, image: &impl ToInputArray, keypoints: &mut impl ToOutputArray, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image.

fn detect_and_compute_async( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut impl ToOutputArray, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool, stream: &mut impl StreamTrait ) -> Result<()>

Detects keypoints and computes the descriptors.

fn detect_and_compute_async_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut impl ToOutputArray, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors.

fn convert( &mut self, gpu_keypoints: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Converts keypoints array from internal representation to standard vector.

impl CUDA_Feature2DAsyncTraitConst for Ptr<CUDA_FastFeatureDetector>

fn as_raw_CUDA_Feature2DAsync(&self) -> *const c_void

impl CUDA_Feature2DAsyncTraitConst for Ptr<CUDA_Feature2DAsync>

fn as_raw_CUDA_Feature2DAsync(&self) -> *const c_void

impl CUDA_Feature2DAsyncTraitConst for Ptr<CUDA_ORB>

fn as_raw_CUDA_Feature2DAsync(&self) -> *const c_void

impl CUDA_HOGTrait for Ptr<CUDA_HOG>

fn as_raw_mut_CUDA_HOG(&mut self) -> *mut c_void

fn set_win_sigma(&mut self, win_sigma: f64) -> Result<()>

Gaussian smoothing window parameter.

fn set_l2_hys_threshold(&mut self, threshold_l2hys: f64) -> Result<()>

L2-Hys normalization method shrinkage.

fn set_gamma_correction(&mut self, gamma_correction: bool) -> Result<()>

Flag to specify whether the gamma correction preprocessing is required or not.

fn set_num_levels(&mut self, nlevels: i32) -> Result<()>

Maximum number of detection window increases.

fn set_hit_threshold(&mut self, hit_threshold: f64) -> Result<()>

Threshold for the distance between features and SVM classifying plane. Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient). But if the free coefficient is omitted (which is allowed), you can specify it manually here.

fn set_win_stride(&mut self, win_stride: Size) -> Result<()>

Window stride. It must be a multiple of block stride.

fn set_scale_factor(&mut self, scale0: f64) -> Result<()>

Coefficient of the detection window increase.

fn set_group_threshold(&mut self, group_threshold: i32) -> Result<()>

Coefficient to regulate the similarity threshold. When detected, some objects can be covered by many rectangles. 0 means not to perform grouping. See groupRectangles.

fn set_descriptor_format( &mut self, descr_format: HOGDescriptor_DescriptorStorageFormat ) -> Result<()>

Descriptor storage format:

fn set_svm_detector(&mut self, detector: &impl ToInputArray) -> Result<()>

Sets coefficients for the linear SVM classifier.

fn detect( &mut self, img: &impl ToInputArray, found_locations: &mut Vector<Point>, confidences: &mut Vector<f64> ) -> Result<()>

Performs object detection without a multi-scale window.

fn detect_def( &mut self, img: &impl ToInputArray, found_locations: &mut Vector<Point> ) -> Result<()>

Performs object detection without a multi-scale window.

fn detect_1( &mut self, img: &impl ToInputArray, found_locations: &mut Vector<Point>, confidences: &mut Vector<f64> ) -> Result<()>

fn detect_without_conf( &mut self, img: &impl ToInputArray, found_locations: &mut Vector<Point> ) -> Result<()>

Performs object detection without a multi-scale window.

fn detect_multi_scale( &mut self, img: &impl ToInputArray, found_locations: &mut Vector<Rect>, confidences: &mut Vector<f64> ) -> Result<()>

Performs object detection with a multi-scale window.

fn detect_multi_scale_def( &mut self, img: &impl ToInputArray, found_locations: &mut Vector<Rect> ) -> Result<()>

Performs object detection with a multi-scale window.

fn detect_multi_scale_1( &mut self, img: &impl ToInputArray, found_locations: &mut Vector<Rect>, confidences: &mut Vector<f64> ) -> Result<()>

fn detect_multi_scale_without_conf( &mut self, img: &impl ToInputArray, found_locations: &mut Vector<Rect> ) -> Result<()>

Performs object detection with a multi-scale window.

fn compute( &mut self, img: &impl ToInputArray, descriptors: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Returns block descriptors computed for the whole image.

fn compute_def( &mut self, img: &impl ToInputArray, descriptors: &mut impl ToOutputArray ) -> Result<()>

Returns block descriptors computed for the whole image.

impl CUDA_HOGTraitConst for Ptr<CUDA_HOG>

fn as_raw_CUDA_HOG(&self) -> *const c_void

fn get_win_sigma(&self) -> Result<f64>

fn get_l2_hys_threshold(&self) -> Result<f64>

fn get_gamma_correction(&self) -> Result<bool>

fn get_num_levels(&self) -> Result<i32>

fn get_hit_threshold(&self) -> Result<f64>

fn get_win_stride(&self) -> Result<Size>

fn get_scale_factor(&self) -> Result<f64>

fn get_group_threshold(&self) -> Result<i32>

fn get_descriptor_format(&self) -> Result<HOGDescriptor_DescriptorStorageFormat>

fn get_descriptor_size(&self) -> Result<size_t>

Returns the number of coefficients required for the classification.

fn get_block_histogram_size(&self) -> Result<size_t>

Returns the block histogram size.

fn get_default_people_detector(&self) -> Result<Mat>

Returns coefficients of the classifier trained for people detection.

impl CUDA_HoughCirclesDetectorTrait for Ptr<CUDA_HoughCirclesDetector>

fn as_raw_mut_CUDA_HoughCirclesDetector(&mut self) -> *mut c_void

fn detect( &mut self, src: &impl ToInputArray, circles: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Finds circles in a grayscale image using the Hough transform.

fn detect_def( &mut self, src: &impl ToInputArray, circles: &mut impl ToOutputArray ) -> Result<()>

Finds circles in a grayscale image using the Hough transform.

fn set_dp(&mut self, dp: f32) -> Result<()>

fn set_min_dist(&mut self, min_dist: f32) -> Result<()>

fn set_canny_threshold(&mut self, canny_threshold: i32) -> Result<()>

fn set_votes_threshold(&mut self, votes_threshold: i32) -> Result<()>

fn set_min_radius(&mut self, min_radius: i32) -> Result<()>

fn set_max_radius(&mut self, max_radius: i32) -> Result<()>

fn set_max_circles(&mut self, max_circles: i32) -> Result<()>

impl CUDA_HoughCirclesDetectorTraitConst for Ptr<CUDA_HoughCirclesDetector>

fn as_raw_CUDA_HoughCirclesDetector(&self) -> *const c_void

fn get_dp(&self) -> Result<f32>

fn get_min_dist(&self) -> Result<f32>

fn get_canny_threshold(&self) -> Result<i32>

fn get_votes_threshold(&self) -> Result<i32>

fn get_min_radius(&self) -> Result<i32>

fn get_max_radius(&self) -> Result<i32>

fn get_max_circles(&self) -> Result<i32>

impl CUDA_HoughLinesDetectorTrait for Ptr<CUDA_HoughLinesDetector>

fn as_raw_mut_CUDA_HoughLinesDetector(&mut self) -> *mut c_void

fn detect( &mut self, src: &impl ToInputArray, lines: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Finds lines in a binary image using the classical Hough transform.

fn detect_def( &mut self, src: &impl ToInputArray, lines: &mut impl ToOutputArray ) -> Result<()>

Finds lines in a binary image using the classical Hough transform.

fn download_results( &mut self, d_lines: &impl ToInputArray, h_lines: &mut impl ToOutputArray, h_votes: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Downloads results from cuda::HoughLinesDetector::detect to host memory.

fn download_results_def( &mut self, d_lines: &impl ToInputArray, h_lines: &mut impl ToOutputArray ) -> Result<()>

Downloads results from cuda::HoughLinesDetector::detect to host memory.

fn set_rho(&mut self, rho: f32) -> Result<()>

fn set_theta(&mut self, theta: f32) -> Result<()>

fn set_threshold(&mut self, threshold: i32) -> Result<()>

fn set_do_sort(&mut self, do_sort: bool) -> Result<()>

fn set_max_lines(&mut self, max_lines: i32) -> Result<()>

impl CUDA_HoughLinesDetectorTraitConst for Ptr<CUDA_HoughLinesDetector>

fn as_raw_CUDA_HoughLinesDetector(&self) -> *const c_void

fn get_rho(&self) -> Result<f32>

fn get_theta(&self) -> Result<f32>

fn get_threshold(&self) -> Result<i32>

fn get_do_sort(&self) -> Result<bool>

fn get_max_lines(&self) -> Result<i32>

impl CUDA_HoughSegmentDetectorTrait for Ptr<CUDA_HoughSegmentDetector>

fn as_raw_mut_CUDA_HoughSegmentDetector(&mut self) -> *mut c_void

fn detect( &mut self, src: &impl ToInputArray, lines: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Finds line segments in a binary image using the probabilistic Hough transform.

fn detect_def( &mut self, src: &impl ToInputArray, lines: &mut impl ToOutputArray ) -> Result<()>

Finds line segments in a binary image using the probabilistic Hough transform.

fn set_rho(&mut self, rho: f32) -> Result<()>

fn set_theta(&mut self, theta: f32) -> Result<()>

fn set_min_line_length(&mut self, min_line_length: i32) -> Result<()>

fn set_max_line_gap(&mut self, max_line_gap: i32) -> Result<()>

fn set_max_lines(&mut self, max_lines: i32) -> Result<()>

fn set_threshold(&mut self, threshold: i32) -> Result<()>

impl CUDA_HoughSegmentDetectorTraitConst for Ptr<CUDA_HoughSegmentDetector>

fn as_raw_CUDA_HoughSegmentDetector(&self) -> *const c_void

fn get_rho(&self) -> Result<f32>

fn get_theta(&self) -> Result<f32>

fn get_min_line_length(&self) -> Result<i32>

fn get_max_line_gap(&self) -> Result<i32>

fn get_max_lines(&self) -> Result<i32>

fn get_threshold(&self) -> Result<i32>

impl CUDA_NvidiaHWOpticalFlowTrait for Ptr<CUDA_NvidiaHWOpticalFlow>

fn as_raw_mut_CUDA_NvidiaHWOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, input_image: &impl ToInputArray, reference_image: &impl ToInputArray, flow: &mut impl ToInputOutputArray, stream: &mut impl StreamTrait, hint: &impl ToInputArray, cost: &mut impl ToOutputArray ) -> Result<()>

Calculates Optical Flow using NVIDIA Optical Flow SDK.

fn calc_def( &mut self, input_image: &impl ToInputArray, reference_image: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates Optical Flow using NVIDIA Optical Flow SDK.

fn collect_garbage(&mut self) -> Result<()>

Releases all buffers, contexts and device pointers.

impl CUDA_NvidiaHWOpticalFlowTrait for Ptr<CUDA_NvidiaOpticalFlow_1_0>

fn as_raw_mut_CUDA_NvidiaHWOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, input_image: &impl ToInputArray, reference_image: &impl ToInputArray, flow: &mut impl ToInputOutputArray, stream: &mut impl StreamTrait, hint: &impl ToInputArray, cost: &mut impl ToOutputArray ) -> Result<()>

Calculates Optical Flow using NVIDIA Optical Flow SDK.

fn calc_def( &mut self, input_image: &impl ToInputArray, reference_image: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates Optical Flow using NVIDIA Optical Flow SDK.

fn collect_garbage(&mut self) -> Result<()>

Releases all buffers, contexts and device pointers.

impl CUDA_NvidiaHWOpticalFlowTrait for Ptr<CUDA_NvidiaOpticalFlow_2_0>

fn as_raw_mut_CUDA_NvidiaHWOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, input_image: &impl ToInputArray, reference_image: &impl ToInputArray, flow: &mut impl ToInputOutputArray, stream: &mut impl StreamTrait, hint: &impl ToInputArray, cost: &mut impl ToOutputArray ) -> Result<()>

Calculates Optical Flow using NVIDIA Optical Flow SDK.

fn calc_def( &mut self, input_image: &impl ToInputArray, reference_image: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates Optical Flow using NVIDIA Optical Flow SDK.

fn collect_garbage(&mut self) -> Result<()>

Releases all buffers, contexts and device pointers.

impl CUDA_NvidiaHWOpticalFlowTraitConst for Ptr<CUDA_NvidiaHWOpticalFlow>

fn as_raw_CUDA_NvidiaHWOpticalFlow(&self) -> *const c_void

fn get_grid_size(&self) -> Result<i32>

Returns grid size of output buffer as per the hardware’s capability.

impl CUDA_NvidiaHWOpticalFlowTraitConst for Ptr<CUDA_NvidiaOpticalFlow_1_0>

fn as_raw_CUDA_NvidiaHWOpticalFlow(&self) -> *const c_void

fn get_grid_size(&self) -> Result<i32>

Returns grid size of output buffer as per the hardware’s capability.

impl CUDA_NvidiaHWOpticalFlowTraitConst for Ptr<CUDA_NvidiaOpticalFlow_2_0>

fn as_raw_CUDA_NvidiaHWOpticalFlow(&self) -> *const c_void

fn get_grid_size(&self) -> Result<i32>

Returns grid size of output buffer as per the hardware’s capability.

impl CUDA_NvidiaOpticalFlow_1_0Trait for Ptr<CUDA_NvidiaOpticalFlow_1_0>

fn as_raw_mut_CUDA_NvidiaOpticalFlow_1_0(&mut self) -> *mut c_void

fn up_sampler( &mut self, flow: &impl ToInputArray, image_size: Size, grid_size: i32, upsampled_flow: &mut impl ToInputOutputArray ) -> Result<()>

The NVIDIA optical flow hardware generates flow vectors at granularity gridSize, which can be queried via function getGridSize(). Upsampler() helper function converts the hardware-generated flow vectors to dense representation (1 flow vector for each pixel) using nearest neighbour upsampling method.

impl CUDA_NvidiaOpticalFlow_1_0TraitConst for Ptr<CUDA_NvidiaOpticalFlow_1_0>

fn as_raw_CUDA_NvidiaOpticalFlow_1_0(&self) -> *const c_void

impl CUDA_NvidiaOpticalFlow_2_0Trait for Ptr<CUDA_NvidiaOpticalFlow_2_0>

fn as_raw_mut_CUDA_NvidiaOpticalFlow_2_0(&mut self) -> *mut c_void

fn convert_to_float( &mut self, flow: &impl ToInputArray, float_flow: &mut impl ToInputOutputArray ) -> Result<()>

convertToFloat() helper function converts the hardware-generated flow vectors to floating point representation (1 flow vector for gridSize). gridSize can be queried via function getGridSize().

impl CUDA_NvidiaOpticalFlow_2_0TraitConst for Ptr<CUDA_NvidiaOpticalFlow_2_0>

fn as_raw_CUDA_NvidiaOpticalFlow_2_0(&self) -> *const c_void

impl CUDA_ORBTrait for Ptr<CUDA_ORB>

fn as_raw_mut_CUDA_ORB(&mut self) -> *mut c_void

fn set_max_features(&mut self, max_features: i32) -> Result<()>

fn set_scale_factor(&mut self, scale_factor: f64) -> Result<()>

fn set_n_levels(&mut self, nlevels: i32) -> Result<()>

fn set_edge_threshold(&mut self, edge_threshold: i32) -> Result<()>

fn set_first_level(&mut self, first_level: i32) -> Result<()>

fn set_wta_k(&mut self, wta_k: i32) -> Result<()>

fn set_score_type(&mut self, score_type: i32) -> Result<()>

fn set_patch_size(&mut self, patch_size: i32) -> Result<()>

fn set_fast_threshold(&mut self, fast_threshold: i32) -> Result<()>

fn set_blur_for_descriptor(&mut self, blur_for_descriptor: bool) -> Result<()>

if true, image will be blurred before descriptors calculation

impl CUDA_ORBTraitConst for Ptr<CUDA_ORB>

fn as_raw_CUDA_ORB(&self) -> *const c_void

fn get_max_features(&self) -> Result<i32>

fn get_scale_factor(&self) -> Result<f64>

fn get_n_levels(&self) -> Result<i32>

fn get_edge_threshold(&self) -> Result<i32>

fn get_first_level(&self) -> Result<i32>

fn get_wta_k(&self) -> Result<i32>

fn get_score_type(&self) -> Result<i32>

fn get_patch_size(&self) -> Result<i32>

fn get_fast_threshold(&self) -> Result<i32>

fn get_blur_for_descriptor(&self) -> Result<bool>

impl CUDA_OpticalFlowDual_TVL1Trait for Ptr<CUDA_OpticalFlowDual_TVL1>

fn as_raw_mut_CUDA_OpticalFlowDual_TVL1(&mut self) -> *mut c_void

fn set_tau(&mut self, tau: f64) -> Result<()>

fn set_lambda(&mut self, lambda: f64) -> Result<()>

fn set_gamma(&mut self, gamma: f64) -> Result<()>

fn set_theta(&mut self, theta: f64) -> Result<()>

fn set_num_scales(&mut self, nscales: i32) -> Result<()>

fn set_num_warps(&mut self, warps: i32) -> Result<()>

fn set_epsilon(&mut self, epsilon: f64) -> Result<()>

fn set_num_iterations(&mut self, iterations: i32) -> Result<()>

fn set_scale_step(&mut self, scale_step: f64) -> Result<()>

fn set_use_initial_flow(&mut self, use_initial_flow: bool) -> Result<()>

impl CUDA_OpticalFlowDual_TVL1TraitConst for Ptr<CUDA_OpticalFlowDual_TVL1>

fn as_raw_CUDA_OpticalFlowDual_TVL1(&self) -> *const c_void

fn get_tau(&self) -> Result<f64>

Time step of the numerical scheme.

fn get_lambda(&self) -> Result<f64>

Weight parameter for the data term, attachment parameter. This is the most relevant parameter, which determines the smoothness of the output. The smaller this parameter is, the smoother the solutions we obtain. It depends on the range of motions of the images, so its value should be adapted to each image sequence.

fn get_gamma(&self) -> Result<f64>

Weight parameter for (u - v)^2, tightness parameter. It serves as a link between the attachment and the regularization terms. In theory, it should have a small value in order to maintain both parts in correspondence. The method is stable for a large range of values of this parameter.

fn get_theta(&self) -> Result<f64>

parameter used for motion estimation. It adds a variable allowing for illumination variations Set this parameter to 1. if you have varying illumination. See: Chambolle et al, A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging Journal of Mathematical imaging and vision, may 2011 Vol 40 issue 1, pp 120-145

fn get_num_scales(&self) -> Result<i32>

Number of scales used to create the pyramid of images.

fn get_num_warps(&self) -> Result<i32>

Number of warpings per scale. Represents the number of times that I1(x+u0) and grad( I1(x+u0) ) are computed per scale. This is a parameter that assures the stability of the method. It also affects the running time, so it is a compromise between speed and accuracy.

fn get_epsilon(&self) -> Result<f64>

Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time. A small value will yield more accurate solutions at the expense of a slower convergence.

fn get_num_iterations(&self) -> Result<i32>

Stopping criterion iterations number used in the numerical scheme.

fn get_scale_step(&self) -> Result<f64>

fn get_use_initial_flow(&self) -> Result<bool>

impl CUDA_RawVideoSourceTrait for Ptr<CUDA_RawVideoSource>

fn as_raw_mut_CUDA_RawVideoSource(&mut self) -> *mut c_void

unsafe fn get_next_packet( &mut self, data: *mut *mut u8, size: &mut size_t ) -> Result<bool>

Returns next packet with RAW video frame.

fn update_format(&mut self, video_format: CUDA_FormatInfo) -> Result<()>

Updates the coded width and height inside format.

impl CUDA_RawVideoSourceTraitConst for Ptr<CUDA_RawVideoSource>

fn as_raw_CUDA_RawVideoSource(&self) -> *const c_void

fn last_packet_contains_key_frame(&self) -> Result<bool>

Returns true if the last packet contained a key frame.

fn format(&self) -> Result<CUDA_FormatInfo>

Returns information about video file format.

fn get_extra_data(&self, extra_data: &mut impl MatTrait) -> Result<()>

Returns any extra data associated with the video source.

fn get(&self, property_id: i32, property_val: &mut f64) -> Result<bool>

Retrieves the specified property used by the VideoSource.

fn get_first_frame_idx(&self) -> Result<i32>

Retrieve the index of the first frame that will returned after construction.

impl CUDA_SparseOpticalFlowTrait for Ptr<CUDA_SparseOpticalFlow>

fn as_raw_mut_CUDA_SparseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, prev_img: &impl ToInputArray, next_img: &impl ToInputArray, prev_pts: &impl ToInputArray, next_pts: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray, err: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Calculates a sparse optical flow.

fn calc_def( &mut self, prev_img: &impl ToInputArray, next_img: &impl ToInputArray, prev_pts: &impl ToInputArray, next_pts: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray ) -> Result<()>

Calculates a sparse optical flow.

impl CUDA_SparseOpticalFlowTrait for Ptr<CUDA_SparsePyrLKOpticalFlow>

fn as_raw_mut_CUDA_SparseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, prev_img: &impl ToInputArray, next_img: &impl ToInputArray, prev_pts: &impl ToInputArray, next_pts: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray, err: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Calculates a sparse optical flow.

fn calc_def( &mut self, prev_img: &impl ToInputArray, next_img: &impl ToInputArray, prev_pts: &impl ToInputArray, next_pts: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray ) -> Result<()>

Calculates a sparse optical flow.

impl CUDA_SparseOpticalFlowTraitConst for Ptr<CUDA_SparseOpticalFlow>

fn as_raw_CUDA_SparseOpticalFlow(&self) -> *const c_void

impl CUDA_SparseOpticalFlowTraitConst for Ptr<CUDA_SparsePyrLKOpticalFlow>

fn as_raw_CUDA_SparseOpticalFlow(&self) -> *const c_void

impl CUDA_SparsePyrLKOpticalFlowTrait for Ptr<CUDA_SparsePyrLKOpticalFlow>

fn as_raw_mut_CUDA_SparsePyrLKOpticalFlow(&mut self) -> *mut c_void

fn set_win_size(&mut self, win_size: Size) -> Result<()>

fn set_max_level(&mut self, max_level: i32) -> Result<()>

fn set_num_iters(&mut self, iters: i32) -> Result<()>

fn set_use_initial_flow(&mut self, use_initial_flow: bool) -> Result<()>

impl CUDA_SparsePyrLKOpticalFlowTraitConst for Ptr<CUDA_SparsePyrLKOpticalFlow>

fn as_raw_CUDA_SparsePyrLKOpticalFlow(&self) -> *const c_void

fn get_win_size(&self) -> Result<Size>

fn get_max_level(&self) -> Result<i32>

fn get_num_iters(&self) -> Result<i32>

fn get_use_initial_flow(&self) -> Result<bool>

impl CUDA_StereoBMTrait for Ptr<CUDA_StereoBM>

fn as_raw_mut_CUDA_StereoBM(&mut self) -> *mut c_void

fn compute( &mut self, left: &impl ToInputArray, right: &impl ToInputArray, disparity: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

impl CUDA_StereoBMTraitConst for Ptr<CUDA_StereoBM>

fn as_raw_CUDA_StereoBM(&self) -> *const c_void

impl CUDA_StereoBeliefPropagationTrait for Ptr<CUDA_StereoBeliefPropagation>

fn as_raw_mut_CUDA_StereoBeliefPropagation(&mut self) -> *mut c_void

fn compute( &mut self, left: &impl ToInputArray, right: &impl ToInputArray, disparity: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Enables the stereo correspondence operator that finds the disparity for the specified data cost.

fn compute_1( &mut self, data: &impl ToInputArray, disparity: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Enables the stereo correspondence operator that finds the disparity for the specified data cost.

fn compute_def( &mut self, data: &impl ToInputArray, disparity: &mut impl ToOutputArray ) -> Result<()>

Enables the stereo correspondence operator that finds the disparity for the specified data cost.

fn set_num_iters(&mut self, iters: i32) -> Result<()>

fn set_num_levels(&mut self, levels: i32) -> Result<()>

fn set_max_data_term(&mut self, max_data_term: f64) -> Result<()>

fn set_data_weight(&mut self, data_weight: f64) -> Result<()>

fn set_max_disc_term(&mut self, max_disc_term: f64) -> Result<()>

fn set_disc_single_jump(&mut self, disc_single_jump: f64) -> Result<()>

fn set_msg_type(&mut self, msg_type: i32) -> Result<()>

impl CUDA_StereoBeliefPropagationTrait for Ptr<CUDA_StereoConstantSpaceBP>

fn as_raw_mut_CUDA_StereoBeliefPropagation(&mut self) -> *mut c_void

fn compute( &mut self, left: &impl ToInputArray, right: &impl ToInputArray, disparity: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Enables the stereo correspondence operator that finds the disparity for the specified data cost.

fn compute_1( &mut self, data: &impl ToInputArray, disparity: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Enables the stereo correspondence operator that finds the disparity for the specified data cost.

fn compute_def( &mut self, data: &impl ToInputArray, disparity: &mut impl ToOutputArray ) -> Result<()>

Enables the stereo correspondence operator that finds the disparity for the specified data cost.

fn set_num_iters(&mut self, iters: i32) -> Result<()>

fn set_num_levels(&mut self, levels: i32) -> Result<()>

fn set_max_data_term(&mut self, max_data_term: f64) -> Result<()>

fn set_data_weight(&mut self, data_weight: f64) -> Result<()>

fn set_max_disc_term(&mut self, max_disc_term: f64) -> Result<()>

fn set_disc_single_jump(&mut self, disc_single_jump: f64) -> Result<()>

fn set_msg_type(&mut self, msg_type: i32) -> Result<()>

impl CUDA_StereoBeliefPropagationTraitConst for Ptr<CUDA_StereoBeliefPropagation>

fn as_raw_CUDA_StereoBeliefPropagation(&self) -> *const c_void

fn get_num_iters(&self) -> Result<i32>

number of BP iterations on each level

fn get_num_levels(&self) -> Result<i32>

number of levels

fn get_max_data_term(&self) -> Result<f64>

truncation of data cost

fn get_data_weight(&self) -> Result<f64>

data weight

fn get_max_disc_term(&self) -> Result<f64>

truncation of discontinuity cost

fn get_disc_single_jump(&self) -> Result<f64>

discontinuity single jump

fn get_msg_type(&self) -> Result<i32>

type for messages (CV_16SC1 or CV_32FC1)

impl CUDA_StereoBeliefPropagationTraitConst for Ptr<CUDA_StereoConstantSpaceBP>

fn as_raw_CUDA_StereoBeliefPropagation(&self) -> *const c_void

fn get_num_iters(&self) -> Result<i32>

number of BP iterations on each level

fn get_num_levels(&self) -> Result<i32>

number of levels

fn get_max_data_term(&self) -> Result<f64>

truncation of data cost

fn get_data_weight(&self) -> Result<f64>

data weight

fn get_max_disc_term(&self) -> Result<f64>

truncation of discontinuity cost

fn get_disc_single_jump(&self) -> Result<f64>

discontinuity single jump

fn get_msg_type(&self) -> Result<i32>

type for messages (CV_16SC1 or CV_32FC1)

impl CUDA_StereoConstantSpaceBPTrait for Ptr<CUDA_StereoConstantSpaceBP>

fn as_raw_mut_CUDA_StereoConstantSpaceBP(&mut self) -> *mut c_void

fn set_nr_plane(&mut self, nr_plane: i32) -> Result<()>

fn set_use_local_init_data_cost( &mut self, use_local_init_data_cost: bool ) -> Result<()>

impl CUDA_StereoConstantSpaceBPTraitConst for Ptr<CUDA_StereoConstantSpaceBP>

fn as_raw_CUDA_StereoConstantSpaceBP(&self) -> *const c_void

fn get_nr_plane(&self) -> Result<i32>

number of active disparity on the first level

fn get_use_local_init_data_cost(&self) -> Result<bool>

impl CUDA_StereoSGMTrait for Ptr<CUDA_StereoSGM>

fn as_raw_mut_CUDA_StereoSGM(&mut self) -> *mut c_void

fn compute( &mut self, left: &impl ToInputArray, right: &impl ToInputArray, disparity: &mut impl ToOutputArray ) -> Result<()>

Computes disparity map for the specified stereo pair

fn compute_with_stream( &mut self, left: &impl ToInputArray, right: &impl ToInputArray, disparity: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Computes disparity map with specified CUDA Stream

impl CUDA_StereoSGMTraitConst for Ptr<CUDA_StereoSGM>

fn as_raw_CUDA_StereoSGM(&self) -> *const c_void

impl CUDA_TemplateMatchingTrait for Ptr<CUDA_TemplateMatching>

fn as_raw_mut_CUDA_TemplateMatching(&mut self) -> *mut c_void

fn match_( &mut self, image: &impl ToInputArray, templ: &impl ToInputArray, result: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Computes a proximity map for a raster template and an image where the template is searched for.

fn match__def( &mut self, image: &impl ToInputArray, templ: &impl ToInputArray, result: &mut impl ToOutputArray ) -> Result<()>

Computes a proximity map for a raster template and an image where the template is searched for.

impl CUDA_TemplateMatchingTraitConst for Ptr<CUDA_TemplateMatching>

fn as_raw_CUDA_TemplateMatching(&self) -> *const c_void

impl CUDA_VideoReaderTrait for Ptr<CUDA_VideoReader>

fn as_raw_mut_CUDA_VideoReader(&mut self) -> *mut c_void

fn next_frame( &mut self, frame: &mut impl GpuMatTrait, stream: &mut impl StreamTrait ) -> Result<bool>

Grabs, decodes and returns the next video frame.

fn next_frame_def(&mut self, frame: &mut impl GpuMatTrait) -> Result<bool>

Grabs, decodes and returns the next video frame.

fn next_frame_with_hist( &mut self, frame: &mut impl GpuMatTrait, histogram: &mut impl GpuMatTrait, stream: &mut impl StreamTrait ) -> Result<bool>

Grabs, decodes and returns the next video frame and frame luma histogram.

fn next_frame_with_hist_def( &mut self, frame: &mut impl GpuMatTrait, histogram: &mut impl GpuMatTrait ) -> Result<bool>

Grabs, decodes and returns the next video frame and frame luma histogram.

fn grab(&mut self, stream: &mut impl StreamTrait) -> Result<bool>

Grabs the next frame from the video source.

fn grab_def(&mut self) -> Result<bool>

Grabs the next frame from the video source.

fn set( &mut self, property_id: CUDA_VideoReaderProps, property_val: f64 ) -> Result<bool>

Sets a property in the VideoReader.

fn set_video_reader_props( &mut self, property_id: CUDA_VideoReaderProps, property_val: f64 ) -> Result<bool>

fn set_1(&mut self, color_format: CUDA_ColorFormat) -> Result<bool>

Set the desired ColorFormat for the frame returned by nextFrame()/retrieve().

impl CUDA_VideoReaderTraitConst for Ptr<CUDA_VideoReader>

fn as_raw_CUDA_VideoReader(&self) -> *const c_void

fn format(&self) -> Result<CUDA_FormatInfo>

Returns information about video file format.

fn retrieve(&self, frame: &mut impl ToOutputArray, idx: size_t) -> Result<bool>

Returns previously grabbed video data.

fn retrieve_def(&self, frame: &mut impl ToOutputArray) -> Result<bool>

Returns previously grabbed video data.

fn retrieve_1(&self, frame: &mut impl MatTrait, idx: size_t) -> Result<bool>

Returns previously grabbed encoded video data.

fn retrieve_2(&self, frame: &mut impl GpuMatTrait) -> Result<bool>

Returns the next video frame.

fn get( &self, property_id: CUDA_VideoReaderProps, property_val: &mut f64 ) -> Result<bool>

Returns the specified VideoReader property

fn get_video_reader_props( &self, property_id: CUDA_VideoReaderProps, property_val_out: &mut f64, property_val_in: f64 ) -> Result<bool>

C++ default parameters

fn get_video_reader_props_def( &self, property_id: CUDA_VideoReaderProps, property_val_out: &mut f64 ) -> Result<bool>

Note

fn get_1(&self, property_id: i32, property_val: &mut f64) -> Result<bool>

Retrieves the specified property used by the VideoSource.

impl CUDA_VideoWriterTrait for Ptr<CUDA_VideoWriter>

fn as_raw_mut_CUDA_VideoWriter(&mut self) -> *mut c_void

fn write(&mut self, frame: &impl ToInputArray) -> Result<()>

Writes the next video frame.

fn release(&mut self) -> Result<()>

Waits until the encoding process has finished before calling EncoderCallback::onEncodingFinished().

impl CUDA_VideoWriterTraitConst for Ptr<CUDA_VideoWriter>

fn as_raw_CUDA_VideoWriter(&self) -> *const c_void

fn get_encoder_params(&self) -> Result<CUDA_EncoderParams>

Retrieve the encoding parameters.

impl CalibrateCRFTrait for Ptr<CalibrateCRF>

fn as_raw_mut_CalibrateCRF(&mut self) -> *mut c_void

fn process( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, times: &impl ToInputArray ) -> Result<()>

Recovers inverse camera response.

impl CalibrateCRFTrait for Ptr<CalibrateDebevec>

fn as_raw_mut_CalibrateCRF(&mut self) -> *mut c_void

fn process( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, times: &impl ToInputArray ) -> Result<()>

Recovers inverse camera response.

impl CalibrateCRFTrait for Ptr<CalibrateRobertson>

fn as_raw_mut_CalibrateCRF(&mut self) -> *mut c_void

fn process( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, times: &impl ToInputArray ) -> Result<()>

Recovers inverse camera response.

impl CalibrateCRFTraitConst for Ptr<CalibrateCRF>

fn as_raw_CalibrateCRF(&self) -> *const c_void

impl CalibrateCRFTraitConst for Ptr<CalibrateDebevec>

fn as_raw_CalibrateCRF(&self) -> *const c_void

impl CalibrateCRFTraitConst for Ptr<CalibrateRobertson>

fn as_raw_CalibrateCRF(&self) -> *const c_void

impl CalibrateDebevecTrait for Ptr<CalibrateDebevec>

fn as_raw_mut_CalibrateDebevec(&mut self) -> *mut c_void

fn set_lambda(&mut self, lambda: f32) -> Result<()>

fn set_samples(&mut self, samples: i32) -> Result<()>

fn set_random(&mut self, random: bool) -> Result<()>

impl CalibrateDebevecTraitConst for Ptr<CalibrateDebevec>

fn as_raw_CalibrateDebevec(&self) -> *const c_void

fn get_lambda(&self) -> Result<f32>

fn get_samples(&self) -> Result<i32>

fn get_random(&self) -> Result<bool>

impl CalibrateRobertsonTrait for Ptr<CalibrateRobertson>

fn as_raw_mut_CalibrateRobertson(&mut self) -> *mut c_void

fn set_max_iter(&mut self, max_iter: i32) -> Result<()>

fn set_threshold(&mut self, threshold: f32) -> Result<()>

impl CalibrateRobertsonTraitConst for Ptr<CalibrateRobertson>

fn as_raw_CalibrateRobertson(&self) -> *const c_void

fn get_max_iter(&self) -> Result<i32>

fn get_threshold(&self) -> Result<f32>

fn get_radiance(&self) -> Result<Mat>

impl CeilLayerTrait for Ptr<CeilLayer>

fn as_raw_mut_CeilLayer(&mut self) -> *mut c_void

impl CeilLayerTraitConst for Ptr<CeilLayer>

fn as_raw_CeilLayer(&self) -> *const c_void

impl CeluLayerTrait for Ptr<CeluLayer>

fn as_raw_mut_CeluLayer(&mut self) -> *mut c_void

fn set_alpha(&mut self, val: f32)

impl CeluLayerTraitConst for Ptr<CeluLayer>

fn as_raw_CeluLayer(&self) -> *const c_void

fn alpha(&self) -> f32

impl ChannelsPReLULayerTrait for Ptr<ChannelsPReLULayer>

fn as_raw_mut_ChannelsPReLULayer(&mut self) -> *mut c_void

impl ChannelsPReLULayerTraitConst for Ptr<ChannelsPReLULayer>

fn as_raw_ChannelsPReLULayer(&self) -> *const c_void

impl CharucoBoardTrait for Ptr<CharucoBoard>

fn as_raw_mut_CharucoBoard(&mut self) -> *mut c_void

fn set_legacy_pattern(&mut self, legacy_pattern: bool) -> Result<()>

set legacy chessboard pattern.

impl CharucoBoardTraitConst for Ptr<CharucoBoard>

fn as_raw_CharucoBoard(&self) -> *const c_void

fn get_legacy_pattern(&self) -> Result<bool>

fn get_chessboard_size(&self) -> Result<Size>

fn get_square_length(&self) -> Result<f32>

fn get_marker_length(&self) -> Result<f32>

fn get_chessboard_corners(&self) -> Result<Vector<Point3f>>

get CharucoBoard::chessboardCorners

fn get_nearest_marker_idx(&self) -> Result<Vector<Vector<i32>>>

get CharucoBoard::nearestMarkerIdx, for each charuco corner, nearest marker index in ids array

fn get_nearest_marker_corners(&self) -> Result<Vector<Vector<i32>>>

get CharucoBoard::nearestMarkerCorners, for each charuco corner, nearest marker corner id of each marker

fn check_charuco_corners_collinear( &self, charuco_ids: &impl ToInputArray ) -> Result<bool>

check whether the ChArUco markers are collinear

impl CharucoDetectorTrait for Ptr<CharucoDetector>

fn as_raw_mut_CharucoDetector(&mut self) -> *mut c_void

fn set_board(&mut self, board: &impl CharucoBoardTraitConst) -> Result<()>

fn set_charuco_parameters( &mut self, charuco_parameters: &mut impl CharucoParametersTrait ) -> Result<()>

fn set_detector_parameters( &mut self, detector_parameters: &impl DetectorParametersTraitConst ) -> Result<()>

fn set_refine_parameters( &mut self, refine_parameters: RefineParameters ) -> Result<()>

impl CharucoDetectorTraitConst for Ptr<CharucoDetector>

fn as_raw_CharucoDetector(&self) -> *const c_void

fn get_board(&self) -> Result<CharucoBoard>

fn get_charuco_parameters(&self) -> Result<CharucoParameters>

fn get_detector_parameters(&self) -> Result<DetectorParameters>

fn get_refine_parameters(&self) -> Result<RefineParameters>

fn detect_board( &self, image: &impl ToInputArray, charuco_corners: &mut impl ToOutputArray, charuco_ids: &mut impl ToOutputArray, marker_corners: &mut impl ToInputOutputArray, marker_ids: &mut impl ToInputOutputArray ) -> Result<()>

detect aruco markers and interpolate position of ChArUco board corners

fn detect_board_def( &self, image: &impl ToInputArray, charuco_corners: &mut impl ToOutputArray, charuco_ids: &mut impl ToOutputArray ) -> Result<()>

detect aruco markers and interpolate position of ChArUco board corners

fn detect_diamonds( &self, image: &impl ToInputArray, diamond_corners: &mut impl ToOutputArray, diamond_ids: &mut impl ToOutputArray, marker_corners: &mut impl ToInputOutputArray, marker_ids: &mut impl ToInputOutputArray ) -> Result<()>

Detect ChArUco Diamond markers

fn detect_diamonds_def( &self, image: &impl ToInputArray, diamond_corners: &mut impl ToOutputArray, diamond_ids: &mut impl ToOutputArray ) -> Result<()>

Detect ChArUco Diamond markers

impl ChiHistogramCostExtractorTrait for Ptr<ChiHistogramCostExtractor>

fn as_raw_mut_ChiHistogramCostExtractor(&mut self) -> *mut c_void

impl ChiHistogramCostExtractorTraitConst for Ptr<ChiHistogramCostExtractor>

fn as_raw_ChiHistogramCostExtractor(&self) -> *const c_void

impl ColorAverageInpainterTrait for Ptr<ColorAverageInpainter>

fn as_raw_mut_ColorAverageInpainter(&mut self) -> *mut c_void

fn inpaint( &mut self, idx: i32, frame: &mut impl MatTrait, mask: &mut impl MatTrait ) -> Result<()>

impl ColorAverageInpainterTraitConst for Ptr<ColorAverageInpainter>

fn as_raw_ColorAverageInpainter(&self) -> *const c_void

impl ColorInpainterTrait for Ptr<ColorInpainter>

fn as_raw_mut_ColorInpainter(&mut self) -> *mut c_void

fn inpaint( &mut self, idx: i32, frame: &mut impl MatTrait, mask: &mut impl MatTrait ) -> Result<()>

impl ColorInpainterTraitConst for Ptr<ColorInpainter>

fn as_raw_ColorInpainter(&self) -> *const c_void

impl ColorMomentHashTrait for Ptr<ColorMomentHash>

fn as_raw_mut_ColorMomentHash(&mut self) -> *mut c_void

impl ColorMomentHashTraitConst for Ptr<ColorMomentHash>

fn as_raw_ColorMomentHash(&self) -> *const c_void

impl ColoredKinfu_ColoredKinFuTrait for Ptr<ColoredKinfu_ColoredKinFu>

fn as_raw_mut_ColoredKinfu_ColoredKinFu(&mut self) -> *mut c_void

fn reset(&mut self) -> Result<()>

Resets the algorithm

fn update( &mut self, depth: &impl ToInputArray, rgb: &impl ToInputArray ) -> Result<bool>

Process next depth frame

impl ColoredKinfu_ColoredKinFuTraitConst for Ptr<ColoredKinfu_ColoredKinFu>

fn as_raw_ColoredKinfu_ColoredKinFu(&self) -> *const c_void

fn get_params(&self) -> Result<ColoredKinfu_Params>

Get current parameters

fn render(&self, image: &mut impl ToOutputArray) -> Result<()>

Renders a volume into an image

fn render_1( &self, image: &mut impl ToOutputArray, camera_pose: Matx44f ) -> Result<()>

Renders a volume into an image

fn get_cloud( &self, points: &mut impl ToOutputArray, normals: &mut impl ToOutputArray, colors: &mut impl ToOutputArray ) -> Result<()>

Gets points, normals and colors of current 3d mesh

fn get_cloud_def( &self, points: &mut impl ToOutputArray, normals: &mut impl ToOutputArray ) -> Result<()>

Gets points, normals and colors of current 3d mesh

fn get_points(&self, points: &mut impl ToOutputArray) -> Result<()>

Gets points of current 3d mesh

fn get_normals( &self, points: &impl ToInputArray, normals: &mut impl ToOutputArray ) -> Result<()>

Calculates normals for given points

fn get_pose(&self) -> Result<Affine3f>

Get current pose in voxel space

impl ColoredKinfu_ParamsTrait for Ptr<ColoredKinfu_Params>

fn as_raw_mut_ColoredKinfu_Params(&mut self) -> *mut c_void

fn set_frame_size(&mut self, val: Size)

frame size in pixels

fn set_rgb_frame_size(&mut self, val: Size)

rgb frame size in pixels

fn set_volume_type(&mut self, val: Kinfu_VolumeType)

fn set_intr(&mut self, val: Matx33f)

camera intrinsics

fn set_rgb_intr(&mut self, val: Matx33f)

rgb camera intrinsics

fn set_depth_factor(&mut self, val: f32)

pre-scale per 1 meter for input values

fn set_bilateral_sigma_depth(&mut self, val: f32)

Depth sigma in meters for bilateral smooth

fn set_bilateral_sigma_spatial(&mut self, val: f32)

Spatial sigma in pixels for bilateral smooth

fn set_bilateral_kernel_size(&mut self, val: i32)

Kernel size in pixels for bilateral smooth

fn set_pyramid_levels(&mut self, val: i32)

Number of pyramid levels for ICP

fn set_volume_dims(&mut self, val: Vec3i)

Resolution of voxel space

fn set_voxel_size(&mut self, val: f32)

Size of voxel in meters

fn set_tsdf_min_camera_movement(&mut self, val: f32)

Minimal camera movement in meters

fn set_volume_pose(&mut self, val: Affine3f)

initial volume pose in meters

fn set_tsdf_trunc_dist(&mut self, val: f32)

distance to truncate in meters

fn set_tsdf_max_weight(&mut self, val: i32)

max number of frames per voxel

fn set_raycast_step_factor(&mut self, val: f32)

A length of one raycast step

fn set_light_pose(&mut self, val: Vec3f)

light pose for rendering in meters

fn set_icp_dist_thresh(&mut self, val: f32)

distance theshold for ICP in meters

fn set_icp_angle_thresh(&mut self, val: f32)

angle threshold for ICP in radians

fn set_icp_iterations(&mut self, val: Vector<i32>)

number of ICP iterations for each pyramid level

fn set_truncate_threshold(&mut self, val: f32)

Threshold for depth truncation in meters

fn set_initial_volume_pose(&mut self, r: Matx33f, t: Vec3f) -> Result<()>

Set Initial Volume Pose Sets the initial pose of the TSDF volume.

fn set_initial_volume_pose_1(&mut self, homogen_tf: Matx44f) -> Result<()>

Set Initial Volume Pose Sets the initial pose of the TSDF volume.

impl ColoredKinfu_ParamsTraitConst for Ptr<ColoredKinfu_Params>

fn as_raw_ColoredKinfu_Params(&self) -> *const c_void

fn frame_size(&self) -> Size

frame size in pixels

fn rgb_frame_size(&self) -> Size

rgb frame size in pixels

fn volume_type(&self) -> Kinfu_VolumeType

fn intr(&self) -> Matx33f

camera intrinsics

fn rgb_intr(&self) -> Matx33f

rgb camera intrinsics

fn depth_factor(&self) -> f32

pre-scale per 1 meter for input values

fn bilateral_sigma_depth(&self) -> f32

Depth sigma in meters for bilateral smooth

fn bilateral_sigma_spatial(&self) -> f32

Spatial sigma in pixels for bilateral smooth

fn bilateral_kernel_size(&self) -> i32

Kernel size in pixels for bilateral smooth

fn pyramid_levels(&self) -> i32

Number of pyramid levels for ICP

fn volume_dims(&self) -> Vec3i

Resolution of voxel space

fn voxel_size(&self) -> f32

Size of voxel in meters

fn tsdf_min_camera_movement(&self) -> f32

Minimal camera movement in meters

fn volume_pose(&self) -> Affine3f

initial volume pose in meters

fn tsdf_trunc_dist(&self) -> f32

distance to truncate in meters

fn tsdf_max_weight(&self) -> i32

max number of frames per voxel

fn raycast_step_factor(&self) -> f32

A length of one raycast step

fn light_pose(&self) -> Vec3f

light pose for rendering in meters

fn icp_dist_thresh(&self) -> f32

distance theshold for ICP in meters

fn icp_angle_thresh(&self) -> f32

angle threshold for ICP in radians

fn icp_iterations(&self) -> Vector<i32>

number of ICP iterations for each pyramid level

fn truncate_threshold(&self) -> f32

Threshold for depth truncation in meters

impl CompareLayerTrait for Ptr<CompareLayer>

fn as_raw_mut_CompareLayer(&mut self) -> *mut c_void

impl CompareLayerTraitConst for Ptr<CompareLayer>

fn as_raw_CompareLayer(&self) -> *const c_void

impl CompositeIndexParamsTrait for Ptr<CompositeIndexParams>

fn as_raw_mut_CompositeIndexParams(&mut self) -> *mut c_void

impl CompositeIndexParamsTraitConst for Ptr<CompositeIndexParams>

fn as_raw_CompositeIndexParams(&self) -> *const c_void

impl CompressedRectilinearPortraitWarperTrait for Ptr<CompressedRectilinearPortraitWarper>

fn as_raw_mut_CompressedRectilinearPortraitWarper(&mut self) -> *mut c_void

impl CompressedRectilinearPortraitWarperTraitConst for Ptr<CompressedRectilinearPortraitWarper>

fn as_raw_CompressedRectilinearPortraitWarper(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl CompressedRectilinearWarperTrait for Ptr<CompressedRectilinearWarper>

fn as_raw_mut_CompressedRectilinearWarper(&mut self) -> *mut c_void

impl CompressedRectilinearWarperTraitConst for Ptr<CompressedRectilinearWarper>

fn as_raw_CompressedRectilinearWarper(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl ConcatLayerTrait for Ptr<ConcatLayer>

fn as_raw_mut_ConcatLayer(&mut self) -> *mut c_void

fn set_axis(&mut self, val: i32)

fn set_padding(&mut self, val: bool)

Add zero padding in case of concatenation of blobs with different spatial sizes.

fn set_padding_value(&mut self, val: i32)

impl ConcatLayerTraitConst for Ptr<ConcatLayer>

fn as_raw_ConcatLayer(&self) -> *const c_void

fn axis(&self) -> i32

fn padding(&self) -> bool

Add zero padding in case of concatenation of blobs with different spatial sizes.

fn padding_value(&self) -> i32

impl ConjGradSolverTrait for Ptr<ConjGradSolver>

fn as_raw_mut_ConjGradSolver(&mut self) -> *mut c_void

impl ConjGradSolverTraitConst for Ptr<ConjGradSolver>

fn as_raw_ConjGradSolver(&self) -> *const c_void

impl ConsistentMosaicInpainterTrait for Ptr<ConsistentMosaicInpainter>

fn as_raw_mut_ConsistentMosaicInpainter(&mut self) -> *mut c_void

fn set_stdev_thresh(&mut self, val: f32) -> Result<()>

fn inpaint( &mut self, idx: i32, frame: &mut impl MatTrait, mask: &mut impl MatTrait ) -> Result<()>

impl ConsistentMosaicInpainterTraitConst for Ptr<ConsistentMosaicInpainter>

fn as_raw_ConsistentMosaicInpainter(&self) -> *const c_void

fn stdev_thresh(&self) -> Result<f32>

impl ConstLayerTrait for Ptr<ConstLayer>

fn as_raw_mut_ConstLayer(&mut self) -> *mut c_void

impl ConstLayerTraitConst for Ptr<ConstLayer>

fn as_raw_ConstLayer(&self) -> *const c_void

impl ContourFittingTrait for Ptr<ContourFitting>

fn as_raw_mut_ContourFitting(&mut self) -> *mut c_void

fn estimate_transformation( &mut self, src: &impl ToInputArray, dst: &impl ToInputArray, alpha_phi_st: &mut impl ToOutputArray, dist: &mut f64, fd_contour: bool ) -> Result<()>

Fit two closed curves using fourier descriptors. More details in PersoonFu1977 and BergerRaghunathan1998

fn estimate_transformation_def( &mut self, src: &impl ToInputArray, dst: &impl ToInputArray, alpha_phi_st: &mut impl ToOutputArray ) -> Result<()>

Fit two closed curves using fourier descriptors. More details in PersoonFu1977 and BergerRaghunathan1998

fn estimate_transformation_1( &mut self, src: &impl ToInputArray, dst: &impl ToInputArray, alpha_phi_st: &mut impl ToOutputArray, dist: &mut f64, fd_contour: bool ) -> Result<()>

Fit two closed curves using fourier descriptors. More details in PersoonFu1977 and BergerRaghunathan1998

fn estimate_transformation_def_1( &mut self, src: &impl ToInputArray, dst: &impl ToInputArray, alpha_phi_st: &mut impl ToOutputArray, dist: &mut f64 ) -> Result<()>

Fit two closed curves using fourier descriptors. More details in PersoonFu1977 and BergerRaghunathan1998

fn set_ctr_size(&mut self, n: i32) -> Result<()>

set number of Fourier descriptors used in estimateTransformation

fn set_fd_size(&mut self, n: i32) -> Result<()>

set number of Fourier descriptors when estimateTransformation used vector

fn get_ctr_size(&mut self) -> Result<i32>

Returns

fn get_fd_size(&mut self) -> Result<i32>

Returns

impl ContourFittingTraitConst for Ptr<ContourFitting>

fn as_raw_ContourFitting(&self) -> *const c_void

impl ConvolutionLayerInt8Trait for Ptr<ConvolutionLayerInt8>

fn as_raw_mut_ConvolutionLayerInt8(&mut self) -> *mut c_void

fn set_input_zp(&mut self, val: i32)

fn set_output_zp(&mut self, val: i32)

fn set_input_sc(&mut self, val: f32)

fn set_output_sc(&mut self, val: f32)

fn set_per_channel(&mut self, val: bool)

fn set_use_winograd(&mut self, val: bool)

C++ default parameters

impl ConvolutionLayerInt8TraitConst for Ptr<ConvolutionLayerInt8>

fn as_raw_ConvolutionLayerInt8(&self) -> *const c_void

fn input_zp(&self) -> i32

fn output_zp(&self) -> i32

fn input_sc(&self) -> f32

fn output_sc(&self) -> f32

fn per_channel(&self) -> bool

fn use_winograd(&self) -> bool

impl ConvolutionLayerTrait for Ptr<ConvolutionLayer>

fn as_raw_mut_ConvolutionLayer(&mut self) -> *mut c_void

fn set_fused_activation(&mut self, val: bool)

C++ default parameters

fn set_fused_add(&mut self, val: bool)

C++ default parameters

fn set_use_winograd(&mut self, val: bool)

C++ default parameters

impl ConvolutionLayerTraitConst for Ptr<ConvolutionLayer>

fn as_raw_ConvolutionLayer(&self) -> *const c_void

fn fused_activation(&self) -> bool

fn fused_add(&self) -> bool

fn use_winograd(&self) -> bool

impl ConvolutionTrait for Ptr<Convolution>

fn as_raw_mut_Convolution(&mut self) -> *mut c_void

fn convolve( &mut self, image: &impl ToInputArray, templ: &impl ToInputArray, result: &mut impl ToOutputArray, ccorr: bool, stream: &mut impl StreamTrait ) -> Result<()>

Computes a convolution (or cross-correlation) of two images.

fn convolve_def( &mut self, image: &impl ToInputArray, templ: &impl ToInputArray, result: &mut impl ToOutputArray ) -> Result<()>

Computes a convolution (or cross-correlation) of two images.

impl ConvolutionTraitConst for Ptr<Convolution>

fn as_raw_Convolution(&self) -> *const c_void

impl CorrelationLayerTrait for Ptr<CorrelationLayer>

fn as_raw_mut_CorrelationLayer(&mut self) -> *mut c_void

impl CorrelationLayerTraitConst for Ptr<CorrelationLayer>

fn as_raw_CorrelationLayer(&self) -> *const c_void

impl CosLayerTrait for Ptr<CosLayer>

fn as_raw_mut_CosLayer(&mut self) -> *mut c_void

impl CosLayerTraitConst for Ptr<CosLayer>

fn as_raw_CosLayer(&self) -> *const c_void

impl CoshLayerTrait for Ptr<CoshLayer>

fn as_raw_mut_CoshLayer(&mut self) -> *mut c_void

impl CoshLayerTraitConst for Ptr<CoshLayer>

fn as_raw_CoshLayer(&self) -> *const c_void

impl CropAndResizeLayerTrait for Ptr<CropAndResizeLayer>

fn as_raw_mut_CropAndResizeLayer(&mut self) -> *mut c_void

impl CropAndResizeLayerTraitConst for Ptr<CropAndResizeLayer>

fn as_raw_CropAndResizeLayer(&self) -> *const c_void

impl CropLayerTrait for Ptr<CropLayer>

fn as_raw_mut_CropLayer(&mut self) -> *mut c_void

impl CropLayerTraitConst for Ptr<CropLayer>

fn as_raw_CropLayer(&self) -> *const c_void

impl CumSumLayerTrait for Ptr<CumSumLayer>

fn as_raw_mut_CumSumLayer(&mut self) -> *mut c_void

fn set_exclusive(&mut self, val: i32)

fn set_reverse(&mut self, val: i32)

impl CumSumLayerTraitConst for Ptr<CumSumLayer>

fn as_raw_CumSumLayer(&self) -> *const c_void

fn exclusive(&self) -> i32

fn reverse(&self) -> i32

impl CustomPatternTrait for Ptr<CustomPattern>

fn as_raw_mut_CustomPattern(&mut self) -> *mut c_void

fn create( &mut self, pattern: &impl ToInputArray, board_size: Size2f, output: &mut impl ToOutputArray ) -> Result<bool>

C++ default parameters

fn create_def( &mut self, pattern: &impl ToInputArray, board_size: Size2f ) -> Result<bool>

Note

fn find_pattern( &mut self, image: &impl ToInputArray, matched_features: &mut impl ToOutputArray, pattern_points: &mut impl ToOutputArray, ratio: f64, proj_error: f64, refine_position: bool, out: &mut impl ToOutputArray, h: &mut impl ToOutputArray, pattern_corners: &mut impl ToOutputArray ) -> Result<bool>

C++ default parameters

fn find_pattern_def( &mut self, image: &impl ToInputArray, matched_features: &mut impl ToOutputArray, pattern_points: &mut impl ToOutputArray ) -> Result<bool>

Note

fn is_initialized(&mut self) -> Result<bool>

fn get_pattern_points( &mut self, original_points: &mut Vector<KeyPoint> ) -> Result<()>

fn get_pixel_size(&mut self) -> Result<f64>

fn set_feature_detector( &mut self, feature_detector: Ptr<Feature2D> ) -> Result<bool>

fn set_descriptor_extractor( &mut self, extractor: Ptr<Feature2D> ) -> Result<bool>

fn set_descriptor_matcher( &mut self, matcher: Ptr<DescriptorMatcher> ) -> Result<bool>

fn get_feature_detector(&mut self) -> Result<Ptr<Feature2D>>

fn get_descriptor_extractor(&mut self) -> Result<Ptr<Feature2D>>

fn get_descriptor_matcher(&mut self) -> Result<Ptr<DescriptorMatcher>>

fn calibrate( &mut self, object_points: &impl ToInputArray, image_points: &impl ToInputArray, image_size: Size, camera_matrix: &mut impl ToInputOutputArray, dist_coeffs: &mut impl ToInputOutputArray, rvecs: &mut impl ToOutputArray, tvecs: &mut impl ToOutputArray, flags: i32, criteria: TermCriteria ) -> Result<f64>

C++ default parameters

fn calibrate_def( &mut self, object_points: &impl ToInputArray, image_points: &impl ToInputArray, image_size: Size, camera_matrix: &mut impl ToInputOutputArray, dist_coeffs: &mut impl ToInputOutputArray, rvecs: &mut impl ToOutputArray, tvecs: &mut impl ToOutputArray ) -> Result<f64>

Note

fn find_rt( &mut self, object_points: &impl ToInputArray, image_points: &impl ToInputArray, camera_matrix: &impl ToInputArray, dist_coeffs: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray, use_extrinsic_guess: bool, flags: i32 ) -> Result<bool>

C++ default parameters

fn find_rt_def( &mut self, object_points: &impl ToInputArray, image_points: &impl ToInputArray, camera_matrix: &impl ToInputArray, dist_coeffs: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray ) -> Result<bool>

Note

fn find_rt_1( &mut self, image: &impl ToInputArray, camera_matrix: &impl ToInputArray, dist_coeffs: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray, use_extrinsic_guess: bool, flags: i32 ) -> Result<bool>

C++ default parameters

fn find_rt_def_1( &mut self, image: &impl ToInputArray, camera_matrix: &impl ToInputArray, dist_coeffs: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray ) -> Result<bool>

Note

fn find_rt_ransac( &mut self, object_points: &impl ToInputArray, image_points: &impl ToInputArray, camera_matrix: &impl ToInputArray, dist_coeffs: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray, use_extrinsic_guess: bool, iterations_count: i32, reprojection_error: f32, min_inliers_count: i32, inliers: &mut impl ToOutputArray, flags: i32 ) -> Result<bool>

C++ default parameters

fn find_rt_ransac_def( &mut self, object_points: &impl ToInputArray, image_points: &impl ToInputArray, camera_matrix: &impl ToInputArray, dist_coeffs: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray ) -> Result<bool>

Note

fn find_rt_ransac_1( &mut self, image: &impl ToInputArray, camera_matrix: &impl ToInputArray, dist_coeffs: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray, use_extrinsic_guess: bool, iterations_count: i32, reprojection_error: f32, min_inliers_count: i32, inliers: &mut impl ToOutputArray, flags: i32 ) -> Result<bool>

C++ default parameters

fn find_rt_ransac_def_1( &mut self, image: &impl ToInputArray, camera_matrix: &impl ToInputArray, dist_coeffs: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray ) -> Result<bool>

Note

fn draw_orientation( &mut self, image: &mut impl ToInputOutputArray, tvec: &impl ToInputArray, rvec: &impl ToInputArray, camera_matrix: &impl ToInputArray, dist_coeffs: &impl ToInputArray, axis_length: f64, axis_width: i32 ) -> Result<()>

C++ default parameters

fn draw_orientation_def( &mut self, image: &mut impl ToInputOutputArray, tvec: &impl ToInputArray, rvec: &impl ToInputArray, camera_matrix: &impl ToInputArray, dist_coeffs: &impl ToInputArray ) -> Result<()>

Note

impl CustomPatternTraitConst for Ptr<CustomPattern>

fn as_raw_CustomPattern(&self) -> *const c_void

impl CylindricalWarperGpuTrait for Ptr<CylindricalWarperGpu>

fn as_raw_mut_CylindricalWarperGpu(&mut self) -> *mut c_void

impl CylindricalWarperGpuTraitConst for Ptr<CylindricalWarperGpu>

fn as_raw_CylindricalWarperGpu(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl CylindricalWarperTrait for Ptr<CylindricalWarper>

fn as_raw_mut_CylindricalWarper(&mut self) -> *mut c_void

impl CylindricalWarperTraitConst for Ptr<CylindricalWarper>

fn as_raw_CylindricalWarper(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl DAISYTrait for Ptr<DAISY>

fn as_raw_mut_DAISY(&mut self) -> *mut c_void

fn set_radius(&mut self, radius: f32) -> Result<()>

fn set_q_radius(&mut self, q_radius: i32) -> Result<()>

fn set_q_theta(&mut self, q_theta: i32) -> Result<()>

fn set_q_hist(&mut self, q_hist: i32) -> Result<()>

fn set_norm(&mut self, norm: i32) -> Result<()>

fn set_h(&mut self, h: &impl ToInputArray) -> Result<()>

fn set_interpolation(&mut self, interpolation: bool) -> Result<()>

fn set_use_orientation(&mut self, use_orientation: bool) -> Result<()>

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

fn compute_1( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

fn compute_2( &mut self, image: &impl ToInputArray, roi: Rect, descriptors: &mut impl ToOutputArray ) -> Result<()>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

fn compute_3( &mut self, image: &impl ToInputArray, descriptors: &mut impl ToOutputArray ) -> Result<()>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

impl DAISYTraitConst for Ptr<DAISY>

fn as_raw_DAISY(&self) -> *const c_void

fn get_radius(&self) -> Result<f32>

fn get_q_radius(&self) -> Result<i32>

fn get_q_theta(&self) -> Result<i32>

fn get_q_hist(&self) -> Result<i32>

fn get_norm(&self) -> Result<i32>

fn get_h(&self) -> Result<Mat>

fn get_interpolation(&self) -> Result<bool>

fn get_use_orientation(&self) -> Result<bool>

fn get_default_name(&self) -> Result<String>

fn get_descriptor( &self, y: f64, x: f64, orientation: i32, descriptor: &mut f32 ) -> Result<()>

Parameters

fn get_descriptor_1( &self, y: f64, x: f64, orientation: i32, descriptor: &mut f32, h: &mut f64 ) -> Result<bool>

Parameters

fn get_unnormalized_descriptor( &self, y: f64, x: f64, orientation: i32, descriptor: &mut f32 ) -> Result<()>

Parameters

fn get_unnormalized_descriptor_1( &self, y: f64, x: f64, orientation: i32, descriptor: &mut f32, h: &mut f64 ) -> Result<bool>

Parameters

impl DFTTrait for Ptr<DFT>

fn as_raw_mut_DFT(&mut self) -> *mut c_void

fn compute( &mut self, image: &impl ToInputArray, result: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Computes an FFT of a given image.

fn compute_def( &mut self, image: &impl ToInputArray, result: &mut impl ToOutputArray ) -> Result<()>

Computes an FFT of a given image.

impl DFTTraitConst for Ptr<DFT>

fn as_raw_DFT(&self) -> *const c_void

impl DISOpticalFlowTrait for Ptr<DISOpticalFlow>

fn as_raw_mut_DISOpticalFlow(&mut self) -> *mut c_void

fn set_finest_scale(&mut self, val: i32) -> Result<()>

Finest level of the Gaussian pyramid on which the flow is computed (zero level corresponds to the original image resolution). The final flow is obtained by bilinear upscaling.

fn set_patch_size(&mut self, val: i32) -> Result<()>

Size of an image patch for matching (in pixels). Normally, default 8x8 patches work well enough in most cases.

fn set_patch_stride(&mut self, val: i32) -> Result<()>

Stride between neighbor patches. Must be less than patch size. Lower values correspond to higher flow quality.

fn set_gradient_descent_iterations(&mut self, val: i32) -> Result<()>

Maximum number of gradient descent iterations in the patch inverse search stage. Higher values may improve quality in some cases.

fn set_variational_refinement_iterations(&mut self, val: i32) -> Result<()>

Maximum number of gradient descent iterations in the patch inverse search stage. Higher values may improve quality in some cases.

fn set_variational_refinement_alpha(&mut self, val: f32) -> Result<()>

Weight of the smoothness term

fn set_variational_refinement_delta(&mut self, val: f32) -> Result<()>

Weight of the color constancy term

fn set_variational_refinement_gamma(&mut self, val: f32) -> Result<()>

Weight of the gradient constancy term

fn set_use_mean_normalization(&mut self, val: bool) -> Result<()>

Whether to use mean-normalization of patches when computing patch distance. It is turned on by default as it typically provides a noticeable quality boost because of increased robustness to illumination variations. Turn it off if you are certain that your sequence doesn’t contain any changes in illumination.

fn set_use_spatial_propagation(&mut self, val: bool) -> Result<()>

Whether to use spatial propagation of good optical flow vectors. This option is turned on by default, as it tends to work better on average and can sometimes help recover from major errors introduced by the coarse-to-fine scheme employed by the DIS optical flow algorithm. Turning this option off can make the output flow field a bit smoother, however.

impl DISOpticalFlowTraitConst for Ptr<DISOpticalFlow>

fn as_raw_DISOpticalFlow(&self) -> *const c_void

fn get_finest_scale(&self) -> Result<i32>

Finest level of the Gaussian pyramid on which the flow is computed (zero level corresponds to the original image resolution). The final flow is obtained by bilinear upscaling.

fn get_patch_size(&self) -> Result<i32>

Size of an image patch for matching (in pixels). Normally, default 8x8 patches work well enough in most cases.

fn get_patch_stride(&self) -> Result<i32>

Stride between neighbor patches. Must be less than patch size. Lower values correspond to higher flow quality.

fn get_gradient_descent_iterations(&self) -> Result<i32>

Maximum number of gradient descent iterations in the patch inverse search stage. Higher values may improve quality in some cases.

fn get_variational_refinement_iterations(&self) -> Result<i32>

Number of fixed point iterations of variational refinement per scale. Set to zero to disable variational refinement completely. Higher values will typically result in more smooth and high-quality flow.

fn get_variational_refinement_alpha(&self) -> Result<f32>

Weight of the smoothness term

fn get_variational_refinement_delta(&self) -> Result<f32>

Weight of the color constancy term

fn get_variational_refinement_gamma(&self) -> Result<f32>

Weight of the gradient constancy term

fn get_use_mean_normalization(&self) -> Result<bool>

Whether to use mean-normalization of patches when computing patch distance. It is turned on by default as it typically provides a noticeable quality boost because of increased robustness to illumination variations. Turn it off if you are certain that your sequence doesn’t contain any changes in illumination.

fn get_use_spatial_propagation(&self) -> Result<bool>

Whether to use spatial propagation of good optical flow vectors. This option is turned on by default, as it tends to work better on average and can sometimes help recover from major errors introduced by the coarse-to-fine scheme employed by the DIS optical flow algorithm. Turning this option off can make the output flow field a bit smoother, however.

impl DPMDetectorTrait for Ptr<DPMDetector>

fn as_raw_mut_DPMDetector(&mut self) -> *mut c_void

fn detect( &mut self, image: &mut impl MatTrait, objects: &mut Vector<DPMDetector_ObjectDetection> ) -> Result<()>

Find rectangular regions in the given image that are likely to contain objects of loaded classes (models) and corresponding confidence levels.

impl DPMDetectorTraitConst for Ptr<DPMDetector>

fn as_raw_DPMDetector(&self) -> *const c_void

fn is_empty(&self) -> Result<bool>

fn get_class_names(&self) -> Result<Vector<String>>

Return the class (model) names that were passed in constructor or method load or extracted from models filenames in those methods.

fn get_class_count(&self) -> Result<size_t>

Return a count of loaded models (classes).

impl DTFilterTrait for Ptr<DTFilter>

fn as_raw_mut_DTFilter(&mut self) -> *mut c_void

fn filter( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, d_depth: i32 ) -> Result<()>

Produce domain transform filtering operation on source image.

fn filter_def( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Produce domain transform filtering operation on source image.

impl DTFilterTraitConst for Ptr<DTFilter>

fn as_raw_DTFilter(&self) -> *const c_void

impl DTreesTrait for Ptr<Boost>

fn as_raw_mut_DTrees(&mut self) -> *mut c_void

fn set_max_categories(&mut self, val: i32) -> Result<()>

Cluster possible values of a categorical variable into K<=maxCategories clusters to find a suboptimal split. If a discrete variable, on which the training procedure tries to make a split, takes more than maxCategories values, the precise best subset estimation may take a very long time because the algorithm is exponential. Instead, many decision trees engines (including our implementation) try to find sub-optimal split in this case by clustering all the samples into maxCategories clusters that is some categories are merged together. The clustering is applied only in n > 2-class classification problems for categorical variables with N > max_categories possible values. In case of regression and 2-class classification the optimal split can be found efficiently without employing clustering, thus the parameter is not used in these cases. Default value is 10.

fn set_max_depth(&mut self, val: i32) -> Result<()>

The maximum possible depth of the tree. That is the training algorithms attempts to split a node while its depth is less than maxDepth. The root node has zero depth. The actual depth may be smaller if the other termination criteria are met (see the outline of the training procedure [ml_intro_trees] “here”), and/or if the tree is pruned. Default value is INT_MAX.

fn set_min_sample_count(&mut self, val: i32) -> Result<()>

If the number of samples in a node is less than this parameter then the node will not be split.

fn set_cv_folds(&mut self, val: i32) -> Result<()>

If CVFolds > 1 then algorithms prunes the built decision tree using K-fold cross-validation procedure where K is equal to CVFolds. Default value is 10.

fn set_use_surrogates(&mut self, val: bool) -> Result<()>

If true then surrogate splits will be built. These splits allow to work with missing data and compute variable importance correctly. Default value is false.

fn set_use1_se_rule(&mut self, val: bool) -> Result<()>

If true then a pruning will be harsher. This will make a tree more compact and more resistant to the training data noise but a bit less accurate. Default value is true.

fn set_truncate_pruned_tree(&mut self, val: bool) -> Result<()>

If true then pruned branches are physically removed from the tree. Otherwise they are retained and it is possible to get results from the original unpruned (or pruned less aggressively) tree. Default value is true.

fn set_regression_accuracy(&mut self, val: f32) -> Result<()>

Termination criteria for regression trees. If all absolute differences between an estimated value in a node and values of train samples in this node are less than this parameter then the node will not be split further. Default value is 0.01f

fn set_priors(&mut self, val: &impl MatTraitConst) -> Result<()>

The array of a priori class probabilities, sorted by the class label value.

impl DTreesTrait for Ptr<DTrees>

fn as_raw_mut_DTrees(&mut self) -> *mut c_void

fn set_max_categories(&mut self, val: i32) -> Result<()>

Cluster possible values of a categorical variable into K<=maxCategories clusters to find a suboptimal split. If a discrete variable, on which the training procedure tries to make a split, takes more than maxCategories values, the precise best subset estimation may take a very long time because the algorithm is exponential. Instead, many decision trees engines (including our implementation) try to find sub-optimal split in this case by clustering all the samples into maxCategories clusters that is some categories are merged together. The clustering is applied only in n > 2-class classification problems for categorical variables with N > max_categories possible values. In case of regression and 2-class classification the optimal split can be found efficiently without employing clustering, thus the parameter is not used in these cases. Default value is 10.

fn set_max_depth(&mut self, val: i32) -> Result<()>

The maximum possible depth of the tree. That is the training algorithms attempts to split a node while its depth is less than maxDepth. The root node has zero depth. The actual depth may be smaller if the other termination criteria are met (see the outline of the training procedure [ml_intro_trees] “here”), and/or if the tree is pruned. Default value is INT_MAX.

fn set_min_sample_count(&mut self, val: i32) -> Result<()>

If the number of samples in a node is less than this parameter then the node will not be split.

fn set_cv_folds(&mut self, val: i32) -> Result<()>

If CVFolds > 1 then algorithms prunes the built decision tree using K-fold cross-validation procedure where K is equal to CVFolds. Default value is 10.

fn set_use_surrogates(&mut self, val: bool) -> Result<()>

If true then surrogate splits will be built. These splits allow to work with missing data and compute variable importance correctly. Default value is false.

fn set_use1_se_rule(&mut self, val: bool) -> Result<()>

If true then a pruning will be harsher. This will make a tree more compact and more resistant to the training data noise but a bit less accurate. Default value is true.

fn set_truncate_pruned_tree(&mut self, val: bool) -> Result<()>

If true then pruned branches are physically removed from the tree. Otherwise they are retained and it is possible to get results from the original unpruned (or pruned less aggressively) tree. Default value is true.

fn set_regression_accuracy(&mut self, val: f32) -> Result<()>

Termination criteria for regression trees. If all absolute differences between an estimated value in a node and values of train samples in this node are less than this parameter then the node will not be split further. Default value is 0.01f

fn set_priors(&mut self, val: &impl MatTraitConst) -> Result<()>

The array of a priori class probabilities, sorted by the class label value.

impl DTreesTrait for Ptr<RTrees>

fn as_raw_mut_DTrees(&mut self) -> *mut c_void

fn set_max_categories(&mut self, val: i32) -> Result<()>

Cluster possible values of a categorical variable into K<=maxCategories clusters to find a suboptimal split. If a discrete variable, on which the training procedure tries to make a split, takes more than maxCategories values, the precise best subset estimation may take a very long time because the algorithm is exponential. Instead, many decision trees engines (including our implementation) try to find sub-optimal split in this case by clustering all the samples into maxCategories clusters that is some categories are merged together. The clustering is applied only in n > 2-class classification problems for categorical variables with N > max_categories possible values. In case of regression and 2-class classification the optimal split can be found efficiently without employing clustering, thus the parameter is not used in these cases. Default value is 10.

fn set_max_depth(&mut self, val: i32) -> Result<()>

The maximum possible depth of the tree. That is the training algorithms attempts to split a node while its depth is less than maxDepth. The root node has zero depth. The actual depth may be smaller if the other termination criteria are met (see the outline of the training procedure [ml_intro_trees] “here”), and/or if the tree is pruned. Default value is INT_MAX.

fn set_min_sample_count(&mut self, val: i32) -> Result<()>

If the number of samples in a node is less than this parameter then the node will not be split.

fn set_cv_folds(&mut self, val: i32) -> Result<()>

If CVFolds > 1 then algorithms prunes the built decision tree using K-fold cross-validation procedure where K is equal to CVFolds. Default value is 10.

fn set_use_surrogates(&mut self, val: bool) -> Result<()>

If true then surrogate splits will be built. These splits allow to work with missing data and compute variable importance correctly. Default value is false.

fn set_use1_se_rule(&mut self, val: bool) -> Result<()>

If true then a pruning will be harsher. This will make a tree more compact and more resistant to the training data noise but a bit less accurate. Default value is true.

fn set_truncate_pruned_tree(&mut self, val: bool) -> Result<()>

If true then pruned branches are physically removed from the tree. Otherwise they are retained and it is possible to get results from the original unpruned (or pruned less aggressively) tree. Default value is true.

fn set_regression_accuracy(&mut self, val: f32) -> Result<()>

Termination criteria for regression trees. If all absolute differences between an estimated value in a node and values of train samples in this node are less than this parameter then the node will not be split further. Default value is 0.01f

fn set_priors(&mut self, val: &impl MatTraitConst) -> Result<()>

The array of a priori class probabilities, sorted by the class label value.

impl DTreesTraitConst for Ptr<Boost>

fn as_raw_DTrees(&self) -> *const c_void

fn get_max_categories(&self) -> Result<i32>

Cluster possible values of a categorical variable into K<=maxCategories clusters to find a suboptimal split. If a discrete variable, on which the training procedure tries to make a split, takes more than maxCategories values, the precise best subset estimation may take a very long time because the algorithm is exponential. Instead, many decision trees engines (including our implementation) try to find sub-optimal split in this case by clustering all the samples into maxCategories clusters that is some categories are merged together. The clustering is applied only in n > 2-class classification problems for categorical variables with N > max_categories possible values. In case of regression and 2-class classification the optimal split can be found efficiently without employing clustering, thus the parameter is not used in these cases. Default value is 10.

fn get_max_depth(&self) -> Result<i32>

The maximum possible depth of the tree. That is the training algorithms attempts to split a node while its depth is less than maxDepth. The root node has zero depth. The actual depth may be smaller if the other termination criteria are met (see the outline of the training procedure [ml_intro_trees] “here”), and/or if the tree is pruned. Default value is INT_MAX.

fn get_min_sample_count(&self) -> Result<i32>

If the number of samples in a node is less than this parameter then the node will not be split.

fn get_cv_folds(&self) -> Result<i32>

If CVFolds > 1 then algorithms prunes the built decision tree using K-fold cross-validation procedure where K is equal to CVFolds. Default value is 10.

fn get_use_surrogates(&self) -> Result<bool>

If true then surrogate splits will be built. These splits allow to work with missing data and compute variable importance correctly. Default value is false.

fn get_use1_se_rule(&self) -> Result<bool>

If true then a pruning will be harsher. This will make a tree more compact and more resistant to the training data noise but a bit less accurate. Default value is true.

fn get_truncate_pruned_tree(&self) -> Result<bool>

If true then pruned branches are physically removed from the tree. Otherwise they are retained and it is possible to get results from the original unpruned (or pruned less aggressively) tree. Default value is true.

fn get_regression_accuracy(&self) -> Result<f32>

Termination criteria for regression trees. If all absolute differences between an estimated value in a node and values of train samples in this node are less than this parameter then the node will not be split further. Default value is 0.01f

fn get_priors(&self) -> Result<Mat>

The array of a priori class probabilities, sorted by the class label value.

fn get_roots(&self) -> Result<Vector<i32>>

Returns indices of root nodes

fn get_nodes(&self) -> Result<Vector<DTrees_Node>>

Returns all the nodes

fn get_splits(&self) -> Result<Vector<DTrees_Split>>

Returns all the splits

fn get_subsets(&self) -> Result<Vector<i32>>

Returns all the bitsets for categorical splits

impl DTreesTraitConst for Ptr<DTrees>

fn as_raw_DTrees(&self) -> *const c_void

fn get_max_categories(&self) -> Result<i32>

Cluster possible values of a categorical variable into K<=maxCategories clusters to find a suboptimal split. If a discrete variable, on which the training procedure tries to make a split, takes more than maxCategories values, the precise best subset estimation may take a very long time because the algorithm is exponential. Instead, many decision trees engines (including our implementation) try to find sub-optimal split in this case by clustering all the samples into maxCategories clusters that is some categories are merged together. The clustering is applied only in n > 2-class classification problems for categorical variables with N > max_categories possible values. In case of regression and 2-class classification the optimal split can be found efficiently without employing clustering, thus the parameter is not used in these cases. Default value is 10.

fn get_max_depth(&self) -> Result<i32>

The maximum possible depth of the tree. That is the training algorithms attempts to split a node while its depth is less than maxDepth. The root node has zero depth. The actual depth may be smaller if the other termination criteria are met (see the outline of the training procedure [ml_intro_trees] “here”), and/or if the tree is pruned. Default value is INT_MAX.

fn get_min_sample_count(&self) -> Result<i32>

If the number of samples in a node is less than this parameter then the node will not be split.

fn get_cv_folds(&self) -> Result<i32>

If CVFolds > 1 then algorithms prunes the built decision tree using K-fold cross-validation procedure where K is equal to CVFolds. Default value is 10.

fn get_use_surrogates(&self) -> Result<bool>

If true then surrogate splits will be built. These splits allow to work with missing data and compute variable importance correctly. Default value is false.

fn get_use1_se_rule(&self) -> Result<bool>

If true then a pruning will be harsher. This will make a tree more compact and more resistant to the training data noise but a bit less accurate. Default value is true.

fn get_truncate_pruned_tree(&self) -> Result<bool>

If true then pruned branches are physically removed from the tree. Otherwise they are retained and it is possible to get results from the original unpruned (or pruned less aggressively) tree. Default value is true.

fn get_regression_accuracy(&self) -> Result<f32>

Termination criteria for regression trees. If all absolute differences between an estimated value in a node and values of train samples in this node are less than this parameter then the node will not be split further. Default value is 0.01f

fn get_priors(&self) -> Result<Mat>

The array of a priori class probabilities, sorted by the class label value.

fn get_roots(&self) -> Result<Vector<i32>>

Returns indices of root nodes

fn get_nodes(&self) -> Result<Vector<DTrees_Node>>

Returns all the nodes

fn get_splits(&self) -> Result<Vector<DTrees_Split>>

Returns all the splits

fn get_subsets(&self) -> Result<Vector<i32>>

Returns all the bitsets for categorical splits

impl DTreesTraitConst for Ptr<RTrees>

fn as_raw_DTrees(&self) -> *const c_void

fn get_max_categories(&self) -> Result<i32>

Cluster possible values of a categorical variable into K<=maxCategories clusters to find a suboptimal split. If a discrete variable, on which the training procedure tries to make a split, takes more than maxCategories values, the precise best subset estimation may take a very long time because the algorithm is exponential. Instead, many decision trees engines (including our implementation) try to find sub-optimal split in this case by clustering all the samples into maxCategories clusters that is some categories are merged together. The clustering is applied only in n > 2-class classification problems for categorical variables with N > max_categories possible values. In case of regression and 2-class classification the optimal split can be found efficiently without employing clustering, thus the parameter is not used in these cases. Default value is 10.

fn get_max_depth(&self) -> Result<i32>

The maximum possible depth of the tree. That is the training algorithms attempts to split a node while its depth is less than maxDepth. The root node has zero depth. The actual depth may be smaller if the other termination criteria are met (see the outline of the training procedure [ml_intro_trees] “here”), and/or if the tree is pruned. Default value is INT_MAX.

fn get_min_sample_count(&self) -> Result<i32>

If the number of samples in a node is less than this parameter then the node will not be split.

fn get_cv_folds(&self) -> Result<i32>

If CVFolds > 1 then algorithms prunes the built decision tree using K-fold cross-validation procedure where K is equal to CVFolds. Default value is 10.

fn get_use_surrogates(&self) -> Result<bool>

If true then surrogate splits will be built. These splits allow to work with missing data and compute variable importance correctly. Default value is false.

fn get_use1_se_rule(&self) -> Result<bool>

If true then a pruning will be harsher. This will make a tree more compact and more resistant to the training data noise but a bit less accurate. Default value is true.

fn get_truncate_pruned_tree(&self) -> Result<bool>

If true then pruned branches are physically removed from the tree. Otherwise they are retained and it is possible to get results from the original unpruned (or pruned less aggressively) tree. Default value is true.

fn get_regression_accuracy(&self) -> Result<f32>

Termination criteria for regression trees. If all absolute differences between an estimated value in a node and values of train samples in this node are less than this parameter then the node will not be split further. Default value is 0.01f

fn get_priors(&self) -> Result<Mat>

The array of a priori class probabilities, sorted by the class label value.

fn get_roots(&self) -> Result<Vector<i32>>

Returns indices of root nodes

fn get_nodes(&self) -> Result<Vector<DTrees_Node>>

Returns all the nodes

fn get_splits(&self) -> Result<Vector<DTrees_Split>>

Returns all the splits

fn get_subsets(&self) -> Result<Vector<i32>>

Returns all the bitsets for categorical splits

impl DataAugmentationLayerTrait for Ptr<DataAugmentationLayer>

fn as_raw_mut_DataAugmentationLayer(&mut self) -> *mut c_void

impl DataAugmentationLayerTraitConst for Ptr<DataAugmentationLayer>

fn as_raw_DataAugmentationLayer(&self) -> *const c_void

impl DeblurerBaseTrait for Ptr<DeblurerBase>

fn as_raw_mut_DeblurerBase(&mut self) -> *mut c_void

fn set_radius(&mut self, val: i32) -> Result<()>

fn deblur( &mut self, idx: i32, frame: &mut impl MatTrait, range: &impl RangeTraitConst ) -> Result<()>

fn set_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_blurriness_rates(&mut self, val: &Vector<f32>) -> Result<()>

impl DeblurerBaseTrait for Ptr<NullDeblurer>

fn as_raw_mut_DeblurerBase(&mut self) -> *mut c_void

fn set_radius(&mut self, val: i32) -> Result<()>

fn deblur( &mut self, idx: i32, frame: &mut impl MatTrait, range: &impl RangeTraitConst ) -> Result<()>

fn set_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_blurriness_rates(&mut self, val: &Vector<f32>) -> Result<()>

impl DeblurerBaseTrait for Ptr<WeightingDeblurer>

fn as_raw_mut_DeblurerBase(&mut self) -> *mut c_void

fn set_radius(&mut self, val: i32) -> Result<()>

fn deblur( &mut self, idx: i32, frame: &mut impl MatTrait, range: &impl RangeTraitConst ) -> Result<()>

fn set_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_blurriness_rates(&mut self, val: &Vector<f32>) -> Result<()>

impl DeblurerBaseTraitConst for Ptr<DeblurerBase>

fn as_raw_DeblurerBase(&self) -> *const c_void

fn radius(&self) -> Result<i32>

fn frames(&self) -> Result<Vector<Mat>>

fn motions(&self) -> Result<Vector<Mat>>

fn blurriness_rates(&self) -> Result<Vector<f32>>

impl DeblurerBaseTraitConst for Ptr<NullDeblurer>

fn as_raw_DeblurerBase(&self) -> *const c_void

fn radius(&self) -> Result<i32>

fn frames(&self) -> Result<Vector<Mat>>

fn motions(&self) -> Result<Vector<Mat>>

fn blurriness_rates(&self) -> Result<Vector<f32>>

impl DeblurerBaseTraitConst for Ptr<WeightingDeblurer>

fn as_raw_DeblurerBase(&self) -> *const c_void

fn radius(&self) -> Result<i32>

fn frames(&self) -> Result<Vector<Mat>>

fn motions(&self) -> Result<Vector<Mat>>

fn blurriness_rates(&self) -> Result<Vector<f32>>

impl Debug for Ptr<AKAZE>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ANN_MLP>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AbsLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AccumLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AcosLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AcoshLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ActivationLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ActivationLayerInt8>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AdaptiveManifoldFilter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AffineFeature>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AffineFeature2D>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AffineTransformer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AffineWarper>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AgastFeatureDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Algorithm>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AlignExposures>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AlignMTB>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ArgLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ArucoDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AsinLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AsinhLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AtanLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AtanhLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AttentionLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AutotunedIndexParams>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<AverageHash>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BEBLID>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BFMatcher>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BIF>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BNLLLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BRISK>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BackendNode>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BackendWrapper>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BackgroundSubtractor>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BackgroundSubtractorCNT>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BackgroundSubtractorGMG>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BackgroundSubtractorGSOC>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BackgroundSubtractorKNN>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BackgroundSubtractorLSBP>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BackgroundSubtractorMOG>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BackgroundSubtractorMOG2>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BaseCascadeClassifier>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BaseCascadeClassifier_MaskGenerator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BaseConvolutionLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BaseOCR>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BaseSFM>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BasicFaceRecognizer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BatchNormLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BatchNormLayerInt8>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BinaryDescriptor>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BinaryDescriptorMatcher>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BlankLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BlockMeanHash>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Board>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Boost>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BoostDesc>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<BriefDescriptorExtractor>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CLAHE>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_BackgroundSubtractorMOG>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_BackgroundSubtractorMOG2>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_BroxOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_CLAHE>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_CannyEdgeDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_CascadeClassifier>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_CornernessCriteria>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_CornersDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_DenseOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_DensePyrLKOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_DescriptorMatcher>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_DisparityBilateralFilter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_EncoderCallback>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_FarnebackOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_FastFeatureDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_Feature2DAsync>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_HOG>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_HoughCirclesDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_HoughLinesDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_HoughSegmentDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_NvidiaHWOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_NvidiaOpticalFlow_1_0>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_NvidiaOpticalFlow_2_0>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_ORB>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_OpticalFlowDual_TVL1>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_RawVideoSource>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_SparseOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_SparsePyrLKOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_StereoBM>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_StereoBeliefPropagation>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_StereoConstantSpaceBP>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_StereoSGM>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_TemplateMatching>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_VideoReader>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CUDA_VideoWriter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CalibrateCRF>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CalibrateDebevec>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CalibrateRobertson>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CeilLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CeluLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ChannelsPReLULayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CharucoBoard>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CharucoDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ChiHistogramCostExtractor>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ColorAverageInpainter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ColorInpainter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ColorMomentHash>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ColoredKinfu_ColoredKinFu>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ColoredKinfu_Params>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CompareLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CompositeIndexParams>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CompressedRectilinearPortraitWarper>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CompressedRectilinearWarper>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ConcatLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ConjGradSolver>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ConsistentMosaicInpainter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ConstLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ContourFitting>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Convolution>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ConvolutionLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ConvolutionLayerInt8>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CorrelationLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CosLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CoshLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CropAndResizeLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CropLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CumSumLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CustomPattern>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CylindricalWarper>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<CylindricalWarperGpu>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DAISY>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DFT>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DISOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DPMDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DTFilter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DTrees>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DataAugmentationLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DeblurerBase>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DeconvolutionLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DenseOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DensePyrLkOptFlowEstimatorGpu>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DenseRLOFOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DepthCleaner>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DequantizeLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DescriptorMatcher>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_AffineBasedEstimator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_AffineBestOf2NearestMatcher>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_BestOf2NearestMatcher>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_BestOf2NearestRangeMatcher>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_Blender>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_BlocksChannelsCompensator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_BlocksCompensator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_BlocksGainCompensator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_BundleAdjusterAffine>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_BundleAdjusterAffinePartial>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_BundleAdjusterBase>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_BundleAdjusterRay>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_BundleAdjusterReproj>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_ChannelsCompensator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_DpSeamFinder>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_Estimator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_ExposureCompensator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_FeatherBlender>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_FeaturesMatcher>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_GainCompensator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_GraphCutSeamFinder>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_GraphCutSeamFinderBase>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_GraphCutSeamFinderGpu>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_HomographyBasedEstimator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_MultiBandBlender>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_NoBundleAdjuster>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_NoExposureCompensator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_NoSeamFinder>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_PairwiseSeamFinder>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_RotationWarper>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_SeamFinder>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Detail_VoronoiSeamFinder>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DetectionBasedTracker_IDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DetectionOutputLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DetectorParameters>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Dictionary>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DisparityFilter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DisparityWLSFilter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DnnSuperResImpl>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DownhillSolver>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<DualTVL1OpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Dynafu_DynaFu>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ELULayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<EM>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<EMDHistogramCostExtractor>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<EMDL1HistogramCostExtractor>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ERFilter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ERFilter_Callback>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<EdgeAwareInterpolator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<EdgeBoxes>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<EdgeDrawing>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<EigenFaceRecognizer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<EinsumLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<EltwiseLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<EltwiseLayerInt8>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ErfLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<EstimateParameters>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ExpLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ExpandLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FREAK>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FaceDetectorYN>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FaceRecognizer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FaceRecognizerSF>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Facemark>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FacemarkAAM>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FacemarkKazemi>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FacemarkLBF>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FacemarkTrain>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FarnebackOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FastBilateralSolverFilter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FastFeatureDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FastGlobalSmootherFilter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FastICPOdometry>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FastLineDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Feature2D>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FileStorage>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Filter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FisherFaceRecognizer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FisheyeWarper>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FlannBasedMatcher>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FlattenLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FloorLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FlowWarpLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Formatted>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Formatter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FreeType2>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<FromFileMotionReader>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GFTTDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GPCTrainingSamples>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GPCTree>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GRULayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GatherElementsLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GatherLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GaussianMotionFilter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GeluApproximationLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GeluLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GemmLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GeneralizedHough>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GeneralizedHoughBallard>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GeneralizedHoughGuil>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GpuMat_Allocator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GraphSegmentation>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GrayCodePattern>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GrayworldWB>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GridBoard>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<GuidedFilter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<HDF5>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<HardSigmoidLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<HardSwishLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<HarrisLaplaceFeatureDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<HausdorffDistanceExtractor>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<HfsSegment>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<HierarchicalClusteringIndexParams>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<HistogramCostExtractor>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<HistogramPhaseUnwrapping>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ICPOdometry>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<IDenseOptFlowEstimator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<IFrameSource>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ILog>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<IMotionStabilizer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<IOutlierRejector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ISparseOptFlowEstimator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ImageMotionEstimatorBase>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ImgHashBase>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<IndexParams>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<InnerProductLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<InnerProductLayerInt8>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<InpainterBase>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<InpaintingPipeline>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<InstanceNormLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<InterpLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<KAZE>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<KDTreeIndexParams>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<KMeansIndexParams>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<KNearest>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<KeypointBasedMotionEstimator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<KeypointBasedMotionEstimatorGpu>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Kinfu_Detail_PoseGraph>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Kinfu_KinFu>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Kinfu_Params>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Kinfu_Volume>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Kinfu_VolumeParams>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LATCH>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LBPHFaceRecognizer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LMSolver>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LMSolver_Callback>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LRNLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LSDDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LSTMLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LUCID>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LargeKinfu>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Layer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LayerNormLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LearningBasedWB>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LineMod_ColorGradient>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LineMod_DepthNormal>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LineMod_Detector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LineMod_Modality>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LineMod_QuantizedPyramid>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LineSegmentDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LinearIndexParams>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LogLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LogToStdout>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LogisticRegression>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LookUpTable>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LpMotionStabilizer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<LshIndexParams>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MACE>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MCC_CChecker>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MCC_CCheckerDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MCC_CCheckerDraw>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MCC_DetectorParameters>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MSDDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MSER>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MVNLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MarrHildrethHash>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MaskFrameSource>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MatMulLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MaxUnpoolLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MercatorWarper>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MergeDebevec>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MergeExposures>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MergeMertens>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MergeRobertson>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MinProblemSolver>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MinProblemSolver_Function>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MishLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MoreAccurateMotionWobbleSuppressor>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MoreAccurateMotionWobbleSuppressorBase>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MoreAccurateMotionWobbleSuppressorGpu>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MotionEstimatorBase>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MotionEstimatorL1>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MotionEstimatorRansacL2>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MotionFilterBase>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MotionInpainter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MotionSaliency>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MotionSaliencyBinWangApr2014>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<MotionStabilizationPipeline>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<NaryEltwiseLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<NormHistogramCostExtractor>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<NormalBayesClassifier>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<NormalizeBBoxLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<NotLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<NullDeblurer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<NullFrameSource>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<NullInpainter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<NullLog>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<NullOutlierRejector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<NullWobbleSuppressor>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<OCRBeamSearchDecoder>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<OCRBeamSearchDecoder_ClassifierCallback>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<OCRHMMDecoder>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<OCRHMMDecoder_ClassifierCallback>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<OCRHolisticWordRecognizer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<OCRTesseract>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ORB>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Objectness>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ObjectnessBING>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Odometry>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<OdometryFrame>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<OnePassStabilizer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<OpticalFlowPCAFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<OriginalClassName>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PCAPrior>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PCTSignatures>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PCTSignaturesSQFD>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PHash>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PaddingLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PaniniPortraitWarper>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PaniniWarper>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ParamGrid>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Params>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PermuteLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PhaseUnwrapping>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PlaneWarper>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PlaneWarperGpu>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Plot2d>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PoolingLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PoolingLayerInt8>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Pose3D>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PoseCluster3D>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PowerLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PredictCollector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PriorBoxLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ProposalLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<PyrLkOptFlowEstimatorBase>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<QRCodeEncoder>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<QualityBRISQUE>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<QualityBase>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<QualityGMSD>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<QualityMSE>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<QualityPSNR>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<QualitySSIM>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<QuantizeLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<QuasiDenseStereo>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RFFeatureGetter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RICInterpolator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RLOFOpticalFlowParameter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RNNLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RTrees>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RadialVarianceHash>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Rapid_GOSTracker>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Rapid_OLSTracker>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Rapid_Rapid>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Rapid_Tracker>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ReLU6Layer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ReLULayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ReciprocalLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ReduceLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RegionLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ReorgLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RequantizeLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ReshapeLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ResizeLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Retina>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RetinaFastToneMapping>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RgbdFrame>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RgbdICPOdometry>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RgbdNormals>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RgbdOdometry>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RgbdPlane>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RidgeDetectionFilter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<RoundLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SFMLibmvEuclideanReconstruction>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SIFT>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SURF>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SURF_CUDA>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SVM>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SVMSGD>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SVM_Kernel>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Saliency>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SavedIndexParams>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ScaleLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ScaleLayerInt8>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ScanSegment>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ScatterLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ScatterNDLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SearchParams>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SelectiveSearchSegmentation>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SelectiveSearchSegmentationStrategy>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SelectiveSearchSegmentationStrategyColor>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SelectiveSearchSegmentationStrategyFill>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SelectiveSearchSegmentationStrategyMultiple>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SelectiveSearchSegmentationStrategySize>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SelectiveSearchSegmentationStrategyTexture>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SeluLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ShapeContextDistanceExtractor>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ShapeDistanceExtractor>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ShapeTransformer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ShiftLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ShiftLayerInt8>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ShrinkLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ShuffleChannelLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SigmoidLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SignLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SimpleBlobDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SimpleWB>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SinLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SinhLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SinusoidalPattern>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SinusoidalPattern_Params>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SliceLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SoftmaxLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SoftmaxLayerInt8>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SoftplusLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SoftsignLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SparseMatchInterpolator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SparseOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SparsePyrLKOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SparsePyrLkOptFlowEstimator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SparsePyrLkOptFlowEstimatorGpu>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SparseRLOFOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SphericalWarper>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SphericalWarperGpu>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SplitLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SqrtLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<StabilizerBase>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<StandardCollector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<StarDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<StatModel>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<StaticSaliency>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<StaticSaliencyFineGrained>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<StaticSaliencySpectralResidual>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<StereoBM>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<StereoMatcher>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<StereoSGBM>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<StereographicWarper>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Stitcher>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<StructuredEdgeDetection>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<StructuredLightPattern>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SuperRes_BroxOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SuperRes_DenseOpticalFlowExt>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SuperRes_DualTVL1OpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SuperRes_FarnebackOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SuperRes_FrameSource>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SuperRes_PyrLKOpticalFlow>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SuperRes_SuperResolution>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SuperpixelLSC>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SuperpixelSEEDS>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SuperpixelSLIC>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SwishLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<SyntheticSequenceGenerator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TBMR>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TEBLID>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TanHLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TanLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TextDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TextDetectorCNN>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ThinPlateSplineShapeTransformer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ThresholdedReluLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TileLayer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<ToFileMotionWriter>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Tonemap>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TonemapDrago>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TonemapDurand>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TonemapMantiuk>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TonemapReinhard>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<Tracker>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TrackerCSRT>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TrackerDaSiamRPN>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TrackerGOTURN>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TrackerKCF>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TrackerMIL>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TrackerNano>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TrackerVit>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TrainData>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TransientAreasSegmentationModule>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TranslationBasedLocalOutlierRejector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TransverseMercatorWarper>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<TwoPassStabilizer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<VGG>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<VariationalRefinement>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<VideoFileSource>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<WBDetector>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<WarperCreator>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<WeightingDeblurer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<WhiteBalancer>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<WindowScene>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<WobbleSuppressorBase>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Debug for Ptr<f32>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl DeconvolutionLayerTrait for Ptr<DeconvolutionLayer>

fn as_raw_mut_DeconvolutionLayer(&mut self) -> *mut c_void

impl DeconvolutionLayerTraitConst for Ptr<DeconvolutionLayer>

fn as_raw_DeconvolutionLayer(&self) -> *const c_void

impl Default for Ptr<f32>

fn default() -> Self

Returns the “default value” for a type.

impl DenseOpticalFlowTrait for Ptr<DISOpticalFlow>

fn as_raw_mut_DenseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates an optical flow.

fn collect_garbage(&mut self) -> Result<()>

Releases all inner buffers.

impl DenseOpticalFlowTrait for Ptr<DenseOpticalFlow>

fn as_raw_mut_DenseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates an optical flow.

fn collect_garbage(&mut self) -> Result<()>

Releases all inner buffers.

impl DenseOpticalFlowTrait for Ptr<DenseRLOFOpticalFlow>

fn as_raw_mut_DenseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates an optical flow.

fn collect_garbage(&mut self) -> Result<()>

Releases all inner buffers.

impl DenseOpticalFlowTrait for Ptr<DualTVL1OpticalFlow>

fn as_raw_mut_DenseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates an optical flow.

fn collect_garbage(&mut self) -> Result<()>

Releases all inner buffers.

impl DenseOpticalFlowTrait for Ptr<FarnebackOpticalFlow>

fn as_raw_mut_DenseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates an optical flow.

fn collect_garbage(&mut self) -> Result<()>

Releases all inner buffers.

impl DenseOpticalFlowTrait for Ptr<OpticalFlowPCAFlow>

fn as_raw_mut_DenseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates an optical flow.

fn collect_garbage(&mut self) -> Result<()>

Releases all inner buffers.

impl DenseOpticalFlowTrait for Ptr<VariationalRefinement>

fn as_raw_mut_DenseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates an optical flow.

fn collect_garbage(&mut self) -> Result<()>

Releases all inner buffers.

impl DenseOpticalFlowTraitConst for Ptr<DISOpticalFlow>

fn as_raw_DenseOpticalFlow(&self) -> *const c_void

impl DenseOpticalFlowTraitConst for Ptr<DenseOpticalFlow>

fn as_raw_DenseOpticalFlow(&self) -> *const c_void

impl DenseOpticalFlowTraitConst for Ptr<DenseRLOFOpticalFlow>

fn as_raw_DenseOpticalFlow(&self) -> *const c_void

impl DenseOpticalFlowTraitConst for Ptr<DualTVL1OpticalFlow>

fn as_raw_DenseOpticalFlow(&self) -> *const c_void

impl DenseOpticalFlowTraitConst for Ptr<FarnebackOpticalFlow>

fn as_raw_DenseOpticalFlow(&self) -> *const c_void

impl DenseOpticalFlowTraitConst for Ptr<OpticalFlowPCAFlow>

fn as_raw_DenseOpticalFlow(&self) -> *const c_void

impl DenseOpticalFlowTraitConst for Ptr<VariationalRefinement>

fn as_raw_DenseOpticalFlow(&self) -> *const c_void

impl DensePyrLkOptFlowEstimatorGpuTrait for Ptr<DensePyrLkOptFlowEstimatorGpu>

fn as_raw_mut_DensePyrLkOptFlowEstimatorGpu(&mut self) -> *mut c_void

fn run( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, flow_x: &mut impl ToInputOutputArray, flow_y: &mut impl ToInputOutputArray, errors: &mut impl ToOutputArray ) -> Result<()>

impl DensePyrLkOptFlowEstimatorGpuTraitConst for Ptr<DensePyrLkOptFlowEstimatorGpu>

fn as_raw_DensePyrLkOptFlowEstimatorGpu(&self) -> *const c_void

impl DenseRLOFOpticalFlowTrait for Ptr<DenseRLOFOpticalFlow>

fn as_raw_mut_DenseRLOFOpticalFlow(&mut self) -> *mut c_void

fn set_rlof_optical_flow_parameter( &mut self, val: Ptr<RLOFOpticalFlowParameter> ) -> Result<()>

Configuration of the RLOF alogrithm.

fn set_forward_backward(&mut self, val: f32) -> Result<()>

Threshold for the forward backward confidence check For each grid point inline formula a motion vector inline formula is computed. * If the forward backward error block formula * is larger than threshold given by this function then the motion vector will not be used by the following * vector field interpolation. inline formula denotes the backward flow. Note, the forward backward test * will only be applied if the threshold > 0. This may results into a doubled runtime for the motion estimation. * see also: getForwardBackward, setGridStep

fn set_grid_step(&mut self, val: Size) -> Result<()>

Size of the grid to spawn the motion vectors. For each grid point a motion vector is computed. Some motion vectors will be removed due to the forwatd backward * threshold (if set >0). The rest will be the base of the vector field interpolation. * getForwardBackward, setGridStep

fn set_interpolation(&mut self, val: InterpolationType) -> Result<()>

Interpolation used to compute the dense optical flow. Two interpolation algorithms are supported * - INTERP_GEO applies the fast geodesic interpolation, see Geistert2016. * - INTERP_EPIC_RESIDUAL applies the edge-preserving interpolation, see Revaud2015,Geistert2016. * see also: ximgproc::EdgeAwareInterpolator, getInterpolation

fn set_epick(&mut self, val: i32) -> Result<()>

see ximgproc::EdgeAwareInterpolator() K value. K is a number of nearest-neighbor matches considered, when fitting a locally affine * model. Usually it should be around 128. However, lower values would make the interpolation noticeably faster. * ximgproc::EdgeAwareInterpolator, setEPICK

fn set_epic_sigma(&mut self, val: f32) -> Result<()>

see ximgproc::EdgeAwareInterpolator() sigma value. Sigma is a parameter defining how fast the weights decrease in the locally-weighted affine * fitting. Higher values can help preserve fine details, lower values can help to get rid of noise in the * output flow. * ximgproc::EdgeAwareInterpolator, setEPICSigma

fn set_epic_lambda(&mut self, val: f32) -> Result<()>

see ximgproc::EdgeAwareInterpolator() lambda value. Lambda is a parameter defining the weight of the edge-aware term in geodesic distance, * should be in the range of 0 to 1000. * ximgproc::EdgeAwareInterpolator, setEPICSigma

fn set_fgs_lambda(&mut self, val: f32) -> Result<()>

see ximgproc::EdgeAwareInterpolator(). Sets the respective fastGlobalSmootherFilter() parameter. * ximgproc::EdgeAwareInterpolator, setFgsLambda

fn set_fgs_sigma(&mut self, val: f32) -> Result<()>

see ximgproc::EdgeAwareInterpolator(). Sets the respective fastGlobalSmootherFilter() parameter. * ximgproc::EdgeAwareInterpolator, ximgproc::fastGlobalSmootherFilter, setFgsSigma

fn set_use_post_proc(&mut self, val: bool) -> Result<()>

enables ximgproc::fastGlobalSmootherFilter

fn set_use_variational_refinement(&mut self, val: bool) -> Result<()>

enables VariationalRefinement

fn set_ricsp_size(&mut self, val: i32) -> Result<()>

Parameter to tune the approximate size of the superpixel used for oversegmentation.

fn set_ricslic_type(&mut self, val: i32) -> Result<()>

Parameter to choose superpixel algorithm variant to use:

impl DenseRLOFOpticalFlowTraitConst for Ptr<DenseRLOFOpticalFlow>

fn as_raw_DenseRLOFOpticalFlow(&self) -> *const c_void

fn get_rlof_optical_flow_parameter( &self ) -> Result<Ptr<RLOFOpticalFlowParameter>>

Configuration of the RLOF alogrithm.

fn get_forward_backward(&self) -> Result<f32>

Threshold for the forward backward confidence check For each grid point inline formula a motion vector inline formula is computed. * If the forward backward error block formula * is larger than threshold given by this function then the motion vector will not be used by the following * vector field interpolation. inline formula denotes the backward flow. Note, the forward backward test * will only be applied if the threshold > 0. This may results into a doubled runtime for the motion estimation. * getForwardBackward, setGridStep

fn get_grid_step(&self) -> Result<Size>

Size of the grid to spawn the motion vectors. For each grid point a motion vector is computed. Some motion vectors will be removed due to the forwatd backward * threshold (if set >0). The rest will be the base of the vector field interpolation. * see also: getForwardBackward, setGridStep

fn get_interpolation(&self) -> Result<InterpolationType>

Interpolation used to compute the dense optical flow. Two interpolation algorithms are supported * - INTERP_GEO applies the fast geodesic interpolation, see Geistert2016. * - INTERP_EPIC_RESIDUAL applies the edge-preserving interpolation, see Revaud2015,Geistert2016. * ximgproc::EdgeAwareInterpolator, getInterpolation

fn get_epick(&self) -> Result<i32>

see ximgproc::EdgeAwareInterpolator() K value. K is a number of nearest-neighbor matches considered, when fitting a locally affine * model. Usually it should be around 128. However, lower values would make the interpolation noticeably faster. * see also: ximgproc::EdgeAwareInterpolator, setEPICK

fn get_epic_sigma(&self) -> Result<f32>

see ximgproc::EdgeAwareInterpolator() sigma value. Sigma is a parameter defining how fast the weights decrease in the locally-weighted affine * fitting. Higher values can help preserve fine details, lower values can help to get rid of noise in the * output flow. * see also: ximgproc::EdgeAwareInterpolator, setEPICSigma

fn get_epic_lambda(&self) -> Result<f32>

see ximgproc::EdgeAwareInterpolator() lambda value. Lambda is a parameter defining the weight of the edge-aware term in geodesic distance, * should be in the range of 0 to 1000. * see also: ximgproc::EdgeAwareInterpolator, setEPICSigma

fn get_fgs_lambda(&self) -> Result<f32>

see ximgproc::EdgeAwareInterpolator(). Sets the respective fastGlobalSmootherFilter() parameter. * see also: ximgproc::EdgeAwareInterpolator, setFgsLambda

fn get_fgs_sigma(&self) -> Result<f32>

see ximgproc::EdgeAwareInterpolator(). Sets the respective fastGlobalSmootherFilter() parameter. * see also: ximgproc::EdgeAwareInterpolator, ximgproc::fastGlobalSmootherFilter, setFgsSigma

fn get_use_post_proc(&self) -> Result<bool>

enables ximgproc::fastGlobalSmootherFilter

fn get_use_variational_refinement(&self) -> Result<bool>

enables VariationalRefinement

fn get_ricsp_size(&self) -> Result<i32>

Parameter to tune the approximate size of the superpixel used for oversegmentation.

fn get_ricslic_type(&self) -> Result<i32>

Parameter to choose superpixel algorithm variant to use:

impl DepthCleanerTrait for Ptr<DepthCleaner>

fn as_raw_mut_DepthCleaner(&mut self) -> *mut c_void

fn set_window_size(&mut self, val: i32) -> Result<()>

fn set_depth(&mut self, val: i32) -> Result<()>

fn set_method(&mut self, val: i32) -> Result<()>

impl DepthCleanerTraitConst for Ptr<DepthCleaner>

fn as_raw_DepthCleaner(&self) -> *const c_void

fn apply( &self, points: &impl ToInputArray, depth: &mut impl ToOutputArray ) -> Result<()>

Given a set of 3d points in a depth image, compute the normals at each point.

fn initialize(&self) -> Result<()>

Initializes some data that is cached for later computation If that function is not called, it will be called the first time normals are computed

fn get_window_size(&self) -> Result<i32>

fn get_depth(&self) -> Result<i32>

fn get_method(&self) -> Result<i32>

impl DequantizeLayerTrait for Ptr<DequantizeLayer>

fn as_raw_mut_DequantizeLayer(&mut self) -> *mut c_void

fn set_scales(&mut self, val: Vector<f32>)

fn set_zeropoints(&mut self, val: Vector<i32>)

impl DequantizeLayerTraitConst for Ptr<DequantizeLayer>

fn as_raw_DequantizeLayer(&self) -> *const c_void

fn scales(&self) -> Vector<f32>

fn zeropoints(&self) -> Vector<i32>

impl Deref for Ptr<f32>

type Target = f32

The resulting type after dereferencing.

fn deref(&self) -> &Self::Target

Dereferences the value.

impl DerefMut for Ptr<f32>

fn deref_mut(&mut self) -> &mut Self::Target

Mutably dereferences the value.

impl DescriptorMatcherTrait for Ptr<BFMatcher>

fn as_raw_mut_DescriptorMatcher(&mut self) -> *mut c_void

fn add(&mut self, descriptors: &impl ToInputArray) -> Result<()>

Adds descriptors to train a CPU(trainDescCollectionis) or GPU(utrainDescCollectionis) descriptor collection.

fn clear(&mut self) -> Result<()>

Clears the train descriptor collections.

fn train(&mut self) -> Result<()>

Trains a descriptor matcher

fn match_( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch>, masks: &impl ToInputArray ) -> Result<()>

Finds the best match for each descriptor from a query set.

fn match__def( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch> ) -> Result<()>

@overload

fn knn_match( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32, masks: &impl ToInputArray, compact_result: bool ) -> Result<()>

Finds the k best matches for each descriptor from a query set.

fn knn_match_def( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32 ) -> Result<()>

@overload

fn radius_match( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32, masks: &impl ToInputArray, compact_result: bool ) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance.

fn radius_match_def( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32 ) -> Result<()>

@overload

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl DescriptorMatcherTrait for Ptr<DescriptorMatcher>

fn as_raw_mut_DescriptorMatcher(&mut self) -> *mut c_void

fn add(&mut self, descriptors: &impl ToInputArray) -> Result<()>

Adds descriptors to train a CPU(trainDescCollectionis) or GPU(utrainDescCollectionis) descriptor collection.

fn clear(&mut self) -> Result<()>

Clears the train descriptor collections.

fn train(&mut self) -> Result<()>

Trains a descriptor matcher

fn match_( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch>, masks: &impl ToInputArray ) -> Result<()>

Finds the best match for each descriptor from a query set.

fn match__def( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch> ) -> Result<()>

@overload

fn knn_match( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32, masks: &impl ToInputArray, compact_result: bool ) -> Result<()>

Finds the k best matches for each descriptor from a query set.

fn knn_match_def( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32 ) -> Result<()>

@overload

fn radius_match( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32, masks: &impl ToInputArray, compact_result: bool ) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance.

fn radius_match_def( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32 ) -> Result<()>

@overload

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl DescriptorMatcherTrait for Ptr<FlannBasedMatcher>

fn as_raw_mut_DescriptorMatcher(&mut self) -> *mut c_void

fn add(&mut self, descriptors: &impl ToInputArray) -> Result<()>

Adds descriptors to train a CPU(trainDescCollectionis) or GPU(utrainDescCollectionis) descriptor collection.

fn clear(&mut self) -> Result<()>

Clears the train descriptor collections.

fn train(&mut self) -> Result<()>

Trains a descriptor matcher

fn match_( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch>, masks: &impl ToInputArray ) -> Result<()>

Finds the best match for each descriptor from a query set.

fn match__def( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch> ) -> Result<()>

@overload

fn knn_match( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32, masks: &impl ToInputArray, compact_result: bool ) -> Result<()>

Finds the k best matches for each descriptor from a query set.

fn knn_match_def( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32 ) -> Result<()>

@overload

fn radius_match( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32, masks: &impl ToInputArray, compact_result: bool ) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance.

fn radius_match_def( &mut self, query_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32 ) -> Result<()>

@overload

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl DescriptorMatcherTraitConst for Ptr<BFMatcher>

fn as_raw_DescriptorMatcher(&self) -> *const c_void

fn get_train_descriptors(&self) -> Result<Vector<Mat>>

Returns a constant link to the train descriptor collection trainDescCollection .

fn empty(&self) -> Result<bool>

Returns true if there are no train descriptors in the both collections.

fn is_mask_supported(&self) -> Result<bool>

Returns true if the descriptor matcher supports masking permissible matches.

fn train_match( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch>, mask: &impl ToInputArray ) -> Result<()>

Finds the best match for each descriptor from a query set.

fn train_match_def( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch> ) -> Result<()>

Finds the best match for each descriptor from a query set.

fn knn_train_match( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32, mask: &impl ToInputArray, compact_result: bool ) -> Result<()>

Finds the k best matches for each descriptor from a query set.

fn knn_train_match_def( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32 ) -> Result<()>

Finds the k best matches for each descriptor from a query set.

fn radius_train_match( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32, mask: &impl ToInputArray, compact_result: bool ) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance.

fn radius_train_match_def( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32 ) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance.

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn clone(&self, empty_train_data: bool) -> Result<Ptr<DescriptorMatcher>>

Clones the matcher.

fn clone_def(&self) -> Result<Ptr<DescriptorMatcher>>

Clones the matcher.

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl DescriptorMatcherTraitConst for Ptr<DescriptorMatcher>

fn as_raw_DescriptorMatcher(&self) -> *const c_void

fn get_train_descriptors(&self) -> Result<Vector<Mat>>

Returns a constant link to the train descriptor collection trainDescCollection .

fn empty(&self) -> Result<bool>

Returns true if there are no train descriptors in the both collections.

fn is_mask_supported(&self) -> Result<bool>

Returns true if the descriptor matcher supports masking permissible matches.

fn train_match( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch>, mask: &impl ToInputArray ) -> Result<()>

Finds the best match for each descriptor from a query set.

fn train_match_def( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch> ) -> Result<()>

Finds the best match for each descriptor from a query set.

fn knn_train_match( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32, mask: &impl ToInputArray, compact_result: bool ) -> Result<()>

Finds the k best matches for each descriptor from a query set.

fn knn_train_match_def( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32 ) -> Result<()>

Finds the k best matches for each descriptor from a query set.

fn radius_train_match( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32, mask: &impl ToInputArray, compact_result: bool ) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance.

fn radius_train_match_def( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32 ) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance.

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn clone(&self, empty_train_data: bool) -> Result<Ptr<DescriptorMatcher>>

Clones the matcher.

fn clone_def(&self) -> Result<Ptr<DescriptorMatcher>>

Clones the matcher.

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl DescriptorMatcherTraitConst for Ptr<FlannBasedMatcher>

fn as_raw_DescriptorMatcher(&self) -> *const c_void

fn get_train_descriptors(&self) -> Result<Vector<Mat>>

Returns a constant link to the train descriptor collection trainDescCollection .

fn empty(&self) -> Result<bool>

Returns true if there are no train descriptors in the both collections.

fn is_mask_supported(&self) -> Result<bool>

Returns true if the descriptor matcher supports masking permissible matches.

fn train_match( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch>, mask: &impl ToInputArray ) -> Result<()>

Finds the best match for each descriptor from a query set.

fn train_match_def( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<DMatch> ) -> Result<()>

Finds the best match for each descriptor from a query set.

fn knn_train_match( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32, mask: &impl ToInputArray, compact_result: bool ) -> Result<()>

Finds the k best matches for each descriptor from a query set.

fn knn_train_match_def( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, k: i32 ) -> Result<()>

Finds the k best matches for each descriptor from a query set.

fn radius_train_match( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32, mask: &impl ToInputArray, compact_result: bool ) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance.

fn radius_train_match_def( &self, query_descriptors: &impl ToInputArray, train_descriptors: &impl ToInputArray, matches: &mut Vector<Vector<DMatch>>, max_distance: f32 ) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance.

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn clone(&self, empty_train_data: bool) -> Result<Ptr<DescriptorMatcher>>

Clones the matcher.

fn clone_def(&self) -> Result<Ptr<DescriptorMatcher>>

Clones the matcher.

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Detail_AffineBasedEstimatorTrait for Ptr<Detail_AffineBasedEstimator>

fn as_raw_mut_Detail_AffineBasedEstimator(&mut self) -> *mut c_void

impl Detail_AffineBasedEstimatorTraitConst for Ptr<Detail_AffineBasedEstimator>

fn as_raw_Detail_AffineBasedEstimator(&self) -> *const c_void

impl Detail_AffineBestOf2NearestMatcherTrait for Ptr<Detail_AffineBestOf2NearestMatcher>

fn as_raw_mut_Detail_AffineBestOf2NearestMatcher(&mut self) -> *mut c_void

impl Detail_AffineBestOf2NearestMatcherTraitConst for Ptr<Detail_AffineBestOf2NearestMatcher>

fn as_raw_Detail_AffineBestOf2NearestMatcher(&self) -> *const c_void

impl Detail_BestOf2NearestMatcherTrait for Ptr<Detail_AffineBestOf2NearestMatcher>

fn as_raw_mut_Detail_BestOf2NearestMatcher(&mut self) -> *mut c_void

fn collect_garbage(&mut self) -> Result<()>

impl Detail_BestOf2NearestMatcherTrait for Ptr<Detail_BestOf2NearestMatcher>

fn as_raw_mut_Detail_BestOf2NearestMatcher(&mut self) -> *mut c_void

fn collect_garbage(&mut self) -> Result<()>

impl Detail_BestOf2NearestMatcherTrait for Ptr<Detail_BestOf2NearestRangeMatcher>

fn as_raw_mut_Detail_BestOf2NearestMatcher(&mut self) -> *mut c_void

fn collect_garbage(&mut self) -> Result<()>

impl Detail_BestOf2NearestMatcherTraitConst for Ptr<Detail_AffineBestOf2NearestMatcher>

fn as_raw_Detail_BestOf2NearestMatcher(&self) -> *const c_void

impl Detail_BestOf2NearestMatcherTraitConst for Ptr<Detail_BestOf2NearestMatcher>

fn as_raw_Detail_BestOf2NearestMatcher(&self) -> *const c_void

impl Detail_BestOf2NearestMatcherTraitConst for Ptr<Detail_BestOf2NearestRangeMatcher>

fn as_raw_Detail_BestOf2NearestMatcher(&self) -> *const c_void

impl Detail_BestOf2NearestRangeMatcherTrait for Ptr<Detail_BestOf2NearestRangeMatcher>

fn as_raw_mut_Detail_BestOf2NearestRangeMatcher(&mut self) -> *mut c_void

impl Detail_BestOf2NearestRangeMatcherTraitConst for Ptr<Detail_BestOf2NearestRangeMatcher>

fn as_raw_Detail_BestOf2NearestRangeMatcher(&self) -> *const c_void

impl Detail_BlenderTrait for Ptr<Detail_Blender>

fn as_raw_mut_Detail_Blender(&mut self) -> *mut c_void

fn prepare( &mut self, corners: &Vector<Point>, sizes: &Vector<Size> ) -> Result<()>

Prepares the blender for blending.

fn prepare_1(&mut self, dst_roi: Rect) -> Result<()>

Prepares the blender for blending.

fn feed( &mut self, img: &impl ToInputArray, mask: &impl ToInputArray, tl: Point ) -> Result<()>

Processes the image.

fn blend( &mut self, dst: &mut impl ToInputOutputArray, dst_mask: &mut impl ToInputOutputArray ) -> Result<()>

Blends and returns the final pano.

impl Detail_BlenderTrait for Ptr<Detail_FeatherBlender>

fn as_raw_mut_Detail_Blender(&mut self) -> *mut c_void

fn prepare( &mut self, corners: &Vector<Point>, sizes: &Vector<Size> ) -> Result<()>

Prepares the blender for blending.

fn prepare_1(&mut self, dst_roi: Rect) -> Result<()>

Prepares the blender for blending.

fn feed( &mut self, img: &impl ToInputArray, mask: &impl ToInputArray, tl: Point ) -> Result<()>

Processes the image.

fn blend( &mut self, dst: &mut impl ToInputOutputArray, dst_mask: &mut impl ToInputOutputArray ) -> Result<()>

Blends and returns the final pano.

impl Detail_BlenderTrait for Ptr<Detail_MultiBandBlender>

fn as_raw_mut_Detail_Blender(&mut self) -> *mut c_void

fn prepare( &mut self, corners: &Vector<Point>, sizes: &Vector<Size> ) -> Result<()>

Prepares the blender for blending.

fn prepare_1(&mut self, dst_roi: Rect) -> Result<()>

Prepares the blender for blending.

fn feed( &mut self, img: &impl ToInputArray, mask: &impl ToInputArray, tl: Point ) -> Result<()>

Processes the image.

fn blend( &mut self, dst: &mut impl ToInputOutputArray, dst_mask: &mut impl ToInputOutputArray ) -> Result<()>

Blends and returns the final pano.

impl Detail_BlenderTraitConst for Ptr<Detail_Blender>

fn as_raw_Detail_Blender(&self) -> *const c_void

impl Detail_BlenderTraitConst for Ptr<Detail_FeatherBlender>

fn as_raw_Detail_Blender(&self) -> *const c_void

impl Detail_BlenderTraitConst for Ptr<Detail_MultiBandBlender>

fn as_raw_Detail_Blender(&self) -> *const c_void

impl Detail_BlocksChannelsCompensatorTrait for Ptr<Detail_BlocksChannelsCompensator>

fn as_raw_mut_Detail_BlocksChannelsCompensator(&mut self) -> *mut c_void

fn feed( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<Tuple<(UMat, u8)>> ) -> Result<()>

impl Detail_BlocksChannelsCompensatorTraitConst for Ptr<Detail_BlocksChannelsCompensator>

fn as_raw_Detail_BlocksChannelsCompensator(&self) -> *const c_void

impl Detail_BlocksCompensatorTrait for Ptr<Detail_BlocksChannelsCompensator>

fn as_raw_mut_Detail_BlocksCompensator(&mut self) -> *mut c_void

fn apply( &mut self, index: i32, corner: Point, image: &mut impl ToInputOutputArray, mask: &impl ToInputArray ) -> Result<()>

fn get_mat_gains(&mut self, umv: &mut Vector<Mat>) -> Result<()>

fn set_mat_gains(&mut self, umv: &mut Vector<Mat>) -> Result<()>

fn set_nr_feeds(&mut self, nr_feeds: i32) -> Result<()>

fn get_nr_feeds(&mut self) -> Result<i32>

fn set_similarity_threshold(&mut self, similarity_threshold: f64) -> Result<()>

fn set_block_size(&mut self, width: i32, height: i32) -> Result<()>

fn set_block_size_1(&mut self, size: Size) -> Result<()>

fn set_nr_gains_filtering_iterations( &mut self, nr_iterations: i32 ) -> Result<()>

impl Detail_BlocksCompensatorTrait for Ptr<Detail_BlocksCompensator>

fn as_raw_mut_Detail_BlocksCompensator(&mut self) -> *mut c_void

fn apply( &mut self, index: i32, corner: Point, image: &mut impl ToInputOutputArray, mask: &impl ToInputArray ) -> Result<()>

fn get_mat_gains(&mut self, umv: &mut Vector<Mat>) -> Result<()>

fn set_mat_gains(&mut self, umv: &mut Vector<Mat>) -> Result<()>

fn set_nr_feeds(&mut self, nr_feeds: i32) -> Result<()>

fn get_nr_feeds(&mut self) -> Result<i32>

fn set_similarity_threshold(&mut self, similarity_threshold: f64) -> Result<()>

fn set_block_size(&mut self, width: i32, height: i32) -> Result<()>

fn set_block_size_1(&mut self, size: Size) -> Result<()>

fn set_nr_gains_filtering_iterations( &mut self, nr_iterations: i32 ) -> Result<()>

impl Detail_BlocksCompensatorTrait for Ptr<Detail_BlocksGainCompensator>

fn as_raw_mut_Detail_BlocksCompensator(&mut self) -> *mut c_void

fn apply( &mut self, index: i32, corner: Point, image: &mut impl ToInputOutputArray, mask: &impl ToInputArray ) -> Result<()>

fn get_mat_gains(&mut self, umv: &mut Vector<Mat>) -> Result<()>

fn set_mat_gains(&mut self, umv: &mut Vector<Mat>) -> Result<()>

fn set_nr_feeds(&mut self, nr_feeds: i32) -> Result<()>

fn get_nr_feeds(&mut self) -> Result<i32>

fn set_similarity_threshold(&mut self, similarity_threshold: f64) -> Result<()>

fn set_block_size(&mut self, width: i32, height: i32) -> Result<()>

fn set_block_size_1(&mut self, size: Size) -> Result<()>

fn set_nr_gains_filtering_iterations( &mut self, nr_iterations: i32 ) -> Result<()>

impl Detail_BlocksCompensatorTraitConst for Ptr<Detail_BlocksChannelsCompensator>

fn as_raw_Detail_BlocksCompensator(&self) -> *const c_void

fn get_similarity_threshold(&self) -> Result<f64>

fn get_block_size(&self) -> Result<Size>

fn get_nr_gains_filtering_iterations(&self) -> Result<i32>

impl Detail_BlocksCompensatorTraitConst for Ptr<Detail_BlocksCompensator>

fn as_raw_Detail_BlocksCompensator(&self) -> *const c_void

fn get_similarity_threshold(&self) -> Result<f64>

fn get_block_size(&self) -> Result<Size>

fn get_nr_gains_filtering_iterations(&self) -> Result<i32>

impl Detail_BlocksCompensatorTraitConst for Ptr<Detail_BlocksGainCompensator>

fn as_raw_Detail_BlocksCompensator(&self) -> *const c_void

fn get_similarity_threshold(&self) -> Result<f64>

fn get_block_size(&self) -> Result<Size>

fn get_nr_gains_filtering_iterations(&self) -> Result<i32>

impl Detail_BlocksGainCompensatorTrait for Ptr<Detail_BlocksGainCompensator>

fn as_raw_mut_Detail_BlocksGainCompensator(&mut self) -> *mut c_void

fn feed( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<Tuple<(UMat, u8)>> ) -> Result<()>

fn apply( &mut self, index: i32, corner: Point, image: &mut impl ToInputOutputArray, mask: &impl ToInputArray ) -> Result<()>

fn get_mat_gains(&mut self, umv: &mut Vector<Mat>) -> Result<()>

fn set_mat_gains(&mut self, umv: &mut Vector<Mat>) -> Result<()>

impl Detail_BlocksGainCompensatorTraitConst for Ptr<Detail_BlocksGainCompensator>

fn as_raw_Detail_BlocksGainCompensator(&self) -> *const c_void

impl Detail_BundleAdjusterAffinePartialTrait for Ptr<Detail_BundleAdjusterAffinePartial>

fn as_raw_mut_Detail_BundleAdjusterAffinePartial(&mut self) -> *mut c_void

impl Detail_BundleAdjusterAffinePartialTraitConst for Ptr<Detail_BundleAdjusterAffinePartial>

fn as_raw_Detail_BundleAdjusterAffinePartial(&self) -> *const c_void

impl Detail_BundleAdjusterAffineTrait for Ptr<Detail_BundleAdjusterAffine>

fn as_raw_mut_Detail_BundleAdjusterAffine(&mut self) -> *mut c_void

impl Detail_BundleAdjusterAffineTraitConst for Ptr<Detail_BundleAdjusterAffine>

fn as_raw_Detail_BundleAdjusterAffine(&self) -> *const c_void

impl Detail_BundleAdjusterBaseTrait for Ptr<Detail_BundleAdjusterAffine>

fn as_raw_mut_Detail_BundleAdjusterBase(&mut self) -> *mut c_void

fn set_refinement_mask(&mut self, mask: &impl MatTraitConst) -> Result<()>

fn set_conf_thresh(&mut self, conf_thresh: f64) -> Result<()>

fn term_criteria(&mut self) -> Result<TermCriteria>

fn set_term_criteria(&mut self, term_criteria: TermCriteria) -> Result<()>

impl Detail_BundleAdjusterBaseTrait for Ptr<Detail_BundleAdjusterAffinePartial>

fn as_raw_mut_Detail_BundleAdjusterBase(&mut self) -> *mut c_void

fn set_refinement_mask(&mut self, mask: &impl MatTraitConst) -> Result<()>

fn set_conf_thresh(&mut self, conf_thresh: f64) -> Result<()>

fn term_criteria(&mut self) -> Result<TermCriteria>

fn set_term_criteria(&mut self, term_criteria: TermCriteria) -> Result<()>

impl Detail_BundleAdjusterBaseTrait for Ptr<Detail_BundleAdjusterBase>

fn as_raw_mut_Detail_BundleAdjusterBase(&mut self) -> *mut c_void

fn set_refinement_mask(&mut self, mask: &impl MatTraitConst) -> Result<()>

fn set_conf_thresh(&mut self, conf_thresh: f64) -> Result<()>

fn term_criteria(&mut self) -> Result<TermCriteria>

fn set_term_criteria(&mut self, term_criteria: TermCriteria) -> Result<()>

impl Detail_BundleAdjusterBaseTrait for Ptr<Detail_BundleAdjusterRay>

fn as_raw_mut_Detail_BundleAdjusterBase(&mut self) -> *mut c_void

fn set_refinement_mask(&mut self, mask: &impl MatTraitConst) -> Result<()>

fn set_conf_thresh(&mut self, conf_thresh: f64) -> Result<()>

fn term_criteria(&mut self) -> Result<TermCriteria>

fn set_term_criteria(&mut self, term_criteria: TermCriteria) -> Result<()>

impl Detail_BundleAdjusterBaseTrait for Ptr<Detail_BundleAdjusterReproj>

fn as_raw_mut_Detail_BundleAdjusterBase(&mut self) -> *mut c_void

fn set_refinement_mask(&mut self, mask: &impl MatTraitConst) -> Result<()>

fn set_conf_thresh(&mut self, conf_thresh: f64) -> Result<()>

fn term_criteria(&mut self) -> Result<TermCriteria>

fn set_term_criteria(&mut self, term_criteria: TermCriteria) -> Result<()>

impl Detail_BundleAdjusterBaseTrait for Ptr<Detail_NoBundleAdjuster>

fn as_raw_mut_Detail_BundleAdjusterBase(&mut self) -> *mut c_void

fn set_refinement_mask(&mut self, mask: &impl MatTraitConst) -> Result<()>

fn set_conf_thresh(&mut self, conf_thresh: f64) -> Result<()>

fn term_criteria(&mut self) -> Result<TermCriteria>

fn set_term_criteria(&mut self, term_criteria: TermCriteria) -> Result<()>

impl Detail_BundleAdjusterBaseTraitConst for Ptr<Detail_BundleAdjusterAffine>

fn as_raw_Detail_BundleAdjusterBase(&self) -> *const c_void

fn refinement_mask(&self) -> Result<Mat>

fn conf_thresh(&self) -> Result<f64>

impl Detail_BundleAdjusterBaseTraitConst for Ptr<Detail_BundleAdjusterAffinePartial>

fn as_raw_Detail_BundleAdjusterBase(&self) -> *const c_void

fn refinement_mask(&self) -> Result<Mat>

fn conf_thresh(&self) -> Result<f64>

impl Detail_BundleAdjusterBaseTraitConst for Ptr<Detail_BundleAdjusterBase>

fn as_raw_Detail_BundleAdjusterBase(&self) -> *const c_void

fn refinement_mask(&self) -> Result<Mat>

fn conf_thresh(&self) -> Result<f64>

impl Detail_BundleAdjusterBaseTraitConst for Ptr<Detail_BundleAdjusterRay>

fn as_raw_Detail_BundleAdjusterBase(&self) -> *const c_void

fn refinement_mask(&self) -> Result<Mat>

fn conf_thresh(&self) -> Result<f64>

impl Detail_BundleAdjusterBaseTraitConst for Ptr<Detail_BundleAdjusterReproj>

fn as_raw_Detail_BundleAdjusterBase(&self) -> *const c_void

fn refinement_mask(&self) -> Result<Mat>

fn conf_thresh(&self) -> Result<f64>

impl Detail_BundleAdjusterBaseTraitConst for Ptr<Detail_NoBundleAdjuster>

fn as_raw_Detail_BundleAdjusterBase(&self) -> *const c_void

fn refinement_mask(&self) -> Result<Mat>

fn conf_thresh(&self) -> Result<f64>

impl Detail_BundleAdjusterRayTrait for Ptr<Detail_BundleAdjusterRay>

fn as_raw_mut_Detail_BundleAdjusterRay(&mut self) -> *mut c_void

impl Detail_BundleAdjusterRayTraitConst for Ptr<Detail_BundleAdjusterRay>

fn as_raw_Detail_BundleAdjusterRay(&self) -> *const c_void

impl Detail_BundleAdjusterReprojTrait for Ptr<Detail_BundleAdjusterReproj>

fn as_raw_mut_Detail_BundleAdjusterReproj(&mut self) -> *mut c_void

impl Detail_BundleAdjusterReprojTraitConst for Ptr<Detail_BundleAdjusterReproj>

fn as_raw_Detail_BundleAdjusterReproj(&self) -> *const c_void

impl Detail_ChannelsCompensatorTrait for Ptr<Detail_ChannelsCompensator>

fn as_raw_mut_Detail_ChannelsCompensator(&mut self) -> *mut c_void

fn feed( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<Tuple<(UMat, u8)>> ) -> Result<()>

fn apply( &mut self, index: i32, corner: Point, image: &mut impl ToInputOutputArray, mask: &impl ToInputArray ) -> Result<()>

fn get_mat_gains(&mut self, umv: &mut Vector<Mat>) -> Result<()>

fn set_mat_gains(&mut self, umv: &mut Vector<Mat>) -> Result<()>

fn set_nr_feeds(&mut self, nr_feeds: i32) -> Result<()>

fn get_nr_feeds(&mut self) -> Result<i32>

fn set_similarity_threshold(&mut self, similarity_threshold: f64) -> Result<()>

impl Detail_ChannelsCompensatorTraitConst for Ptr<Detail_ChannelsCompensator>

fn as_raw_Detail_ChannelsCompensator(&self) -> *const c_void

fn get_similarity_threshold(&self) -> Result<f64>

fn gains(&self) -> Result<Vector<Scalar>>

impl Detail_DpSeamFinderTrait for Ptr<Detail_DpSeamFinder>

fn as_raw_mut_Detail_DpSeamFinder(&mut self) -> *mut c_void

fn set_cost_function( &mut self, val: Detail_DpSeamFinder_CostFunction ) -> Result<()>

fn set_cost_function_1(&mut self, val: &str) -> Result<()>

fn find( &mut self, src: &Vector<UMat>, corners: &Vector<Point>, masks: &mut Vector<UMat> ) -> Result<()>

impl Detail_DpSeamFinderTraitConst for Ptr<Detail_DpSeamFinder>

fn as_raw_Detail_DpSeamFinder(&self) -> *const c_void

fn cost_function(&self) -> Result<Detail_DpSeamFinder_CostFunction>

impl Detail_EstimatorTrait for Ptr<Detail_AffineBasedEstimator>

fn as_raw_mut_Detail_Estimator(&mut self) -> *mut c_void

fn apply( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &Vector<Detail_MatchesInfo>, cameras: &mut Vector<Detail_CameraParams> ) -> Result<bool>

Estimates camera parameters.

impl Detail_EstimatorTrait for Ptr<Detail_BundleAdjusterAffine>

fn as_raw_mut_Detail_Estimator(&mut self) -> *mut c_void

fn apply( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &Vector<Detail_MatchesInfo>, cameras: &mut Vector<Detail_CameraParams> ) -> Result<bool>

Estimates camera parameters.

impl Detail_EstimatorTrait for Ptr<Detail_BundleAdjusterAffinePartial>

fn as_raw_mut_Detail_Estimator(&mut self) -> *mut c_void

fn apply( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &Vector<Detail_MatchesInfo>, cameras: &mut Vector<Detail_CameraParams> ) -> Result<bool>

Estimates camera parameters.

impl Detail_EstimatorTrait for Ptr<Detail_BundleAdjusterBase>

fn as_raw_mut_Detail_Estimator(&mut self) -> *mut c_void

fn apply( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &Vector<Detail_MatchesInfo>, cameras: &mut Vector<Detail_CameraParams> ) -> Result<bool>

Estimates camera parameters.

impl Detail_EstimatorTrait for Ptr<Detail_BundleAdjusterRay>

fn as_raw_mut_Detail_Estimator(&mut self) -> *mut c_void

fn apply( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &Vector<Detail_MatchesInfo>, cameras: &mut Vector<Detail_CameraParams> ) -> Result<bool>

Estimates camera parameters.

impl Detail_EstimatorTrait for Ptr<Detail_BundleAdjusterReproj>

fn as_raw_mut_Detail_Estimator(&mut self) -> *mut c_void

fn apply( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &Vector<Detail_MatchesInfo>, cameras: &mut Vector<Detail_CameraParams> ) -> Result<bool>

Estimates camera parameters.

impl Detail_EstimatorTrait for Ptr<Detail_Estimator>

fn as_raw_mut_Detail_Estimator(&mut self) -> *mut c_void

fn apply( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &Vector<Detail_MatchesInfo>, cameras: &mut Vector<Detail_CameraParams> ) -> Result<bool>

Estimates camera parameters.

impl Detail_EstimatorTrait for Ptr<Detail_HomographyBasedEstimator>

fn as_raw_mut_Detail_Estimator(&mut self) -> *mut c_void

fn apply( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &Vector<Detail_MatchesInfo>, cameras: &mut Vector<Detail_CameraParams> ) -> Result<bool>

Estimates camera parameters.

impl Detail_EstimatorTrait for Ptr<Detail_NoBundleAdjuster>

fn as_raw_mut_Detail_Estimator(&mut self) -> *mut c_void

fn apply( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &Vector<Detail_MatchesInfo>, cameras: &mut Vector<Detail_CameraParams> ) -> Result<bool>

Estimates camera parameters.

impl Detail_EstimatorTraitConst for Ptr<Detail_AffineBasedEstimator>

fn as_raw_Detail_Estimator(&self) -> *const c_void

impl Detail_EstimatorTraitConst for Ptr<Detail_BundleAdjusterAffine>

fn as_raw_Detail_Estimator(&self) -> *const c_void

impl Detail_EstimatorTraitConst for Ptr<Detail_BundleAdjusterAffinePartial>

fn as_raw_Detail_Estimator(&self) -> *const c_void

impl Detail_EstimatorTraitConst for Ptr<Detail_BundleAdjusterBase>

fn as_raw_Detail_Estimator(&self) -> *const c_void

impl Detail_EstimatorTraitConst for Ptr<Detail_BundleAdjusterRay>

fn as_raw_Detail_Estimator(&self) -> *const c_void

impl Detail_EstimatorTraitConst for Ptr<Detail_BundleAdjusterReproj>

fn as_raw_Detail_Estimator(&self) -> *const c_void

impl Detail_EstimatorTraitConst for Ptr<Detail_Estimator>

fn as_raw_Detail_Estimator(&self) -> *const c_void

impl Detail_EstimatorTraitConst for Ptr<Detail_HomographyBasedEstimator>

fn as_raw_Detail_Estimator(&self) -> *const c_void

impl Detail_EstimatorTraitConst for Ptr<Detail_NoBundleAdjuster>

fn as_raw_Detail_Estimator(&self) -> *const c_void

impl Detail_ExposureCompensatorTrait for Ptr<Detail_BlocksChannelsCompensator>

fn as_raw_mut_Detail_ExposureCompensator(&mut self) -> *mut c_void

fn feed( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<UMat> ) -> Result<()>

Parameters

fn feed_1( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<Tuple<(UMat, u8)>> ) -> Result<()>

Parameters

fn apply( &mut self, index: i32, corner: Point, image: &mut impl ToInputOutputArray, mask: &impl ToInputArray ) -> Result<()>

Compensate exposure in the specified image.

fn get_mat_gains(&mut self, unnamed: &mut Vector<Mat>) -> Result<()>

fn set_mat_gains(&mut self, unnamed: &mut Vector<Mat>) -> Result<()>

fn set_update_gain(&mut self, b: bool) -> Result<()>

fn get_update_gain(&mut self) -> Result<bool>

impl Detail_ExposureCompensatorTrait for Ptr<Detail_BlocksCompensator>

fn as_raw_mut_Detail_ExposureCompensator(&mut self) -> *mut c_void

fn feed( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<UMat> ) -> Result<()>

Parameters

fn feed_1( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<Tuple<(UMat, u8)>> ) -> Result<()>

Parameters

fn apply( &mut self, index: i32, corner: Point, image: &mut impl ToInputOutputArray, mask: &impl ToInputArray ) -> Result<()>

Compensate exposure in the specified image.

fn get_mat_gains(&mut self, unnamed: &mut Vector<Mat>) -> Result<()>

fn set_mat_gains(&mut self, unnamed: &mut Vector<Mat>) -> Result<()>

fn set_update_gain(&mut self, b: bool) -> Result<()>

fn get_update_gain(&mut self) -> Result<bool>

impl Detail_ExposureCompensatorTrait for Ptr<Detail_BlocksGainCompensator>

fn as_raw_mut_Detail_ExposureCompensator(&mut self) -> *mut c_void

fn feed( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<UMat> ) -> Result<()>

Parameters

fn feed_1( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<Tuple<(UMat, u8)>> ) -> Result<()>

Parameters

fn apply( &mut self, index: i32, corner: Point, image: &mut impl ToInputOutputArray, mask: &impl ToInputArray ) -> Result<()>

Compensate exposure in the specified image.

fn get_mat_gains(&mut self, unnamed: &mut Vector<Mat>) -> Result<()>

fn set_mat_gains(&mut self, unnamed: &mut Vector<Mat>) -> Result<()>

fn set_update_gain(&mut self, b: bool) -> Result<()>

fn get_update_gain(&mut self) -> Result<bool>

impl Detail_ExposureCompensatorTrait for Ptr<Detail_ChannelsCompensator>

fn as_raw_mut_Detail_ExposureCompensator(&mut self) -> *mut c_void

fn feed( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<UMat> ) -> Result<()>

Parameters

fn feed_1( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<Tuple<(UMat, u8)>> ) -> Result<()>

Parameters

fn apply( &mut self, index: i32, corner: Point, image: &mut impl ToInputOutputArray, mask: &impl ToInputArray ) -> Result<()>

Compensate exposure in the specified image.

fn get_mat_gains(&mut self, unnamed: &mut Vector<Mat>) -> Result<()>

fn set_mat_gains(&mut self, unnamed: &mut Vector<Mat>) -> Result<()>

fn set_update_gain(&mut self, b: bool) -> Result<()>

fn get_update_gain(&mut self) -> Result<bool>

impl Detail_ExposureCompensatorTrait for Ptr<Detail_ExposureCompensator>

fn as_raw_mut_Detail_ExposureCompensator(&mut self) -> *mut c_void

fn feed( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<UMat> ) -> Result<()>

Parameters

fn feed_1( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<Tuple<(UMat, u8)>> ) -> Result<()>

Parameters

fn apply( &mut self, index: i32, corner: Point, image: &mut impl ToInputOutputArray, mask: &impl ToInputArray ) -> Result<()>

Compensate exposure in the specified image.

fn get_mat_gains(&mut self, unnamed: &mut Vector<Mat>) -> Result<()>

fn set_mat_gains(&mut self, unnamed: &mut Vector<Mat>) -> Result<()>

fn set_update_gain(&mut self, b: bool) -> Result<()>

fn get_update_gain(&mut self) -> Result<bool>

impl Detail_ExposureCompensatorTrait for Ptr<Detail_GainCompensator>

fn as_raw_mut_Detail_ExposureCompensator(&mut self) -> *mut c_void

fn feed( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<UMat> ) -> Result<()>

Parameters

fn feed_1( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<Tuple<(UMat, u8)>> ) -> Result<()>

Parameters

fn apply( &mut self, index: i32, corner: Point, image: &mut impl ToInputOutputArray, mask: &impl ToInputArray ) -> Result<()>

Compensate exposure in the specified image.

fn get_mat_gains(&mut self, unnamed: &mut Vector<Mat>) -> Result<()>

fn set_mat_gains(&mut self, unnamed: &mut Vector<Mat>) -> Result<()>

fn set_update_gain(&mut self, b: bool) -> Result<()>

fn get_update_gain(&mut self) -> Result<bool>

impl Detail_ExposureCompensatorTrait for Ptr<Detail_NoExposureCompensator>

fn as_raw_mut_Detail_ExposureCompensator(&mut self) -> *mut c_void

fn feed( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<UMat> ) -> Result<()>

Parameters

fn feed_1( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<Tuple<(UMat, u8)>> ) -> Result<()>

Parameters

fn apply( &mut self, index: i32, corner: Point, image: &mut impl ToInputOutputArray, mask: &impl ToInputArray ) -> Result<()>

Compensate exposure in the specified image.

fn get_mat_gains(&mut self, unnamed: &mut Vector<Mat>) -> Result<()>

fn set_mat_gains(&mut self, unnamed: &mut Vector<Mat>) -> Result<()>

fn set_update_gain(&mut self, b: bool) -> Result<()>

fn get_update_gain(&mut self) -> Result<bool>

impl Detail_ExposureCompensatorTraitConst for Ptr<Detail_BlocksChannelsCompensator>

fn as_raw_Detail_ExposureCompensator(&self) -> *const c_void

impl Detail_ExposureCompensatorTraitConst for Ptr<Detail_BlocksCompensator>

fn as_raw_Detail_ExposureCompensator(&self) -> *const c_void

impl Detail_ExposureCompensatorTraitConst for Ptr<Detail_BlocksGainCompensator>

fn as_raw_Detail_ExposureCompensator(&self) -> *const c_void

impl Detail_ExposureCompensatorTraitConst for Ptr<Detail_ChannelsCompensator>

fn as_raw_Detail_ExposureCompensator(&self) -> *const c_void

impl Detail_ExposureCompensatorTraitConst for Ptr<Detail_ExposureCompensator>

fn as_raw_Detail_ExposureCompensator(&self) -> *const c_void

impl Detail_ExposureCompensatorTraitConst for Ptr<Detail_GainCompensator>

fn as_raw_Detail_ExposureCompensator(&self) -> *const c_void

impl Detail_ExposureCompensatorTraitConst for Ptr<Detail_NoExposureCompensator>

fn as_raw_Detail_ExposureCompensator(&self) -> *const c_void

impl Detail_FeatherBlenderTrait for Ptr<Detail_FeatherBlender>

fn as_raw_mut_Detail_FeatherBlender(&mut self) -> *mut c_void

fn set_sharpness(&mut self, val: f32) -> Result<()>

fn prepare(&mut self, dst_roi: Rect) -> Result<()>

fn feed( &mut self, img: &impl ToInputArray, mask: &impl ToInputArray, tl: Point ) -> Result<()>

fn blend( &mut self, dst: &mut impl ToInputOutputArray, dst_mask: &mut impl ToInputOutputArray ) -> Result<()>

fn create_weight_maps( &mut self, masks: &Vector<UMat>, corners: &Vector<Point>, weight_maps: &mut Vector<UMat> ) -> Result<Rect>

Creates weight maps for fixed set of source images by their masks and top-left corners. Final image can be obtained by simple weighting of the source images.

impl Detail_FeatherBlenderTraitConst for Ptr<Detail_FeatherBlender>

fn as_raw_Detail_FeatherBlender(&self) -> *const c_void

fn sharpness(&self) -> Result<f32>

impl Detail_FeaturesMatcherTrait for Ptr<Detail_AffineBestOf2NearestMatcher>

fn as_raw_mut_Detail_FeaturesMatcher(&mut self) -> *mut c_void

fn apply( &mut self, features1: &impl Detail_ImageFeaturesTraitConst, features2: &impl Detail_ImageFeaturesTraitConst, matches_info: &mut impl Detail_MatchesInfoTrait ) -> Result<()>

Performs images matching.

fn apply2( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &mut Vector<Detail_MatchesInfo>, mask: &impl UMatTraitConst ) -> Result<()>

Performs images matching.

fn apply2_def( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &mut Vector<Detail_MatchesInfo> ) -> Result<()>

Performs images matching.

fn collect_garbage(&mut self) -> Result<()>

Frees unused memory allocated before if there is any.

impl Detail_FeaturesMatcherTrait for Ptr<Detail_BestOf2NearestMatcher>

fn as_raw_mut_Detail_FeaturesMatcher(&mut self) -> *mut c_void

fn apply( &mut self, features1: &impl Detail_ImageFeaturesTraitConst, features2: &impl Detail_ImageFeaturesTraitConst, matches_info: &mut impl Detail_MatchesInfoTrait ) -> Result<()>

Performs images matching.

fn apply2( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &mut Vector<Detail_MatchesInfo>, mask: &impl UMatTraitConst ) -> Result<()>

Performs images matching.

fn apply2_def( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &mut Vector<Detail_MatchesInfo> ) -> Result<()>

Performs images matching.

fn collect_garbage(&mut self) -> Result<()>

Frees unused memory allocated before if there is any.

impl Detail_FeaturesMatcherTrait for Ptr<Detail_BestOf2NearestRangeMatcher>

fn as_raw_mut_Detail_FeaturesMatcher(&mut self) -> *mut c_void

fn apply( &mut self, features1: &impl Detail_ImageFeaturesTraitConst, features2: &impl Detail_ImageFeaturesTraitConst, matches_info: &mut impl Detail_MatchesInfoTrait ) -> Result<()>

Performs images matching.

fn apply2( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &mut Vector<Detail_MatchesInfo>, mask: &impl UMatTraitConst ) -> Result<()>

Performs images matching.

fn apply2_def( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &mut Vector<Detail_MatchesInfo> ) -> Result<()>

Performs images matching.

fn collect_garbage(&mut self) -> Result<()>

Frees unused memory allocated before if there is any.

impl Detail_FeaturesMatcherTrait for Ptr<Detail_FeaturesMatcher>

fn as_raw_mut_Detail_FeaturesMatcher(&mut self) -> *mut c_void

fn apply( &mut self, features1: &impl Detail_ImageFeaturesTraitConst, features2: &impl Detail_ImageFeaturesTraitConst, matches_info: &mut impl Detail_MatchesInfoTrait ) -> Result<()>

Performs images matching.

fn apply2( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &mut Vector<Detail_MatchesInfo>, mask: &impl UMatTraitConst ) -> Result<()>

Performs images matching.

fn apply2_def( &mut self, features: &Vector<Detail_ImageFeatures>, pairwise_matches: &mut Vector<Detail_MatchesInfo> ) -> Result<()>

Performs images matching.

fn collect_garbage(&mut self) -> Result<()>

Frees unused memory allocated before if there is any.

impl Detail_FeaturesMatcherTraitConst for Ptr<Detail_AffineBestOf2NearestMatcher>

fn as_raw_Detail_FeaturesMatcher(&self) -> *const c_void

fn is_thread_safe(&self) -> Result<bool>

Returns

impl Detail_FeaturesMatcherTraitConst for Ptr<Detail_BestOf2NearestMatcher>

fn as_raw_Detail_FeaturesMatcher(&self) -> *const c_void

fn is_thread_safe(&self) -> Result<bool>

Returns

impl Detail_FeaturesMatcherTraitConst for Ptr<Detail_BestOf2NearestRangeMatcher>

fn as_raw_Detail_FeaturesMatcher(&self) -> *const c_void

fn is_thread_safe(&self) -> Result<bool>

Returns

impl Detail_FeaturesMatcherTraitConst for Ptr<Detail_FeaturesMatcher>

fn as_raw_Detail_FeaturesMatcher(&self) -> *const c_void

fn is_thread_safe(&self) -> Result<bool>

Returns

impl Detail_GainCompensatorTrait for Ptr<Detail_GainCompensator>

fn as_raw_mut_Detail_GainCompensator(&mut self) -> *mut c_void

fn feed( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<Tuple<(UMat, u8)>> ) -> Result<()>

fn single_feed( &mut self, corners: &Vector<Point>, images: &Vector<UMat>, masks: &Vector<Tuple<(UMat, u8)>> ) -> Result<()>

fn apply( &mut self, index: i32, corner: Point, image: &mut impl ToInputOutputArray, mask: &impl ToInputArray ) -> Result<()>

fn get_mat_gains(&mut self, umv: &mut Vector<Mat>) -> Result<()>

fn set_mat_gains(&mut self, umv: &mut Vector<Mat>) -> Result<()>

fn set_nr_feeds(&mut self, nr_feeds: i32) -> Result<()>

fn get_nr_feeds(&mut self) -> Result<i32>

fn set_similarity_threshold(&mut self, similarity_threshold: f64) -> Result<()>

fn prepare_similarity_mask( &mut self, corners: &Vector<Point>, images: &Vector<UMat> ) -> Result<()>

impl Detail_GainCompensatorTraitConst for Ptr<Detail_GainCompensator>

fn as_raw_Detail_GainCompensator(&self) -> *const c_void

fn get_similarity_threshold(&self) -> Result<f64>

fn gains(&self) -> Result<Vector<f64>>

impl Detail_GraphCutSeamFinderBaseTrait for Ptr<Detail_GraphCutSeamFinder>

fn as_raw_mut_Detail_GraphCutSeamFinderBase(&mut self) -> *mut c_void

impl Detail_GraphCutSeamFinderBaseTrait for Ptr<Detail_GraphCutSeamFinderBase>

fn as_raw_mut_Detail_GraphCutSeamFinderBase(&mut self) -> *mut c_void

impl Detail_GraphCutSeamFinderBaseTrait for Ptr<Detail_GraphCutSeamFinderGpu>

fn as_raw_mut_Detail_GraphCutSeamFinderBase(&mut self) -> *mut c_void

impl Detail_GraphCutSeamFinderBaseTraitConst for Ptr<Detail_GraphCutSeamFinder>

fn as_raw_Detail_GraphCutSeamFinderBase(&self) -> *const c_void

impl Detail_GraphCutSeamFinderBaseTraitConst for Ptr<Detail_GraphCutSeamFinderBase>

fn as_raw_Detail_GraphCutSeamFinderBase(&self) -> *const c_void

impl Detail_GraphCutSeamFinderBaseTraitConst for Ptr<Detail_GraphCutSeamFinderGpu>

fn as_raw_Detail_GraphCutSeamFinderBase(&self) -> *const c_void

impl Detail_GraphCutSeamFinderGpuTrait for Ptr<Detail_GraphCutSeamFinderGpu>

fn as_raw_mut_Detail_GraphCutSeamFinderGpu(&mut self) -> *mut c_void

fn find( &mut self, src: &Vector<UMat>, corners: &Vector<Point>, masks: &mut Vector<UMat> ) -> Result<()>

fn find_in_pair( &mut self, first: size_t, second: size_t, roi: Rect ) -> Result<()>

impl Detail_GraphCutSeamFinderGpuTraitConst for Ptr<Detail_GraphCutSeamFinderGpu>

fn as_raw_Detail_GraphCutSeamFinderGpu(&self) -> *const c_void

impl Detail_GraphCutSeamFinderTrait for Ptr<Detail_GraphCutSeamFinder>

fn as_raw_mut_Detail_GraphCutSeamFinder(&mut self) -> *mut c_void

fn find( &mut self, src: &Vector<UMat>, corners: &Vector<Point>, masks: &mut Vector<UMat> ) -> Result<()>

impl Detail_GraphCutSeamFinderTraitConst for Ptr<Detail_GraphCutSeamFinder>

fn as_raw_Detail_GraphCutSeamFinder(&self) -> *const c_void

impl Detail_HomographyBasedEstimatorTrait for Ptr<Detail_HomographyBasedEstimator>

fn as_raw_mut_Detail_HomographyBasedEstimator(&mut self) -> *mut c_void

impl Detail_HomographyBasedEstimatorTraitConst for Ptr<Detail_HomographyBasedEstimator>

fn as_raw_Detail_HomographyBasedEstimator(&self) -> *const c_void

impl Detail_MultiBandBlenderTrait for Ptr<Detail_MultiBandBlender>

fn as_raw_mut_Detail_MultiBandBlender(&mut self) -> *mut c_void

fn set_num_bands(&mut self, val: i32) -> Result<()>

fn prepare(&mut self, dst_roi: Rect) -> Result<()>

fn feed( &mut self, img: &impl ToInputArray, mask: &impl ToInputArray, tl: Point ) -> Result<()>

fn blend( &mut self, dst: &mut impl ToInputOutputArray, dst_mask: &mut impl ToInputOutputArray ) -> Result<()>

impl Detail_MultiBandBlenderTraitConst for Ptr<Detail_MultiBandBlender>

fn as_raw_Detail_MultiBandBlender(&self) -> *const c_void

fn num_bands(&self) -> Result<i32>

impl Detail_NoBundleAdjusterTrait for Ptr<Detail_NoBundleAdjuster>

fn as_raw_mut_Detail_NoBundleAdjuster(&mut self) -> *mut c_void

impl Detail_NoBundleAdjusterTraitConst for Ptr<Detail_NoBundleAdjuster>

fn as_raw_Detail_NoBundleAdjuster(&self) -> *const c_void

impl Detail_NoExposureCompensatorTrait for Ptr<Detail_NoExposureCompensator>

fn as_raw_mut_Detail_NoExposureCompensator(&mut self) -> *mut c_void

fn feed( &mut self, unnamed: &Vector<Point>, unnamed_1: &Vector<UMat>, unnamed_2: &Vector<Tuple<(UMat, u8)>> ) -> Result<()>

fn apply( &mut self, unnamed: i32, unnamed_1: Point, unnamed_2: &mut impl ToInputOutputArray, unnamed_3: &impl ToInputArray ) -> Result<()>

fn get_mat_gains(&mut self, umv: &mut Vector<Mat>) -> Result<()>

fn set_mat_gains(&mut self, umv: &mut Vector<Mat>) -> Result<()>

impl Detail_NoExposureCompensatorTraitConst for Ptr<Detail_NoExposureCompensator>

fn as_raw_Detail_NoExposureCompensator(&self) -> *const c_void

impl Detail_NoSeamFinderTrait for Ptr<Detail_NoSeamFinder>

fn as_raw_mut_Detail_NoSeamFinder(&mut self) -> *mut c_void

fn find( &mut self, unnamed: &Vector<UMat>, unnamed_1: &Vector<Point>, unnamed_2: &mut Vector<UMat> ) -> Result<()>

impl Detail_NoSeamFinderTraitConst for Ptr<Detail_NoSeamFinder>

fn as_raw_Detail_NoSeamFinder(&self) -> *const c_void

impl Detail_PairwiseSeamFinderTrait for Ptr<Detail_GraphCutSeamFinderGpu>

fn as_raw_mut_Detail_PairwiseSeamFinder(&mut self) -> *mut c_void

fn find( &mut self, src: &Vector<UMat>, corners: &Vector<Point>, masks: &mut Vector<UMat> ) -> Result<()>

impl Detail_PairwiseSeamFinderTrait for Ptr<Detail_PairwiseSeamFinder>

fn as_raw_mut_Detail_PairwiseSeamFinder(&mut self) -> *mut c_void

fn find( &mut self, src: &Vector<UMat>, corners: &Vector<Point>, masks: &mut Vector<UMat> ) -> Result<()>

impl Detail_PairwiseSeamFinderTrait for Ptr<Detail_VoronoiSeamFinder>

fn as_raw_mut_Detail_PairwiseSeamFinder(&mut self) -> *mut c_void

fn find( &mut self, src: &Vector<UMat>, corners: &Vector<Point>, masks: &mut Vector<UMat> ) -> Result<()>

impl Detail_PairwiseSeamFinderTraitConst for Ptr<Detail_GraphCutSeamFinderGpu>

fn as_raw_Detail_PairwiseSeamFinder(&self) -> *const c_void

impl Detail_PairwiseSeamFinderTraitConst for Ptr<Detail_PairwiseSeamFinder>

fn as_raw_Detail_PairwiseSeamFinder(&self) -> *const c_void

impl Detail_PairwiseSeamFinderTraitConst for Ptr<Detail_VoronoiSeamFinder>

fn as_raw_Detail_PairwiseSeamFinder(&self) -> *const c_void

impl Detail_RotationWarperTrait for Ptr<Detail_RotationWarper>

fn as_raw_mut_Detail_RotationWarper(&mut self) -> *mut c_void

fn warp_point( &mut self, pt: Point2f, k: &impl ToInputArray, r: &impl ToInputArray ) -> Result<Point2f>

Projects the image point.

fn warp_point_backward( &mut self, pt: Point2f, k: &impl ToInputArray, r: &impl ToInputArray ) -> Result<Point2f>

fn build_maps( &mut self, src_size: Size, k: &impl ToInputArray, r: &impl ToInputArray, xmap: &mut impl ToOutputArray, ymap: &mut impl ToOutputArray ) -> Result<Rect>

Builds the projection maps according to the given camera data.

fn warp( &mut self, src: &impl ToInputArray, k: &impl ToInputArray, r: &impl ToInputArray, interp_mode: i32, border_mode: i32, dst: &mut impl ToOutputArray ) -> Result<Point>

Projects the image.

fn warp_backward( &mut self, src: &impl ToInputArray, k: &impl ToInputArray, r: &impl ToInputArray, interp_mode: i32, border_mode: i32, dst_size: Size, dst: &mut impl ToOutputArray ) -> Result<()>

Projects the image backward.

fn warp_roi( &mut self, src_size: Size, k: &impl ToInputArray, r: &impl ToInputArray ) -> Result<Rect>

Parameters

fn set_scale(&mut self, unnamed: f32) -> Result<()>

impl Detail_RotationWarperTraitConst for Ptr<Detail_RotationWarper>

fn as_raw_Detail_RotationWarper(&self) -> *const c_void

fn get_scale(&self) -> Result<f32>

impl Detail_SeamFinderTrait for Ptr<Detail_DpSeamFinder>

fn as_raw_mut_Detail_SeamFinder(&mut self) -> *mut c_void

fn find( &mut self, src: &Vector<UMat>, corners: &Vector<Point>, masks: &mut Vector<UMat> ) -> Result<()>

Estimates seams.

impl Detail_SeamFinderTrait for Ptr<Detail_GraphCutSeamFinder>

fn as_raw_mut_Detail_SeamFinder(&mut self) -> *mut c_void

fn find( &mut self, src: &Vector<UMat>, corners: &Vector<Point>, masks: &mut Vector<UMat> ) -> Result<()>

Estimates seams.

impl Detail_SeamFinderTrait for Ptr<Detail_GraphCutSeamFinderGpu>

fn as_raw_mut_Detail_SeamFinder(&mut self) -> *mut c_void

fn find( &mut self, src: &Vector<UMat>, corners: &Vector<Point>, masks: &mut Vector<UMat> ) -> Result<()>

Estimates seams.

impl Detail_SeamFinderTrait for Ptr<Detail_NoSeamFinder>

fn as_raw_mut_Detail_SeamFinder(&mut self) -> *mut c_void

fn find( &mut self, src: &Vector<UMat>, corners: &Vector<Point>, masks: &mut Vector<UMat> ) -> Result<()>

Estimates seams.

impl Detail_SeamFinderTrait for Ptr<Detail_PairwiseSeamFinder>

fn as_raw_mut_Detail_SeamFinder(&mut self) -> *mut c_void

fn find( &mut self, src: &Vector<UMat>, corners: &Vector<Point>, masks: &mut Vector<UMat> ) -> Result<()>

Estimates seams.

impl Detail_SeamFinderTrait for Ptr<Detail_SeamFinder>

fn as_raw_mut_Detail_SeamFinder(&mut self) -> *mut c_void

fn find( &mut self, src: &Vector<UMat>, corners: &Vector<Point>, masks: &mut Vector<UMat> ) -> Result<()>

Estimates seams.

impl Detail_SeamFinderTrait for Ptr<Detail_VoronoiSeamFinder>

fn as_raw_mut_Detail_SeamFinder(&mut self) -> *mut c_void

fn find( &mut self, src: &Vector<UMat>, corners: &Vector<Point>, masks: &mut Vector<UMat> ) -> Result<()>

Estimates seams.

impl Detail_SeamFinderTraitConst for Ptr<Detail_DpSeamFinder>

fn as_raw_Detail_SeamFinder(&self) -> *const c_void

impl Detail_SeamFinderTraitConst for Ptr<Detail_GraphCutSeamFinder>

fn as_raw_Detail_SeamFinder(&self) -> *const c_void

impl Detail_SeamFinderTraitConst for Ptr<Detail_GraphCutSeamFinderGpu>

fn as_raw_Detail_SeamFinder(&self) -> *const c_void

impl Detail_SeamFinderTraitConst for Ptr<Detail_NoSeamFinder>

fn as_raw_Detail_SeamFinder(&self) -> *const c_void

impl Detail_SeamFinderTraitConst for Ptr<Detail_PairwiseSeamFinder>

fn as_raw_Detail_SeamFinder(&self) -> *const c_void

impl Detail_SeamFinderTraitConst for Ptr<Detail_SeamFinder>

fn as_raw_Detail_SeamFinder(&self) -> *const c_void

impl Detail_SeamFinderTraitConst for Ptr<Detail_VoronoiSeamFinder>

fn as_raw_Detail_SeamFinder(&self) -> *const c_void

impl Detail_VoronoiSeamFinderTrait for Ptr<Detail_VoronoiSeamFinder>

fn as_raw_mut_Detail_VoronoiSeamFinder(&mut self) -> *mut c_void

fn find( &mut self, src: &Vector<UMat>, corners: &Vector<Point>, masks: &mut Vector<UMat> ) -> Result<()>

fn find_1( &mut self, size: &Vector<Size>, corners: &Vector<Point>, masks: &mut Vector<UMat> ) -> Result<()>

impl Detail_VoronoiSeamFinderTraitConst for Ptr<Detail_VoronoiSeamFinder>

fn as_raw_Detail_VoronoiSeamFinder(&self) -> *const c_void

impl DetectionBasedTracker_IDetectorTrait for Ptr<DetectionBasedTracker_IDetector>

fn as_raw_mut_DetectionBasedTracker_IDetector(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl MatTraitConst, objects: &mut Vector<Rect> ) -> Result<()>

fn set_min_object_size(&mut self, min: Size) -> Result<()>

fn set_max_object_size(&mut self, max: Size) -> Result<()>

fn get_scale_factor(&mut self) -> Result<f32>

fn set_scale_factor(&mut self, value: f32) -> Result<()>

fn get_min_neighbours(&mut self) -> Result<i32>

fn set_min_neighbours(&mut self, value: i32) -> Result<()>

impl DetectionBasedTracker_IDetectorTraitConst for Ptr<DetectionBasedTracker_IDetector>

fn as_raw_DetectionBasedTracker_IDetector(&self) -> *const c_void

fn get_min_object_size(&self) -> Result<Size>

fn get_max_object_size(&self) -> Result<Size>

impl DetectionOutputLayerTrait for Ptr<DetectionOutputLayer>

fn as_raw_mut_DetectionOutputLayer(&mut self) -> *mut c_void

impl DetectionOutputLayerTraitConst for Ptr<DetectionOutputLayer>

fn as_raw_DetectionOutputLayer(&self) -> *const c_void

impl DetectorParametersTrait for Ptr<DetectorParameters>

fn as_raw_mut_DetectorParameters(&mut self) -> *mut c_void

fn set_adaptive_thresh_win_size_min(&mut self, val: i32)

minimum window size for adaptive thresholding before finding contours (default 3).

fn set_adaptive_thresh_win_size_max(&mut self, val: i32)

maximum window size for adaptive thresholding before finding contours (default 23).

fn set_adaptive_thresh_win_size_step(&mut self, val: i32)

increments from adaptiveThreshWinSizeMin to adaptiveThreshWinSizeMax during the thresholding (default 10).

fn set_adaptive_thresh_constant(&mut self, val: f64)

constant for adaptive thresholding before finding contours (default 7)

fn set_min_marker_perimeter_rate(&mut self, val: f64)

determine minimum perimeter for marker contour to be detected.

fn set_max_marker_perimeter_rate(&mut self, val: f64)

determine maximum perimeter for marker contour to be detected.

fn set_polygonal_approx_accuracy_rate(&mut self, val: f64)

minimum accuracy during the polygonal approximation process to determine which contours are squares. (default 0.03)

fn set_min_corner_distance_rate(&mut self, val: f64)

minimum distance between corners for detected markers relative to its perimeter (default 0.05)

fn set_min_distance_to_border(&mut self, val: i32)

minimum distance of any corner to the image border for detected markers (in pixels) (default 3)

fn set_min_marker_distance_rate(&mut self, val: f64)

minimum average distance between the corners of the two markers to be grouped (default 0.125).

fn set_min_group_distance(&mut self, val: f32)

minimum average distance between the corners of the two markers in group to add them to the list of candidates

fn set_corner_refinement_method(&mut self, val: i32)

default value CORNER_REFINE_NONE

fn set_corner_refinement_win_size(&mut self, val: i32)

maximum window size for the corner refinement process (in pixels) (default 5).

fn set_relative_corner_refinment_win_size(&mut self, val: f32)

Dynamic window size for corner refinement relative to Aruco module size (default 0.3).

fn set_corner_refinement_max_iterations(&mut self, val: i32)

maximum number of iterations for stop criteria of the corner refinement process (default 30).

fn set_corner_refinement_min_accuracy(&mut self, val: f64)

minimum error for the stop cristeria of the corner refinement process (default: 0.1)

fn set_marker_border_bits(&mut self, val: i32)

number of bits of the marker border, i.e. marker border width (default 1).

fn set_perspective_remove_pixel_per_cell(&mut self, val: i32)

number of bits (per dimension) for each cell of the marker when removing the perspective (default 4).

fn set_perspective_remove_ignored_margin_per_cell(&mut self, val: f64)

width of the margin of pixels on each cell not considered for the determination of the cell bit.

fn set_max_erroneous_bits_in_border_rate(&mut self, val: f64)

maximum number of accepted erroneous bits in the border (i.e. number of allowed white bits in the border).

fn set_min_otsu_std_dev(&mut self, val: f64)

minimun standard deviation in pixels values during the decodification step to apply Otsu thresholding (otherwise, all the bits are set to 0 or 1 depending on mean higher than 128 or not) (default 5.0)

fn set_error_correction_rate(&mut self, val: f64)

error correction rate respect to the maximun error correction capability for each dictionary (default 0.6).

fn set_april_tag_quad_decimate(&mut self, val: f32)

April :: User-configurable parameters.

fn set_april_tag_quad_sigma(&mut self, val: f32)

what Gaussian blur should be applied to the segmented image (used for quad detection?)

fn set_april_tag_min_cluster_pixels(&mut self, val: i32)

reject quads containing too few pixels (default 5).

fn set_april_tag_max_nmaxima(&mut self, val: i32)

how many corner candidates to consider when segmenting a group of pixels into a quad (default 10).

fn set_april_tag_critical_rad(&mut self, val: f32)

reject quads where pairs of edges have angles that are close to straight or close to 180 degrees.

fn set_april_tag_max_line_fit_mse(&mut self, val: f32)

when fitting lines to the contours, what is the maximum mean squared error

fn set_april_tag_min_white_black_diff(&mut self, val: i32)

add an extra check that the white model must be (overall) brighter than the black model.

fn set_april_tag_deglitch(&mut self, val: i32)

should the thresholded image be deglitched? Only useful for very noisy images (default 0).

fn set_detect_inverted_marker(&mut self, val: bool)

to check if there is a white marker.

fn set_use_aruco3_detection(&mut self, val: bool)

enable the new and faster Aruco detection strategy.

fn set_min_side_length_canonical_img(&mut self, val: i32)

minimum side length of a marker in the canonical image. Latter is the binarized image in which contours are searched.

fn set_min_marker_length_ratio_original_img(&mut self, val: f32)

range [0,1], eq (2) from paper. The parameter tau_i has a direct influence on the processing speed.

fn read_detector_parameters( &mut self, fn_: &impl FileNodeTraitConst ) -> Result<bool>

Read a new set of DetectorParameters from FileNode (use FileStorage.root()).

fn write_detector_parameters( &mut self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<bool>

Write a set of DetectorParameters to FileStorage

fn write_detector_parameters_def( &mut self, fs: &mut impl FileStorageTrait ) -> Result<bool>

Write a set of DetectorParameters to FileStorage

impl DetectorParametersTraitConst for Ptr<DetectorParameters>

fn as_raw_DetectorParameters(&self) -> *const c_void

fn adaptive_thresh_win_size_min(&self) -> i32

minimum window size for adaptive thresholding before finding contours (default 3).

fn adaptive_thresh_win_size_max(&self) -> i32

maximum window size for adaptive thresholding before finding contours (default 23).

fn adaptive_thresh_win_size_step(&self) -> i32

increments from adaptiveThreshWinSizeMin to adaptiveThreshWinSizeMax during the thresholding (default 10).

fn adaptive_thresh_constant(&self) -> f64

constant for adaptive thresholding before finding contours (default 7)

fn min_marker_perimeter_rate(&self) -> f64

determine minimum perimeter for marker contour to be detected.

fn max_marker_perimeter_rate(&self) -> f64

determine maximum perimeter for marker contour to be detected.

fn polygonal_approx_accuracy_rate(&self) -> f64

minimum accuracy during the polygonal approximation process to determine which contours are squares. (default 0.03)

fn min_corner_distance_rate(&self) -> f64

minimum distance between corners for detected markers relative to its perimeter (default 0.05)

fn min_distance_to_border(&self) -> i32

minimum distance of any corner to the image border for detected markers (in pixels) (default 3)

fn min_marker_distance_rate(&self) -> f64

minimum average distance between the corners of the two markers to be grouped (default 0.125).

fn min_group_distance(&self) -> f32

minimum average distance between the corners of the two markers in group to add them to the list of candidates

fn corner_refinement_method(&self) -> i32

default value CORNER_REFINE_NONE

fn corner_refinement_win_size(&self) -> i32

maximum window size for the corner refinement process (in pixels) (default 5).

fn relative_corner_refinment_win_size(&self) -> f32

Dynamic window size for corner refinement relative to Aruco module size (default 0.3).

fn corner_refinement_max_iterations(&self) -> i32

maximum number of iterations for stop criteria of the corner refinement process (default 30).

fn corner_refinement_min_accuracy(&self) -> f64

minimum error for the stop cristeria of the corner refinement process (default: 0.1)

fn marker_border_bits(&self) -> i32

number of bits of the marker border, i.e. marker border width (default 1).

fn perspective_remove_pixel_per_cell(&self) -> i32

number of bits (per dimension) for each cell of the marker when removing the perspective (default 4).

fn perspective_remove_ignored_margin_per_cell(&self) -> f64

width of the margin of pixels on each cell not considered for the determination of the cell bit.

fn max_erroneous_bits_in_border_rate(&self) -> f64

maximum number of accepted erroneous bits in the border (i.e. number of allowed white bits in the border).

fn min_otsu_std_dev(&self) -> f64

minimun standard deviation in pixels values during the decodification step to apply Otsu thresholding (otherwise, all the bits are set to 0 or 1 depending on mean higher than 128 or not) (default 5.0)

fn error_correction_rate(&self) -> f64

error correction rate respect to the maximun error correction capability for each dictionary (default 0.6).

fn april_tag_quad_decimate(&self) -> f32

April :: User-configurable parameters.

fn april_tag_quad_sigma(&self) -> f32

what Gaussian blur should be applied to the segmented image (used for quad detection?)

fn april_tag_min_cluster_pixels(&self) -> i32

reject quads containing too few pixels (default 5).

fn april_tag_max_nmaxima(&self) -> i32

how many corner candidates to consider when segmenting a group of pixels into a quad (default 10).

fn april_tag_critical_rad(&self) -> f32

reject quads where pairs of edges have angles that are close to straight or close to 180 degrees.

fn april_tag_max_line_fit_mse(&self) -> f32

when fitting lines to the contours, what is the maximum mean squared error

fn april_tag_min_white_black_diff(&self) -> i32

add an extra check that the white model must be (overall) brighter than the black model.

fn april_tag_deglitch(&self) -> i32

should the thresholded image be deglitched? Only useful for very noisy images (default 0).

fn detect_inverted_marker(&self) -> bool

to check if there is a white marker.

fn use_aruco3_detection(&self) -> bool

enable the new and faster Aruco detection strategy.

fn min_side_length_canonical_img(&self) -> i32

minimum side length of a marker in the canonical image. Latter is the binarized image in which contours are searched.

fn min_marker_length_ratio_original_img(&self) -> f32

range [0,1], eq (2) from paper. The parameter tau_i has a direct influence on the processing speed.

impl DictionaryTrait for Ptr<Dictionary>

fn as_raw_mut_Dictionary(&mut self) -> *mut c_void

fn set_bytes_list(&mut self, val: Mat)

marker code information. See class description for more details

fn set_marker_size(&mut self, val: i32)

number of bits per dimension

fn set_max_correction_bits(&mut self, val: i32)

maximum number of bits that can be corrected

fn read_dictionary(&mut self, fn_: &impl FileNodeTraitConst) -> Result<bool>

Read a new dictionary from FileNode.

fn write_dictionary( &mut self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

Write a dictionary to FileStorage, format is the same as in readDictionary().

fn write_dictionary_def(&mut self, fs: &mut impl FileStorageTrait) -> Result<()>

Write a dictionary to FileStorage, format is the same as in readDictionary().

impl DictionaryTraitConst for Ptr<Dictionary>

fn as_raw_Dictionary(&self) -> *const c_void

fn bytes_list(&self) -> Mat

marker code information. See class description for more details

fn marker_size(&self) -> i32

number of bits per dimension

fn max_correction_bits(&self) -> i32

maximum number of bits that can be corrected

fn identify( &self, only_bits: &impl MatTraitConst, idx: &mut i32, rotation: &mut i32, max_correction_rate: f64 ) -> Result<bool>

Given a matrix of bits. Returns whether if marker is identified or not.

fn get_distance_to_id( &self, bits: &impl ToInputArray, id: i32, all_rotations: bool ) -> Result<i32>

Returns Hamming distance of the input bits to the specific id.

fn get_distance_to_id_def( &self, bits: &impl ToInputArray, id: i32 ) -> Result<i32>

Returns Hamming distance of the input bits to the specific id.

fn generate_image_marker( &self, id: i32, side_pixels: i32, _img: &mut impl ToOutputArray, border_bits: i32 ) -> Result<()>

Generate a canonical marker image

fn generate_image_marker_def( &self, id: i32, side_pixels: i32, _img: &mut impl ToOutputArray ) -> Result<()>

Generate a canonical marker image

impl DisparityFilterTrait for Ptr<DisparityFilter>

fn as_raw_mut_DisparityFilter(&mut self) -> *mut c_void

fn filter( &mut self, disparity_map_left: &impl ToInputArray, left_view: &impl ToInputArray, filtered_disparity_map: &mut impl ToOutputArray, disparity_map_right: &impl ToInputArray, roi: Rect, right_view: &impl ToInputArray ) -> Result<()>

Apply filtering to the disparity map.

fn filter_def( &mut self, disparity_map_left: &impl ToInputArray, left_view: &impl ToInputArray, filtered_disparity_map: &mut impl ToOutputArray ) -> Result<()>

Apply filtering to the disparity map.

impl DisparityFilterTrait for Ptr<DisparityWLSFilter>

fn as_raw_mut_DisparityFilter(&mut self) -> *mut c_void

fn filter( &mut self, disparity_map_left: &impl ToInputArray, left_view: &impl ToInputArray, filtered_disparity_map: &mut impl ToOutputArray, disparity_map_right: &impl ToInputArray, roi: Rect, right_view: &impl ToInputArray ) -> Result<()>

Apply filtering to the disparity map.

fn filter_def( &mut self, disparity_map_left: &impl ToInputArray, left_view: &impl ToInputArray, filtered_disparity_map: &mut impl ToOutputArray ) -> Result<()>

Apply filtering to the disparity map.

impl DisparityFilterTraitConst for Ptr<DisparityFilter>

fn as_raw_DisparityFilter(&self) -> *const c_void

impl DisparityFilterTraitConst for Ptr<DisparityWLSFilter>

fn as_raw_DisparityFilter(&self) -> *const c_void

impl DisparityWLSFilterTrait for Ptr<DisparityWLSFilter>

fn as_raw_mut_DisparityWLSFilter(&mut self) -> *mut c_void

fn get_lambda(&mut self) -> Result<f64>

Lambda is a parameter defining the amount of regularization during filtering. Larger values force filtered disparity map edges to adhere more to source image edges. Typical value is 8000.

fn set_lambda(&mut self, _lambda: f64) -> Result<()>

See also

fn get_sigma_color(&mut self) -> Result<f64>

SigmaColor is a parameter defining how sensitive the filtering process is to source image edges. Large values can lead to disparity leakage through low-contrast edges. Small values can make the filter too sensitive to noise and textures in the source image. Typical values range from 0.8 to 2.0.

fn set_sigma_color(&mut self, _sigma_color: f64) -> Result<()>

See also

fn get_lr_cthresh(&mut self) -> Result<i32>

LRCthresh is a threshold of disparity difference used in left-right-consistency check during confidence map computation. The default value of 24 (1.5 pixels) is virtually always good enough.

fn set_lr_cthresh(&mut self, _lrc_thresh: i32) -> Result<()>

See also

fn get_depth_discontinuity_radius(&mut self) -> Result<i32>

DepthDiscontinuityRadius is a parameter used in confidence computation. It defines the size of low-confidence regions around depth discontinuities.

fn set_depth_discontinuity_radius(&mut self, _disc_radius: i32) -> Result<()>

See also

fn get_confidence_map(&mut self) -> Result<Mat>

Get the confidence map that was used in the last filter call. It is a CV_32F one-channel image with values ranging from 0.0 (totally untrusted regions of the raw disparity map) to 255.0 (regions containing correct disparity values with a high degree of confidence).

fn get_roi(&mut self) -> Result<Rect>

Get the ROI used in the last filter call

impl DisparityWLSFilterTraitConst for Ptr<DisparityWLSFilter>

fn as_raw_DisparityWLSFilter(&self) -> *const c_void

impl DnnSuperResImplTrait for Ptr<DnnSuperResImpl>

fn as_raw_mut_DnnSuperResImpl(&mut self) -> *mut c_void

fn read_model(&mut self, path: &str) -> Result<()>

Read the model from the given path

fn read_model_1(&mut self, weights: &str, definition: &str) -> Result<()>

Read the model from the given path

fn set_model(&mut self, algo: &str, scale: i32) -> Result<()>

Set desired model

fn set_preferable_backend(&mut self, backend_id: i32) -> Result<()>

Set computation backend

fn set_preferable_target(&mut self, target_id: i32) -> Result<()>

Set computation target

fn upsample( &mut self, img: &impl ToInputArray, result: &mut impl ToOutputArray ) -> Result<()>

Upsample via neural network

fn upsample_multioutput( &mut self, img: &impl ToInputArray, imgs_new: &mut Vector<Mat>, scale_factors: &Vector<i32>, node_names: &Vector<String> ) -> Result<()>

Upsample via neural network of multiple outputs

fn get_scale(&mut self) -> Result<i32>

Returns the scale factor of the model:

fn get_algorithm(&mut self) -> Result<String>

Returns the scale factor of the model:

impl DnnSuperResImplTraitConst for Ptr<DnnSuperResImpl>

fn as_raw_DnnSuperResImpl(&self) -> *const c_void

impl DownhillSolverTrait for Ptr<DownhillSolver>

fn as_raw_mut_DownhillSolver(&mut self) -> *mut c_void

fn set_init_step(&mut self, step: &impl ToInputArray) -> Result<()>

Sets the initial step that will be used in downhill simplex algorithm.

impl DownhillSolverTraitConst for Ptr<DownhillSolver>

fn as_raw_DownhillSolver(&self) -> *const c_void

fn get_init_step(&self, step: &mut impl ToOutputArray) -> Result<()>

Returns the initial step that will be used in downhill simplex algorithm.

impl<T: ?Sized> Drop for Ptr<T>

where Self: PtrExtern,

fn drop(&mut self)

Executes the destructor for this type.

impl DualTVL1OpticalFlowTrait for Ptr<DualTVL1OpticalFlow>

fn as_raw_mut_DualTVL1OpticalFlow(&mut self) -> *mut c_void

fn set_tau(&mut self, val: f64) -> Result<()>

Time step of the numerical scheme

fn set_lambda(&mut self, val: f64) -> Result<()>

Weight parameter for the data term, attachment parameter

fn set_theta(&mut self, val: f64) -> Result<()>

Weight parameter for (u - v)^2, tightness parameter

fn set_gamma(&mut self, val: f64) -> Result<()>

coefficient for additional illumination variation term

fn set_scales_number(&mut self, val: i32) -> Result<()>

Number of scales used to create the pyramid of images

fn set_warpings_number(&mut self, val: i32) -> Result<()>

Number of warpings per scale

fn set_epsilon(&mut self, val: f64) -> Result<()>

Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time

fn set_inner_iterations(&mut self, val: i32) -> Result<()>

Inner iterations (between outlier filtering) used in the numerical scheme

fn set_outer_iterations(&mut self, val: i32) -> Result<()>

Outer iterations (number of inner loops) used in the numerical scheme

fn set_use_initial_flow(&mut self, val: bool) -> Result<()>

Use initial flow

fn set_scale_step(&mut self, val: f64) -> Result<()>

Step between scales (<1)

fn set_median_filtering(&mut self, val: i32) -> Result<()>

Median filter kernel size (1 = no filter) (3 or 5)

impl DualTVL1OpticalFlowTraitConst for Ptr<DualTVL1OpticalFlow>

fn as_raw_DualTVL1OpticalFlow(&self) -> *const c_void

fn get_tau(&self) -> Result<f64>

Time step of the numerical scheme

fn get_lambda(&self) -> Result<f64>

Weight parameter for the data term, attachment parameter

fn get_theta(&self) -> Result<f64>

Weight parameter for (u - v)^2, tightness parameter

fn get_gamma(&self) -> Result<f64>

coefficient for additional illumination variation term

fn get_scales_number(&self) -> Result<i32>

Number of scales used to create the pyramid of images

fn get_warpings_number(&self) -> Result<i32>

Number of warpings per scale

fn get_epsilon(&self) -> Result<f64>

Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time

fn get_inner_iterations(&self) -> Result<i32>

Inner iterations (between outlier filtering) used in the numerical scheme

fn get_outer_iterations(&self) -> Result<i32>

Outer iterations (number of inner loops) used in the numerical scheme

fn get_use_initial_flow(&self) -> Result<bool>

Use initial flow

fn get_scale_step(&self) -> Result<f64>

Step between scales (<1)

fn get_median_filtering(&self) -> Result<i32>

Median filter kernel size (1 = no filter) (3 or 5)

impl Dynafu_DynaFuTrait for Ptr<Dynafu_DynaFu>

fn as_raw_mut_Dynafu_DynaFu(&mut self) -> *mut c_void

fn reset(&mut self) -> Result<()>

Resets the algorithm

fn update(&mut self, depth: &impl ToInputArray) -> Result<bool>

Process next depth frame

fn render_surface( &mut self, depth_image: &mut impl ToOutputArray, vert_image: &mut impl ToOutputArray, norm_image: &mut impl ToOutputArray, warp: bool ) -> Result<()>

C++ default parameters

fn render_surface_def( &mut self, depth_image: &mut impl ToOutputArray, vert_image: &mut impl ToOutputArray, norm_image: &mut impl ToOutputArray ) -> Result<()>

Note

impl Dynafu_DynaFuTraitConst for Ptr<Dynafu_DynaFu>

fn as_raw_Dynafu_DynaFu(&self) -> *const c_void

fn get_params(&self) -> Result<Kinfu_Params>

Get current parameters

fn render( &self, image: &mut impl ToOutputArray, camera_pose: Matx44f ) -> Result<()>

Renders a volume into an image

fn render_def(&self, image: &mut impl ToOutputArray) -> Result<()>

Renders a volume into an image

fn get_cloud( &self, points: &mut impl ToOutputArray, normals: &mut impl ToOutputArray ) -> Result<()>

Gets points and normals of current 3d mesh

fn get_points(&self, points: &mut impl ToOutputArray) -> Result<()>

Gets points of current 3d mesh

fn get_normals( &self, points: &impl ToInputArray, normals: &mut impl ToOutputArray ) -> Result<()>

Calculates normals for given points

fn get_pose(&self) -> Result<Affine3f>

Get current pose in voxel space

fn get_nodes_pos(&self) -> Result<Vector<Point3f>>

fn march_cubes( &self, vertices: &mut impl ToOutputArray, edges: &mut impl ToOutputArray ) -> Result<()>

impl ELULayerTrait for Ptr<ELULayer>

fn as_raw_mut_ELULayer(&mut self) -> *mut c_void

fn set_alpha(&mut self, val: f32)

impl ELULayerTraitConst for Ptr<ELULayer>

fn as_raw_ELULayer(&self) -> *const c_void

fn alpha(&self) -> f32

impl EMDHistogramCostExtractorTrait for Ptr<EMDHistogramCostExtractor>

fn as_raw_mut_EMDHistogramCostExtractor(&mut self) -> *mut c_void

fn set_norm_flag(&mut self, flag: i32) -> Result<()>

impl EMDHistogramCostExtractorTraitConst for Ptr<EMDHistogramCostExtractor>

fn as_raw_EMDHistogramCostExtractor(&self) -> *const c_void

fn get_norm_flag(&self) -> Result<i32>

impl EMDL1HistogramCostExtractorTrait for Ptr<EMDL1HistogramCostExtractor>

fn as_raw_mut_EMDL1HistogramCostExtractor(&mut self) -> *mut c_void

impl EMDL1HistogramCostExtractorTraitConst for Ptr<EMDL1HistogramCostExtractor>

fn as_raw_EMDL1HistogramCostExtractor(&self) -> *const c_void

impl EMTrait for Ptr<EM>

fn as_raw_mut_EM(&mut self) -> *mut c_void

fn set_clusters_number(&mut self, val: i32) -> Result<()>

The number of mixture components in the Gaussian mixture model. Default value of the parameter is EM::DEFAULT_NCLUSTERS=5. Some of %EM implementation could determine the optimal number of mixtures within a specified value range, but that is not the case in ML yet.

fn set_covariance_matrix_type(&mut self, val: i32) -> Result<()>

Constraint on covariance matrices which defines type of matrices. See EM::Types.

fn set_term_criteria(&mut self, val: TermCriteria) -> Result<()>

The termination criteria of the %EM algorithm. The %EM algorithm can be terminated by the number of iterations termCrit.maxCount (number of M-steps) or when relative change of likelihood logarithm is less than termCrit.epsilon. Default maximum number of iterations is EM::DEFAULT_MAX_ITERS=100.

fn train_em( &mut self, samples: &impl ToInputArray, log_likelihoods: &mut impl ToOutputArray, labels: &mut impl ToOutputArray, probs: &mut impl ToOutputArray ) -> Result<bool>

Estimate the Gaussian mixture parameters from a samples set.

fn train_em_def(&mut self, samples: &impl ToInputArray) -> Result<bool>

Estimate the Gaussian mixture parameters from a samples set.

fn train_e( &mut self, samples: &impl ToInputArray, means0: &impl ToInputArray, covs0: &impl ToInputArray, weights0: &impl ToInputArray, log_likelihoods: &mut impl ToOutputArray, labels: &mut impl ToOutputArray, probs: &mut impl ToOutputArray ) -> Result<bool>

Estimate the Gaussian mixture parameters from a samples set.

fn train_e_def( &mut self, samples: &impl ToInputArray, means0: &impl ToInputArray ) -> Result<bool>

Estimate the Gaussian mixture parameters from a samples set.

fn train_m( &mut self, samples: &impl ToInputArray, probs0: &impl ToInputArray, log_likelihoods: &mut impl ToOutputArray, labels: &mut impl ToOutputArray, probs: &mut impl ToOutputArray ) -> Result<bool>

Estimate the Gaussian mixture parameters from a samples set.

fn train_m_def( &mut self, samples: &impl ToInputArray, probs0: &impl ToInputArray ) -> Result<bool>

Estimate the Gaussian mixture parameters from a samples set.

impl EMTraitConst for Ptr<EM>

fn as_raw_EM(&self) -> *const c_void

fn get_clusters_number(&self) -> Result<i32>

The number of mixture components in the Gaussian mixture model. Default value of the parameter is EM::DEFAULT_NCLUSTERS=5. Some of %EM implementation could determine the optimal number of mixtures within a specified value range, but that is not the case in ML yet.

fn get_covariance_matrix_type(&self) -> Result<i32>

Constraint on covariance matrices which defines type of matrices. See EM::Types.

fn get_term_criteria(&self) -> Result<TermCriteria>

The termination criteria of the %EM algorithm. The %EM algorithm can be terminated by the number of iterations termCrit.maxCount (number of M-steps) or when relative change of likelihood logarithm is less than termCrit.epsilon. Default maximum number of iterations is EM::DEFAULT_MAX_ITERS=100.

fn get_weights(&self) -> Result<Mat>

Returns weights of the mixtures

fn get_means(&self) -> Result<Mat>

Returns the cluster centers (means of the Gaussian mixture)

fn get_covs(&self, covs: &mut Vector<Mat>) -> Result<()>

Returns covariation matrices

fn predict( &self, samples: &impl ToInputArray, results: &mut impl ToOutputArray, flags: i32 ) -> Result<f32>

Returns posterior probabilities for the provided samples

fn predict_def(&self, samples: &impl ToInputArray) -> Result<f32>

Returns posterior probabilities for the provided samples

fn predict2( &self, sample: &impl ToInputArray, probs: &mut impl ToOutputArray ) -> Result<Vec2d>

Returns a likelihood logarithm value and an index of the most probable mixture component for the given sample.

impl ERFilterTrait for Ptr<ERFilter>

fn as_raw_mut_ERFilter(&mut self) -> *mut c_void

fn run( &mut self, image: &impl ToInputArray, regions: &mut Vector<ERStat> ) -> Result<()>

The key method of ERFilter algorithm.

fn set_callback(&mut self, cb: &Ptr<ERFilter_Callback>) -> Result<()>

set/get methods to set the algorithm properties,

fn set_threshold_delta(&mut self, threshold_delta: i32) -> Result<()>

fn set_min_area(&mut self, min_area: f32) -> Result<()>

fn set_max_area(&mut self, max_area: f32) -> Result<()>

fn set_min_probability(&mut self, min_probability: f32) -> Result<()>

fn set_min_probability_diff(&mut self, min_probability_diff: f32) -> Result<()>

fn set_non_max_suppression(&mut self, non_max_suppression: bool) -> Result<()>

impl ERFilterTraitConst for Ptr<ERFilter>

fn as_raw_ERFilter(&self) -> *const c_void

fn get_num_rejected(&self) -> Result<i32>

impl ERFilter_CallbackTrait for Ptr<ERFilter_Callback>

fn as_raw_mut_ERFilter_Callback(&mut self) -> *mut c_void

fn eval(&mut self, stat: &impl ERStatTraitConst) -> Result<f64>

The classifier must return probability measure for the region.

impl ERFilter_CallbackTraitConst for Ptr<ERFilter_Callback>

fn as_raw_ERFilter_Callback(&self) -> *const c_void

impl EdgeAwareInterpolatorTrait for Ptr<EdgeAwareInterpolator>

fn as_raw_mut_EdgeAwareInterpolator(&mut self) -> *mut c_void

fn set_cost_map(&mut self, _cost_map: &impl MatTraitConst) -> Result<()>

Interface to provide a more elaborated cost map, i.e. edge map, for the edge-aware term. This implementation is based on a rather simple gradient-based edge map estimation. To used more complex edge map estimator (e.g. StructuredEdgeDetection that has been used in the original publication) that may lead to improved accuracies, the internal edge map estimation can be bypassed here.

fn set_k(&mut self, _k: i32) -> Result<()>

Parameter to tune the approximate size of the superpixel used for oversegmentation.

fn get_k(&mut self) -> Result<i32>

See also

fn set_sigma(&mut self, _sigma: f32) -> Result<()>

Sigma is a parameter defining how fast the weights decrease in the locally-weighted affine fitting. Higher values can help preserve fine details, lower values can help to get rid of noise in the output flow.

fn get_sigma(&mut self) -> Result<f32>

See also

fn set_lambda(&mut self, _lambda: f32) -> Result<()>

Lambda is a parameter defining the weight of the edge-aware term in geodesic distance, should be in the range of 0 to 1000.

fn get_lambda(&mut self) -> Result<f32>

See also

fn set_use_post_processing(&mut self, _use_post_proc: bool) -> Result<()>

Sets whether the fastGlobalSmootherFilter() post-processing is employed. It is turned on by default.

fn get_use_post_processing(&mut self) -> Result<bool>

See also

fn set_fgs_lambda(&mut self, _lambda: f32) -> Result<()>

Sets the respective fastGlobalSmootherFilter() parameter.

fn get_fgs_lambda(&mut self) -> Result<f32>

See also

fn set_fgs_sigma(&mut self, _sigma: f32) -> Result<()>

See also

fn get_fgs_sigma(&mut self) -> Result<f32>

See also

impl EdgeAwareInterpolatorTraitConst for Ptr<EdgeAwareInterpolator>

fn as_raw_EdgeAwareInterpolator(&self) -> *const c_void

impl EdgeBoxesTrait for Ptr<EdgeBoxes>

fn as_raw_mut_EdgeBoxes(&mut self) -> *mut c_void

fn get_bounding_boxes( &mut self, edge_map: &impl ToInputArray, orientation_map: &impl ToInputArray, boxes: &mut Vector<Rect>, scores: &mut impl ToOutputArray ) -> Result<()>

Returns array containing proposal boxes.

fn get_bounding_boxes_def( &mut self, edge_map: &impl ToInputArray, orientation_map: &impl ToInputArray, boxes: &mut Vector<Rect> ) -> Result<()>

Returns array containing proposal boxes.

fn set_alpha(&mut self, value: f32) -> Result<()>

Sets the step size of sliding window search.

fn set_beta(&mut self, value: f32) -> Result<()>

Sets the nms threshold for object proposals.

fn set_eta(&mut self, value: f32) -> Result<()>

Sets the adaptation rate for nms threshold.

fn set_min_score(&mut self, value: f32) -> Result<()>

Sets the min score of boxes to detect.

fn set_max_boxes(&mut self, value: i32) -> Result<()>

Sets max number of boxes to detect.

fn set_edge_min_mag(&mut self, value: f32) -> Result<()>

Sets the edge min magnitude.

fn set_edge_merge_thr(&mut self, value: f32) -> Result<()>

Sets the edge merge threshold.

fn set_cluster_min_mag(&mut self, value: f32) -> Result<()>

Sets the cluster min magnitude.

fn set_max_aspect_ratio(&mut self, value: f32) -> Result<()>

Sets the max aspect ratio of boxes.

fn set_min_box_area(&mut self, value: f32) -> Result<()>

Sets the minimum area of boxes.

fn set_gamma(&mut self, value: f32) -> Result<()>

Sets the affinity sensitivity

fn set_kappa(&mut self, value: f32) -> Result<()>

Sets the scale sensitivity.

impl EdgeBoxesTraitConst for Ptr<EdgeBoxes>

fn as_raw_EdgeBoxes(&self) -> *const c_void

fn get_alpha(&self) -> Result<f32>

Returns the step size of sliding window search.

fn get_beta(&self) -> Result<f32>

Returns the nms threshold for object proposals.

fn get_eta(&self) -> Result<f32>

Returns adaptation rate for nms threshold.

fn get_min_score(&self) -> Result<f32>

Returns the min score of boxes to detect.

fn get_max_boxes(&self) -> Result<i32>

Returns the max number of boxes to detect.

fn get_edge_min_mag(&self) -> Result<f32>

Returns the edge min magnitude.

fn get_edge_merge_thr(&self) -> Result<f32>

Returns the edge merge threshold.

fn get_cluster_min_mag(&self) -> Result<f32>

Returns the cluster min magnitude.

fn get_max_aspect_ratio(&self) -> Result<f32>

Returns the max aspect ratio of boxes.

fn get_min_box_area(&self) -> Result<f32>

Returns the minimum area of boxes.

fn get_gamma(&self) -> Result<f32>

Returns the affinity sensitivity.

fn get_kappa(&self) -> Result<f32>

Returns the scale sensitivity.

impl EdgeDrawingTrait for Ptr<EdgeDrawing>

fn as_raw_mut_EdgeDrawing(&mut self) -> *mut c_void

fn set_params(&mut self, val: EdgeDrawing_Params)

fn detect_edges(&mut self, src: &impl ToInputArray) -> Result<()>

Detects edges in a grayscale image and prepares them to detect lines and ellipses.

fn get_edge_image(&mut self, dst: &mut impl ToOutputArray) -> Result<()>

returns Edge Image prepared by detectEdges() function.

fn get_gradient_image(&mut self, dst: &mut impl ToOutputArray) -> Result<()>

returns Gradient Image prepared by detectEdges() function.

fn get_segments(&mut self) -> Result<Vector<Vector<Point>>>

Returns std::vector<std::vector> of detected edge segments, see detectEdges()

fn detect_lines(&mut self, lines: &mut impl ToOutputArray) -> Result<()>

Detects lines.

fn detect_ellipses(&mut self, ellipses: &mut impl ToOutputArray) -> Result<()>

Detects circles and ellipses.

fn set_params_1(&mut self, parameters: EdgeDrawing_Params) -> Result<()>

sets parameters.

impl EdgeDrawingTraitConst for Ptr<EdgeDrawing>

fn as_raw_EdgeDrawing(&self) -> *const c_void

fn params(&self) -> EdgeDrawing_Params

fn get_segment_indices_of_lines(&self) -> Result<Vector<i32>>

Returns for each line found in detectLines() its edge segment index in getSegments()

impl EigenFaceRecognizerTrait for Ptr<EigenFaceRecognizer>

fn as_raw_mut_EigenFaceRecognizer(&mut self) -> *mut c_void

impl EigenFaceRecognizerTraitConst for Ptr<EigenFaceRecognizer>

fn as_raw_EigenFaceRecognizer(&self) -> *const c_void

impl EinsumLayerTrait for Ptr<EinsumLayer>

fn as_raw_mut_EinsumLayer(&mut self) -> *mut c_void

impl EinsumLayerTraitConst for Ptr<EinsumLayer>

fn as_raw_EinsumLayer(&self) -> *const c_void

impl EltwiseLayerInt8Trait for Ptr<EltwiseLayerInt8>

fn as_raw_mut_EltwiseLayerInt8(&mut self) -> *mut c_void

impl EltwiseLayerInt8TraitConst for Ptr<EltwiseLayerInt8>

fn as_raw_EltwiseLayerInt8(&self) -> *const c_void

impl EltwiseLayerTrait for Ptr<EltwiseLayer>

fn as_raw_mut_EltwiseLayer(&mut self) -> *mut c_void

impl EltwiseLayerTraitConst for Ptr<EltwiseLayer>

fn as_raw_EltwiseLayer(&self) -> *const c_void

impl ErfLayerTrait for Ptr<ErfLayer>

fn as_raw_mut_ErfLayer(&mut self) -> *mut c_void

impl ErfLayerTraitConst for Ptr<ErfLayer>

fn as_raw_ErfLayer(&self) -> *const c_void

impl EstimateParametersTrait for Ptr<EstimateParameters>

fn as_raw_mut_EstimateParameters(&mut self) -> *mut c_void

fn set_pattern(&mut self, val: PatternPositionType)

fn set_use_extrinsic_guess(&mut self, val: bool)

fn set_solve_pnp_method(&mut self, val: i32)

impl EstimateParametersTraitConst for Ptr<EstimateParameters>

fn as_raw_EstimateParameters(&self) -> *const c_void

fn pattern(&self) -> PatternPositionType

fn use_extrinsic_guess(&self) -> bool

fn solve_pnp_method(&self) -> i32

impl ExpLayerTrait for Ptr<ExpLayer>

fn as_raw_mut_ExpLayer(&mut self) -> *mut c_void

fn set_base(&mut self, val: f32)

fn set_scale(&mut self, val: f32)

fn set_shift(&mut self, val: f32)

impl ExpLayerTraitConst for Ptr<ExpLayer>

fn as_raw_ExpLayer(&self) -> *const c_void

fn base(&self) -> f32

fn scale(&self) -> f32

fn shift(&self) -> f32

impl ExpandLayerTrait for Ptr<ExpandLayer>

fn as_raw_mut_ExpandLayer(&mut self) -> *mut c_void

impl ExpandLayerTraitConst for Ptr<ExpandLayer>

fn as_raw_ExpandLayer(&self) -> *const c_void

impl FREAKTrait for Ptr<FREAK>

fn as_raw_mut_FREAK(&mut self) -> *mut c_void

fn set_orientation_normalized( &mut self, orientation_normalized: bool ) -> Result<()>

fn set_scale_normalized(&mut self, scale_normalized: bool) -> Result<()>

fn set_pattern_scale(&mut self, pattern_scale: f64) -> Result<()>

fn set_n_octaves(&mut self, n_octaves: i32) -> Result<()>

impl FREAKTraitConst for Ptr<FREAK>

fn as_raw_FREAK(&self) -> *const c_void

fn get_orientation_normalized(&self) -> Result<bool>

fn get_scale_normalized(&self) -> Result<bool>

fn get_pattern_scale(&self) -> Result<f64>

fn get_n_octaves(&self) -> Result<i32>

fn get_default_name(&self) -> Result<String>

impl FaceDetectorYNTrait for Ptr<FaceDetectorYN>

fn as_raw_mut_FaceDetectorYN(&mut self) -> *mut c_void

fn set_input_size(&mut self, input_size: Size) -> Result<()>

Set the size for the network input, which overwrites the input size of creating model. Call this method when the size of input image does not match the input size when creating model

fn get_input_size(&mut self) -> Result<Size>

fn set_score_threshold(&mut self, score_threshold: f32) -> Result<()>

Set the score threshold to filter out bounding boxes of score less than the given value

fn get_score_threshold(&mut self) -> Result<f32>

fn set_nms_threshold(&mut self, nms_threshold: f32) -> Result<()>

Set the Non-maximum-suppression threshold to suppress bounding boxes that have IoU greater than the given value

fn get_nms_threshold(&mut self) -> Result<f32>

fn set_top_k(&mut self, top_k: i32) -> Result<()>

Set the number of bounding boxes preserved before NMS

fn get_top_k(&mut self) -> Result<i32>

fn detect( &mut self, image: &impl ToInputArray, faces: &mut impl ToOutputArray ) -> Result<i32>

Detects faces in the input image. Following is an example output.

impl FaceDetectorYNTraitConst for Ptr<FaceDetectorYN>

fn as_raw_FaceDetectorYN(&self) -> *const c_void

impl FaceRecognizerSFTrait for Ptr<FaceRecognizerSF>

fn as_raw_mut_FaceRecognizerSF(&mut self) -> *mut c_void

fn feature( &mut self, aligned_img: &impl ToInputArray, face_feature: &mut impl ToOutputArray ) -> Result<()>

Extracting face feature from aligned image

impl FaceRecognizerSFTraitConst for Ptr<FaceRecognizerSF>

fn as_raw_FaceRecognizerSF(&self) -> *const c_void

fn align_crop( &self, src_img: &impl ToInputArray, face_box: &impl ToInputArray, aligned_img: &mut impl ToOutputArray ) -> Result<()>

Aligning image to put face on the standard position

fn match_( &self, face_feature1: &impl ToInputArray, face_feature2: &impl ToInputArray, dis_type: i32 ) -> Result<f64>

Calculating the distance between two face features

fn match__def( &self, face_feature1: &impl ToInputArray, face_feature2: &impl ToInputArray ) -> Result<f64>

Calculating the distance between two face features

impl FaceRecognizerTrait for Ptr<BasicFaceRecognizer>

fn as_raw_mut_FaceRecognizer(&mut self) -> *mut c_void

fn train( &mut self, src: &impl ToInputArray, labels: &impl ToInputArray ) -> Result<()>

Trains a FaceRecognizer with given data and associated labels.

fn update( &mut self, src: &impl ToInputArray, labels: &impl ToInputArray ) -> Result<()>

Updates a FaceRecognizer with given data and associated labels.

fn read(&mut self, filename: &str) -> Result<()>

Loads a FaceRecognizer and its model state.

fn read_1(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Loads a FaceRecognizer and its model state.

fn set_label_info(&mut self, label: i32, str_info: &str) -> Result<()>

Sets string info for the specified model’s label.

fn set_threshold(&mut self, val: f64) -> Result<()>

Sets threshold of model

impl FaceRecognizerTrait for Ptr<EigenFaceRecognizer>

fn as_raw_mut_FaceRecognizer(&mut self) -> *mut c_void

fn train( &mut self, src: &impl ToInputArray, labels: &impl ToInputArray ) -> Result<()>

Trains a FaceRecognizer with given data and associated labels.

fn update( &mut self, src: &impl ToInputArray, labels: &impl ToInputArray ) -> Result<()>

Updates a FaceRecognizer with given data and associated labels.

fn read(&mut self, filename: &str) -> Result<()>

Loads a FaceRecognizer and its model state.

fn read_1(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Loads a FaceRecognizer and its model state.

fn set_label_info(&mut self, label: i32, str_info: &str) -> Result<()>

Sets string info for the specified model’s label.

fn set_threshold(&mut self, val: f64) -> Result<()>

Sets threshold of model

impl FaceRecognizerTrait for Ptr<FaceRecognizer>

fn as_raw_mut_FaceRecognizer(&mut self) -> *mut c_void

fn train( &mut self, src: &impl ToInputArray, labels: &impl ToInputArray ) -> Result<()>

Trains a FaceRecognizer with given data and associated labels.

fn update( &mut self, src: &impl ToInputArray, labels: &impl ToInputArray ) -> Result<()>

Updates a FaceRecognizer with given data and associated labels.

fn read(&mut self, filename: &str) -> Result<()>

Loads a FaceRecognizer and its model state.

fn read_1(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Loads a FaceRecognizer and its model state.

fn set_label_info(&mut self, label: i32, str_info: &str) -> Result<()>

Sets string info for the specified model’s label.

fn set_threshold(&mut self, val: f64) -> Result<()>

Sets threshold of model

impl FaceRecognizerTrait for Ptr<FisherFaceRecognizer>

fn as_raw_mut_FaceRecognizer(&mut self) -> *mut c_void

fn train( &mut self, src: &impl ToInputArray, labels: &impl ToInputArray ) -> Result<()>

Trains a FaceRecognizer with given data and associated labels.

fn update( &mut self, src: &impl ToInputArray, labels: &impl ToInputArray ) -> Result<()>

Updates a FaceRecognizer with given data and associated labels.

fn read(&mut self, filename: &str) -> Result<()>

Loads a FaceRecognizer and its model state.

fn read_1(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Loads a FaceRecognizer and its model state.

fn set_label_info(&mut self, label: i32, str_info: &str) -> Result<()>

Sets string info for the specified model’s label.

fn set_threshold(&mut self, val: f64) -> Result<()>

Sets threshold of model

impl FaceRecognizerTrait for Ptr<LBPHFaceRecognizer>

fn as_raw_mut_FaceRecognizer(&mut self) -> *mut c_void

fn train( &mut self, src: &impl ToInputArray, labels: &impl ToInputArray ) -> Result<()>

Trains a FaceRecognizer with given data and associated labels.

fn update( &mut self, src: &impl ToInputArray, labels: &impl ToInputArray ) -> Result<()>

Updates a FaceRecognizer with given data and associated labels.

fn read(&mut self, filename: &str) -> Result<()>

Loads a FaceRecognizer and its model state.

fn read_1(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Loads a FaceRecognizer and its model state.

fn set_label_info(&mut self, label: i32, str_info: &str) -> Result<()>

Sets string info for the specified model’s label.

fn set_threshold(&mut self, val: f64) -> Result<()>

Sets threshold of model

impl FaceRecognizerTraitConst for Ptr<BasicFaceRecognizer>

fn as_raw_FaceRecognizer(&self) -> *const c_void

fn predict_label(&self, src: &impl ToInputArray) -> Result<i32>

Predicts a label and associated confidence (e.g. distance) for a given input image.

fn predict( &self, src: &impl ToInputArray, label: &mut i32, confidence: &mut f64 ) -> Result<()>

Predicts a label and associated confidence (e.g. distance) for a given input image.

fn predict_collect( &self, src: &impl ToInputArray, collector: Ptr<PredictCollector> ) -> Result<()>

if implemented - send all result of prediction to collector that can be used for somehow custom result handling

fn write(&self, filename: &str) -> Result<()>

Saves a FaceRecognizer and its model state.

fn write_1(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Saves a FaceRecognizer and its model state.

fn empty(&self) -> Result<bool>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

fn get_label_info(&self, label: i32) -> Result<String>

Gets string information by label.

fn get_labels_by_string(&self, str: &str) -> Result<Vector<i32>>

Gets vector of labels by string.

fn get_threshold(&self) -> Result<f64>

threshold parameter accessor - required for default BestMinDist collector

impl FaceRecognizerTraitConst for Ptr<EigenFaceRecognizer>

fn as_raw_FaceRecognizer(&self) -> *const c_void

fn predict_label(&self, src: &impl ToInputArray) -> Result<i32>

Predicts a label and associated confidence (e.g. distance) for a given input image.

fn predict( &self, src: &impl ToInputArray, label: &mut i32, confidence: &mut f64 ) -> Result<()>

Predicts a label and associated confidence (e.g. distance) for a given input image.

fn predict_collect( &self, src: &impl ToInputArray, collector: Ptr<PredictCollector> ) -> Result<()>

if implemented - send all result of prediction to collector that can be used for somehow custom result handling

fn write(&self, filename: &str) -> Result<()>

Saves a FaceRecognizer and its model state.

fn write_1(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Saves a FaceRecognizer and its model state.

fn empty(&self) -> Result<bool>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

fn get_label_info(&self, label: i32) -> Result<String>

Gets string information by label.

fn get_labels_by_string(&self, str: &str) -> Result<Vector<i32>>

Gets vector of labels by string.

fn get_threshold(&self) -> Result<f64>

threshold parameter accessor - required for default BestMinDist collector

impl FaceRecognizerTraitConst for Ptr<FaceRecognizer>

fn as_raw_FaceRecognizer(&self) -> *const c_void

fn predict_label(&self, src: &impl ToInputArray) -> Result<i32>

Predicts a label and associated confidence (e.g. distance) for a given input image.

fn predict( &self, src: &impl ToInputArray, label: &mut i32, confidence: &mut f64 ) -> Result<()>

Predicts a label and associated confidence (e.g. distance) for a given input image.

fn predict_collect( &self, src: &impl ToInputArray, collector: Ptr<PredictCollector> ) -> Result<()>

if implemented - send all result of prediction to collector that can be used for somehow custom result handling

fn write(&self, filename: &str) -> Result<()>

Saves a FaceRecognizer and its model state.

fn write_1(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Saves a FaceRecognizer and its model state.

fn empty(&self) -> Result<bool>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

fn get_label_info(&self, label: i32) -> Result<String>

Gets string information by label.

fn get_labels_by_string(&self, str: &str) -> Result<Vector<i32>>

Gets vector of labels by string.

fn get_threshold(&self) -> Result<f64>

threshold parameter accessor - required for default BestMinDist collector

impl FaceRecognizerTraitConst for Ptr<FisherFaceRecognizer>

fn as_raw_FaceRecognizer(&self) -> *const c_void

fn predict_label(&self, src: &impl ToInputArray) -> Result<i32>

Predicts a label and associated confidence (e.g. distance) for a given input image.

fn predict( &self, src: &impl ToInputArray, label: &mut i32, confidence: &mut f64 ) -> Result<()>

Predicts a label and associated confidence (e.g. distance) for a given input image.

fn predict_collect( &self, src: &impl ToInputArray, collector: Ptr<PredictCollector> ) -> Result<()>

if implemented - send all result of prediction to collector that can be used for somehow custom result handling

fn write(&self, filename: &str) -> Result<()>

Saves a FaceRecognizer and its model state.

fn write_1(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Saves a FaceRecognizer and its model state.

fn empty(&self) -> Result<bool>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

fn get_label_info(&self, label: i32) -> Result<String>

Gets string information by label.

fn get_labels_by_string(&self, str: &str) -> Result<Vector<i32>>

Gets vector of labels by string.

fn get_threshold(&self) -> Result<f64>

threshold parameter accessor - required for default BestMinDist collector

impl FaceRecognizerTraitConst for Ptr<LBPHFaceRecognizer>

fn as_raw_FaceRecognizer(&self) -> *const c_void

fn predict_label(&self, src: &impl ToInputArray) -> Result<i32>

Predicts a label and associated confidence (e.g. distance) for a given input image.

fn predict( &self, src: &impl ToInputArray, label: &mut i32, confidence: &mut f64 ) -> Result<()>

Predicts a label and associated confidence (e.g. distance) for a given input image.

fn predict_collect( &self, src: &impl ToInputArray, collector: Ptr<PredictCollector> ) -> Result<()>

if implemented - send all result of prediction to collector that can be used for somehow custom result handling

fn write(&self, filename: &str) -> Result<()>

Saves a FaceRecognizer and its model state.

fn write_1(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Saves a FaceRecognizer and its model state.

fn empty(&self) -> Result<bool>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

fn get_label_info(&self, label: i32) -> Result<String>

Gets string information by label.

fn get_labels_by_string(&self, str: &str) -> Result<Vector<i32>>

Gets vector of labels by string.

fn get_threshold(&self) -> Result<f64>

threshold parameter accessor - required for default BestMinDist collector

impl FacemarkAAMTrait for Ptr<FacemarkAAM>

fn as_raw_mut_FacemarkAAM(&mut self) -> *mut c_void

fn fit_config( &mut self, image: &impl ToInputArray, roi: &impl ToInputArray, _landmarks: &mut impl ToOutputArray, runtime_params: &Vector<FacemarkAAM_Config> ) -> Result<bool>

overload with additional Config structures

impl FacemarkAAMTraitConst for Ptr<FacemarkAAM>

fn as_raw_FacemarkAAM(&self) -> *const c_void

impl FacemarkKazemiTrait for Ptr<FacemarkKazemi>

fn as_raw_mut_FacemarkKazemi(&mut self) -> *mut c_void

fn training( &mut self, images: &mut Vector<Mat>, landmarks: &mut Vector<Vector<Point2f>>, configfile: &str, scale: Size, model_filename: &str ) -> Result<bool>

This function is used to train the model using gradient boosting to get a cascade of regressors which can then be used to predict shape.

fn training_def( &mut self, images: &mut Vector<Mat>, landmarks: &mut Vector<Vector<Point2f>>, configfile: &str, scale: Size ) -> Result<bool>

This function is used to train the model using gradient boosting to get a cascade of regressors which can then be used to predict shape.

fn set_face_detector( &mut self, f: Option<Box<dyn FnMut(*const c_void, *const c_void) -> bool + Send + Sync + 'static>> ) -> Result<bool>

set the custom face detector

fn get_faces( &mut self, image: &impl ToInputArray, faces: &mut impl ToOutputArray ) -> Result<bool>

get faces using the custom detector

impl FacemarkKazemiTraitConst for Ptr<FacemarkKazemi>

fn as_raw_FacemarkKazemi(&self) -> *const c_void

impl FacemarkLBFTrait for Ptr<FacemarkLBF>

fn as_raw_mut_FacemarkLBF(&mut self) -> *mut c_void

impl FacemarkLBFTraitConst for Ptr<FacemarkLBF>

fn as_raw_FacemarkLBF(&self) -> *const c_void

impl FacemarkTrainTrait for Ptr<FacemarkAAM>

fn as_raw_mut_FacemarkTrain(&mut self) -> *mut c_void

fn add_training_sample( &mut self, image: &impl ToInputArray, landmarks: &impl ToInputArray ) -> Result<bool>

Add one training sample to the trainer.

unsafe fn training(&mut self, parameters: *mut c_void) -> Result<()>

Trains a Facemark algorithm using the given dataset. Before the training process, training samples should be added to the trainer using face::addTrainingSample function.

fn training_def(&mut self) -> Result<()>

Trains a Facemark algorithm using the given dataset. Before the training process, training samples should be added to the trainer using face::addTrainingSample function.

fn set_face_detector(&mut self, detector: FN_FaceDetector) -> Result<bool>

Set a user defined face detector for the Facemark algorithm.

fn get_faces( &mut self, image: &impl ToInputArray, faces: &mut impl ToOutputArray ) -> Result<bool>

Detect faces from a given image using default or user defined face detector. Some Algorithm might not provide a default face detector.

unsafe fn get_data(&mut self, items: *mut c_void) -> Result<bool>

Get data from an algorithm

fn get_data_def(&mut self) -> Result<bool>

Get data from an algorithm

impl FacemarkTrainTrait for Ptr<FacemarkLBF>

fn as_raw_mut_FacemarkTrain(&mut self) -> *mut c_void

fn add_training_sample( &mut self, image: &impl ToInputArray, landmarks: &impl ToInputArray ) -> Result<bool>

Add one training sample to the trainer.

unsafe fn training(&mut self, parameters: *mut c_void) -> Result<()>

Trains a Facemark algorithm using the given dataset. Before the training process, training samples should be added to the trainer using face::addTrainingSample function.

fn training_def(&mut self) -> Result<()>

Trains a Facemark algorithm using the given dataset. Before the training process, training samples should be added to the trainer using face::addTrainingSample function.

fn set_face_detector(&mut self, detector: FN_FaceDetector) -> Result<bool>

Set a user defined face detector for the Facemark algorithm.

fn get_faces( &mut self, image: &impl ToInputArray, faces: &mut impl ToOutputArray ) -> Result<bool>

Detect faces from a given image using default or user defined face detector. Some Algorithm might not provide a default face detector.

unsafe fn get_data(&mut self, items: *mut c_void) -> Result<bool>

Get data from an algorithm

fn get_data_def(&mut self) -> Result<bool>

Get data from an algorithm

impl FacemarkTrainTrait for Ptr<FacemarkTrain>

fn as_raw_mut_FacemarkTrain(&mut self) -> *mut c_void

fn add_training_sample( &mut self, image: &impl ToInputArray, landmarks: &impl ToInputArray ) -> Result<bool>

Add one training sample to the trainer.

unsafe fn training(&mut self, parameters: *mut c_void) -> Result<()>

Trains a Facemark algorithm using the given dataset. Before the training process, training samples should be added to the trainer using face::addTrainingSample function.

fn training_def(&mut self) -> Result<()>

Trains a Facemark algorithm using the given dataset. Before the training process, training samples should be added to the trainer using face::addTrainingSample function.

fn set_face_detector(&mut self, detector: FN_FaceDetector) -> Result<bool>

Set a user defined face detector for the Facemark algorithm.

fn get_faces( &mut self, image: &impl ToInputArray, faces: &mut impl ToOutputArray ) -> Result<bool>

Detect faces from a given image using default or user defined face detector. Some Algorithm might not provide a default face detector.

unsafe fn get_data(&mut self, items: *mut c_void) -> Result<bool>

Get data from an algorithm

fn get_data_def(&mut self) -> Result<bool>

Get data from an algorithm

impl FacemarkTrainTraitConst for Ptr<FacemarkAAM>

fn as_raw_FacemarkTrain(&self) -> *const c_void

impl FacemarkTrainTraitConst for Ptr<FacemarkLBF>

fn as_raw_FacemarkTrain(&self) -> *const c_void

impl FacemarkTrainTraitConst for Ptr<FacemarkTrain>

fn as_raw_FacemarkTrain(&self) -> *const c_void

impl FacemarkTrait for Ptr<Facemark>

fn as_raw_mut_Facemark(&mut self) -> *mut c_void

fn load_model(&mut self, model: &str) -> Result<()>

A function to load the trained model before the fitting process.

fn fit( &mut self, image: &impl ToInputArray, faces: &impl ToInputArray, landmarks: &mut impl ToOutputArray ) -> Result<bool>

Detect facial landmarks from an image.

impl FacemarkTrait for Ptr<FacemarkAAM>

fn as_raw_mut_Facemark(&mut self) -> *mut c_void

fn load_model(&mut self, model: &str) -> Result<()>

A function to load the trained model before the fitting process.

fn fit( &mut self, image: &impl ToInputArray, faces: &impl ToInputArray, landmarks: &mut impl ToOutputArray ) -> Result<bool>

Detect facial landmarks from an image.

impl FacemarkTrait for Ptr<FacemarkKazemi>

fn as_raw_mut_Facemark(&mut self) -> *mut c_void

fn load_model(&mut self, model: &str) -> Result<()>

A function to load the trained model before the fitting process.

fn fit( &mut self, image: &impl ToInputArray, faces: &impl ToInputArray, landmarks: &mut impl ToOutputArray ) -> Result<bool>

Detect facial landmarks from an image.

impl FacemarkTrait for Ptr<FacemarkLBF>

fn as_raw_mut_Facemark(&mut self) -> *mut c_void

fn load_model(&mut self, model: &str) -> Result<()>

A function to load the trained model before the fitting process.

fn fit( &mut self, image: &impl ToInputArray, faces: &impl ToInputArray, landmarks: &mut impl ToOutputArray ) -> Result<bool>

Detect facial landmarks from an image.

impl FacemarkTrait for Ptr<FacemarkTrain>

fn as_raw_mut_Facemark(&mut self) -> *mut c_void

fn load_model(&mut self, model: &str) -> Result<()>

A function to load the trained model before the fitting process.

fn fit( &mut self, image: &impl ToInputArray, faces: &impl ToInputArray, landmarks: &mut impl ToOutputArray ) -> Result<bool>

Detect facial landmarks from an image.

impl FacemarkTraitConst for Ptr<Facemark>

fn as_raw_Facemark(&self) -> *const c_void

impl FacemarkTraitConst for Ptr<FacemarkAAM>

fn as_raw_Facemark(&self) -> *const c_void

impl FacemarkTraitConst for Ptr<FacemarkKazemi>

fn as_raw_Facemark(&self) -> *const c_void

impl FacemarkTraitConst for Ptr<FacemarkLBF>

fn as_raw_Facemark(&self) -> *const c_void

impl FacemarkTraitConst for Ptr<FacemarkTrain>

fn as_raw_Facemark(&self) -> *const c_void

impl FarnebackOpticalFlowTrait for Ptr<FarnebackOpticalFlow>

fn as_raw_mut_FarnebackOpticalFlow(&mut self) -> *mut c_void

fn set_num_levels(&mut self, num_levels: i32) -> Result<()>

fn set_pyr_scale(&mut self, pyr_scale: f64) -> Result<()>

fn set_fast_pyramids(&mut self, fast_pyramids: bool) -> Result<()>

fn set_win_size(&mut self, win_size: i32) -> Result<()>

fn set_num_iters(&mut self, num_iters: i32) -> Result<()>

fn set_poly_n(&mut self, poly_n: i32) -> Result<()>

fn set_poly_sigma(&mut self, poly_sigma: f64) -> Result<()>

fn set_flags(&mut self, flags: i32) -> Result<()>

impl FarnebackOpticalFlowTraitConst for Ptr<FarnebackOpticalFlow>

fn as_raw_FarnebackOpticalFlow(&self) -> *const c_void

fn get_num_levels(&self) -> Result<i32>

fn get_pyr_scale(&self) -> Result<f64>

fn get_fast_pyramids(&self) -> Result<bool>

fn get_win_size(&self) -> Result<i32>

fn get_num_iters(&self) -> Result<i32>

fn get_poly_n(&self) -> Result<i32>

fn get_poly_sigma(&self) -> Result<f64>

fn get_flags(&self) -> Result<i32>

impl FastBilateralSolverFilterTrait for Ptr<FastBilateralSolverFilter>

fn as_raw_mut_FastBilateralSolverFilter(&mut self) -> *mut c_void

fn filter( &mut self, src: &impl ToInputArray, confidence: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Apply smoothing operation to the source image.

impl FastBilateralSolverFilterTraitConst for Ptr<FastBilateralSolverFilter>

fn as_raw_FastBilateralSolverFilter(&self) -> *const c_void

impl FastFeatureDetectorTrait for Ptr<FastFeatureDetector>

fn as_raw_mut_FastFeatureDetector(&mut self) -> *mut c_void

fn set_threshold(&mut self, threshold: i32) -> Result<()>

fn set_nonmax_suppression(&mut self, f: bool) -> Result<()>

fn set_type(&mut self, typ: FastFeatureDetector_DetectorType) -> Result<()>

impl FastFeatureDetectorTraitConst for Ptr<FastFeatureDetector>

fn as_raw_FastFeatureDetector(&self) -> *const c_void

fn get_threshold(&self) -> Result<i32>

fn get_nonmax_suppression(&self) -> Result<bool>

fn get_type(&self) -> Result<FastFeatureDetector_DetectorType>

fn get_default_name(&self) -> Result<String>

impl FastGlobalSmootherFilterTrait for Ptr<FastGlobalSmootherFilter>

fn as_raw_mut_FastGlobalSmootherFilter(&mut self) -> *mut c_void

fn filter( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Apply smoothing operation to the source image.

impl FastGlobalSmootherFilterTraitConst for Ptr<FastGlobalSmootherFilter>

fn as_raw_FastGlobalSmootherFilter(&self) -> *const c_void

impl FastICPOdometryTrait for Ptr<FastICPOdometry>

fn as_raw_mut_FastICPOdometry(&mut self) -> *mut c_void

fn set_camera_matrix(&mut self, val: &impl MatTraitConst) -> Result<()>

fn set_max_dist_diff(&mut self, val: f32) -> Result<()>

fn set_angle_threshold(&mut self, f: f32) -> Result<()>

fn set_sigma_depth(&mut self, f: f32) -> Result<()>

fn set_sigma_spatial(&mut self, f: f32) -> Result<()>

fn set_kernel_size(&mut self, f: i32) -> Result<()>

fn set_iteration_counts(&mut self, val: &impl MatTraitConst) -> Result<()>

fn set_transform_type(&mut self, val: i32) -> Result<()>

impl FastICPOdometryTraitConst for Ptr<FastICPOdometry>

fn as_raw_FastICPOdometry(&self) -> *const c_void

fn prepare_frame_cache( &self, frame: &mut Ptr<OdometryFrame>, cache_type: i32 ) -> Result<Size>

fn get_camera_matrix(&self) -> Result<Mat>

fn get_max_dist_diff(&self) -> Result<f64>

fn get_angle_threshold(&self) -> Result<f32>

fn get_sigma_depth(&self) -> Result<f32>

fn get_sigma_spatial(&self) -> Result<f32>

fn get_kernel_size(&self) -> Result<i32>

fn get_iteration_counts(&self) -> Result<Mat>

fn get_transform_type(&self) -> Result<i32>

impl FastLineDetectorTrait for Ptr<FastLineDetector>

fn as_raw_mut_FastLineDetector(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, lines: &mut impl ToOutputArray ) -> Result<()>

@example fld_lines.cpp An example using the FastLineDetector

fn draw_segments( &mut self, image: &mut impl ToInputOutputArray, lines: &impl ToInputArray, draw_arrow: bool, linecolor: Scalar, linethickness: i32 ) -> Result<()>

Draws the line segments on a given image.

fn draw_segments_def( &mut self, image: &mut impl ToInputOutputArray, lines: &impl ToInputArray ) -> Result<()>

Draws the line segments on a given image.

impl FastLineDetectorTraitConst for Ptr<FastLineDetector>

fn as_raw_FastLineDetector(&self) -> *const c_void

impl Feature2DTrait for Ptr<AKAZE>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<AffineFeature>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<AffineFeature2D>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<AgastFeatureDetector>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<BEBLID>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<BRISK>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<BoostDesc>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<BriefDescriptorExtractor>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<CUDA_FastFeatureDetector>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<CUDA_Feature2DAsync>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<CUDA_ORB>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<DAISY>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<FREAK>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<FastFeatureDetector>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<Feature2D>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<GFTTDetector>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<HarrisLaplaceFeatureDetector>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<KAZE>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<LATCH>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<LUCID>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<MSDDetector>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<MSER>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<ORB>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<SIFT>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<SURF>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<SimpleBlobDetector>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<StarDetector>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<TBMR>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<TEBLID>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTrait for Ptr<VGG>

fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>> ) -> Result<()>

@overload

fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes the descriptors

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>

Detects keypoints and computes the descriptors

fn read(&mut self, file_name: &str) -> Result<()>

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTraitConst for Ptr<AKAZE>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<AffineFeature>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<AffineFeature2D>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<AgastFeatureDetector>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<BEBLID>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<BRISK>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<BoostDesc>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<BriefDescriptorExtractor>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<CUDA_FastFeatureDetector>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<CUDA_Feature2DAsync>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<CUDA_ORB>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<DAISY>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<FREAK>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<FastFeatureDetector>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<Feature2D>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<GFTTDetector>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<HarrisLaplaceFeatureDetector>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<KAZE>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<LATCH>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<LUCID>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<MSDDetector>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<MSER>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<ORB>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<SIFT>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<SURF>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<SimpleBlobDetector>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<StarDetector>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<TBMR>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<TEBLID>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl Feature2DTraitConst for Ptr<VGG>

fn as_raw_Feature2D(&self) -> *const c_void

fn descriptor_size(&self) -> Result<i32>

fn descriptor_type(&self) -> Result<i32>

fn default_norm(&self) -> Result<i32>

fn write(&self, file_name: &str) -> Result<()>

fn write_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn empty(&self) -> Result<bool>

Return true if detector object is empty

fn get_default_name(&self) -> Result<String>

fn write_to_storage_with_name( &self, fs: &mut impl FileStorageTrait, name: &str ) -> Result<()>

fn write_to_storage_ptr_with_name( &self, fs: &Ptr<FileStorage>, name: &str ) -> Result<()>

impl FileStorageTrait for Ptr<FileStorage>

fn as_raw_mut_FileStorage(&mut self) -> *mut c_void

fn set_state(&mut self, val: i32)

fn set_elname(&mut self, val: &str)

fn open(&mut self, filename: &str, flags: i32, encoding: &str) -> Result<bool>

Opens a file.

fn open_def(&mut self, filename: &str, flags: i32) -> Result<bool>

Opens a file.

fn release(&mut self) -> Result<()>

Closes the file and releases all the memory buffers.

fn release_and_get_string(&mut self) -> Result<String>

Closes the file and releases all the memory buffers.

fn write_i32(&mut self, name: &str, val: i32) -> Result<()>

Simplified writing API to use with bindings.

fn write_f64(&mut self, name: &str, val: f64) -> Result<()>

Simplified writing API to use with bindings.

fn write_str(&mut self, name: &str, val: &str) -> Result<()>

Simplified writing API to use with bindings.

fn write_mat(&mut self, name: &str, val: &impl MatTraitConst) -> Result<()>

Simplified writing API to use with bindings.

fn write_str_vec(&mut self, name: &str, val: &Vector<String>) -> Result<()>

Simplified writing API to use with bindings.

fn write_raw(&mut self, fmt: &str, vec: &mut [u8]) -> Result<()>

Writes multiple numbers.

fn write_comment(&mut self, comment: &str, append: bool) -> Result<()>

Writes a comment.

fn write_comment_def(&mut self, comment: &str) -> Result<()>

Writes a comment.

fn start_write_struct( &mut self, name: &str, flags: i32, type_name: &str ) -> Result<()>

Starts to write a nested structure (sequence or a mapping).

fn start_write_struct_def(&mut self, name: &str, flags: i32) -> Result<()>

Starts to write a nested structure (sequence or a mapping).

fn end_write_struct(&mut self) -> Result<()>

Finishes writing nested structure (should pair startWriteStruct())

impl FileStorageTraitConst for Ptr<FileStorage>

fn as_raw_FileStorage(&self) -> *const c_void

fn state(&self) -> i32

fn elname(&self) -> String

fn is_opened(&self) -> Result<bool>

Checks whether the file is opened.

fn get_first_top_level_node(&self) -> Result<FileNode>

Returns the first element of the top-level mapping.

fn root(&self, streamidx: i32) -> Result<FileNode>

Returns the top-level mapping

fn root_def(&self) -> Result<FileNode>

Returns the top-level mapping

fn get(&self, nodename: &str) -> Result<FileNode>

Returns the specified element of the top-level mapping.

fn get_node(&self, nodename: &str) -> Result<FileNode>

Returns the specified element of the top-level mapping.

fn get_format(&self) -> Result<i32>

Returns the current format.

impl FilterTrait for Ptr<Filter>

fn as_raw_mut_Filter(&mut self) -> *mut c_void

fn apply( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Applies the specified filter to the image.

fn apply_def( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Applies the specified filter to the image.

impl FilterTraitConst for Ptr<Filter>

fn as_raw_Filter(&self) -> *const c_void

impl FisherFaceRecognizerTrait for Ptr<FisherFaceRecognizer>

fn as_raw_mut_FisherFaceRecognizer(&mut self) -> *mut c_void

impl FisherFaceRecognizerTraitConst for Ptr<FisherFaceRecognizer>

fn as_raw_FisherFaceRecognizer(&self) -> *const c_void

impl FisheyeWarperTrait for Ptr<FisheyeWarper>

fn as_raw_mut_FisheyeWarper(&mut self) -> *mut c_void

impl FisheyeWarperTraitConst for Ptr<FisheyeWarper>

fn as_raw_FisheyeWarper(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl FlannBasedMatcherTrait for Ptr<FlannBasedMatcher>

fn as_raw_mut_FlannBasedMatcher(&mut self) -> *mut c_void

fn add(&mut self, descriptors: &impl ToInputArray) -> Result<()>

fn clear(&mut self) -> Result<()>

fn read(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

fn train(&mut self) -> Result<()>

impl FlannBasedMatcherTraitConst for Ptr<FlannBasedMatcher>

fn as_raw_FlannBasedMatcher(&self) -> *const c_void

fn write(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

fn is_mask_supported(&self) -> Result<bool>

fn clone(&self, empty_train_data: bool) -> Result<Ptr<DescriptorMatcher>>

C++ default parameters

fn clone_def(&self) -> Result<Ptr<DescriptorMatcher>>

Note

impl FlattenLayerTrait for Ptr<FlattenLayer>

fn as_raw_mut_FlattenLayer(&mut self) -> *mut c_void

impl FlattenLayerTraitConst for Ptr<FlattenLayer>

fn as_raw_FlattenLayer(&self) -> *const c_void

impl FloorLayerTrait for Ptr<FloorLayer>

fn as_raw_mut_FloorLayer(&mut self) -> *mut c_void

impl FloorLayerTraitConst for Ptr<FloorLayer>

fn as_raw_FloorLayer(&self) -> *const c_void

impl FlowWarpLayerTrait for Ptr<FlowWarpLayer>

fn as_raw_mut_FlowWarpLayer(&mut self) -> *mut c_void

impl FlowWarpLayerTraitConst for Ptr<FlowWarpLayer>

fn as_raw_FlowWarpLayer(&self) -> *const c_void

impl FormattedTrait for Ptr<Formatted>

fn as_raw_mut_Formatted(&mut self) -> *mut c_void

fn next(&mut self) -> Result<String>

fn reset(&mut self) -> Result<()>

impl FormattedTraitConst for Ptr<Formatted>

fn as_raw_Formatted(&self) -> *const c_void

impl FormatterTrait for Ptr<Formatter>

fn as_raw_mut_Formatter(&mut self) -> *mut c_void

fn set16f_precision(&mut self, p: i32) -> Result<()>

C++ default parameters

fn set16f_precision_def(&mut self) -> Result<()>

Note

fn set32f_precision(&mut self, p: i32) -> Result<()>

C++ default parameters

fn set32f_precision_def(&mut self) -> Result<()>

Note

fn set64f_precision(&mut self, p: i32) -> Result<()>

C++ default parameters

fn set64f_precision_def(&mut self) -> Result<()>

Note

fn set_multiline(&mut self, ml: bool) -> Result<()>

C++ default parameters

fn set_multiline_def(&mut self) -> Result<()>

Note

impl FormatterTraitConst for Ptr<Formatter>

fn as_raw_Formatter(&self) -> *const c_void

fn format(&self, mtx: &impl MatTraitConst) -> Result<Ptr<Formatted>>

impl FreeType2Trait for Ptr<FreeType2>

fn as_raw_mut_FreeType2(&mut self) -> *mut c_void

fn load_font_data(&mut self, font_file_name: &str, idx: i32) -> Result<()>

Load font data.

unsafe fn load_font_data_1( &mut self, p_buf: *mut c_char, buf_size: size_t, idx: i32 ) -> Result<()>

Load font data.

fn set_split_number(&mut self, num: i32) -> Result<()>

Set Split Number from Bezier-curve to line

fn put_text( &mut self, img: &mut impl ToInputOutputArray, text: &str, org: Point, font_height: i32, color: Scalar, thickness: i32, line_type: i32, bottom_left_origin: bool ) -> Result<()>

Draws a text string.

fn get_text_size( &mut self, text: &str, font_height: i32, thickness: i32, base_line: &mut i32 ) -> Result<Size>

Calculates the width and height of a text string.

impl FreeType2TraitConst for Ptr<FreeType2>

fn as_raw_FreeType2(&self) -> *const c_void

impl From<Ptr<AKAZE>> for Ptr<Algorithm>

fn from(s: Ptr<AKAZE>) -> Self

Converts to this type from the input type.

impl From<Ptr<AKAZE>> for Ptr<Feature2D>

fn from(s: Ptr<AKAZE>) -> Self

Converts to this type from the input type.

impl From<Ptr<ANN_MLP>> for Ptr<Algorithm>

fn from(s: Ptr<ANN_MLP>) -> Self

Converts to this type from the input type.

impl From<Ptr<ANN_MLP>> for Ptr<StatModel>

fn from(s: Ptr<ANN_MLP>) -> Self

Converts to this type from the input type.

impl From<Ptr<AbsLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<AbsLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AbsLayer>> for Ptr<Algorithm>

fn from(s: Ptr<AbsLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AbsLayer>> for Ptr<Layer>

fn from(s: Ptr<AbsLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AccumLayer>> for Ptr<Algorithm>

fn from(s: Ptr<AccumLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AccumLayer>> for Ptr<Layer>

fn from(s: Ptr<AccumLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AcosLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<AcosLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AcosLayer>> for Ptr<Algorithm>

fn from(s: Ptr<AcosLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AcosLayer>> for Ptr<Layer>

fn from(s: Ptr<AcosLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AcoshLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<AcoshLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AcoshLayer>> for Ptr<Algorithm>

fn from(s: Ptr<AcoshLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AcoshLayer>> for Ptr<Layer>

fn from(s: Ptr<AcoshLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ActivationLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ActivationLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ActivationLayer>> for Ptr<Layer>

fn from(s: Ptr<ActivationLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ActivationLayerInt8>> for Ptr<ActivationLayer>

fn from(s: Ptr<ActivationLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<ActivationLayerInt8>> for Ptr<Algorithm>

fn from(s: Ptr<ActivationLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<ActivationLayerInt8>> for Ptr<Layer>

fn from(s: Ptr<ActivationLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<AdaptiveManifoldFilter>> for Ptr<Algorithm>

fn from(s: Ptr<AdaptiveManifoldFilter>) -> Self

Converts to this type from the input type.

impl From<Ptr<AffineFeature>> for Ptr<Algorithm>

fn from(s: Ptr<AffineFeature>) -> Self

Converts to this type from the input type.

impl From<Ptr<AffineFeature>> for Ptr<Feature2D>

fn from(s: Ptr<AffineFeature>) -> Self

Converts to this type from the input type.

impl From<Ptr<AffineFeature2D>> for Ptr<Algorithm>

fn from(s: Ptr<AffineFeature2D>) -> Self

Converts to this type from the input type.

impl From<Ptr<AffineFeature2D>> for Ptr<Feature2D>

fn from(s: Ptr<AffineFeature2D>) -> Self

Converts to this type from the input type.

impl From<Ptr<AffineTransformer>> for Ptr<Algorithm>

fn from(s: Ptr<AffineTransformer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AffineTransformer>> for Ptr<ShapeTransformer>

fn from(s: Ptr<AffineTransformer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AffineWarper>> for Ptr<WarperCreator>

fn from(s: Ptr<AffineWarper>) -> Self

Converts to this type from the input type.

impl From<Ptr<AgastFeatureDetector>> for Ptr<Algorithm>

fn from(s: Ptr<AgastFeatureDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<AgastFeatureDetector>> for Ptr<Feature2D>

fn from(s: Ptr<AgastFeatureDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<AlignExposures>> for Ptr<Algorithm>

fn from(s: Ptr<AlignExposures>) -> Self

Converts to this type from the input type.

impl From<Ptr<AlignMTB>> for Ptr<Algorithm>

fn from(s: Ptr<AlignMTB>) -> Self

Converts to this type from the input type.

impl From<Ptr<AlignMTB>> for Ptr<AlignExposures>

fn from(s: Ptr<AlignMTB>) -> Self

Converts to this type from the input type.

impl From<Ptr<ArgLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ArgLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ArgLayer>> for Ptr<Layer>

fn from(s: Ptr<ArgLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ArucoDetector>> for Ptr<Algorithm>

fn from(s: Ptr<ArucoDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<AsinLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<AsinLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AsinLayer>> for Ptr<Algorithm>

fn from(s: Ptr<AsinLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AsinLayer>> for Ptr<Layer>

fn from(s: Ptr<AsinLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AsinhLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<AsinhLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AsinhLayer>> for Ptr<Algorithm>

fn from(s: Ptr<AsinhLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AsinhLayer>> for Ptr<Layer>

fn from(s: Ptr<AsinhLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AtanLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<AtanLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AtanLayer>> for Ptr<Algorithm>

fn from(s: Ptr<AtanLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AtanLayer>> for Ptr<Layer>

fn from(s: Ptr<AtanLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AtanhLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<AtanhLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AtanhLayer>> for Ptr<Algorithm>

fn from(s: Ptr<AtanhLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AtanhLayer>> for Ptr<Layer>

fn from(s: Ptr<AtanhLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AttentionLayer>> for Ptr<Algorithm>

fn from(s: Ptr<AttentionLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AttentionLayer>> for Ptr<Layer>

fn from(s: Ptr<AttentionLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<AutotunedIndexParams>> for Ptr<IndexParams>

fn from(s: Ptr<AutotunedIndexParams>) -> Self

Converts to this type from the input type.

impl From<Ptr<AverageHash>> for Ptr<Algorithm>

fn from(s: Ptr<AverageHash>) -> Self

Converts to this type from the input type.

impl From<Ptr<AverageHash>> for Ptr<ImgHashBase>

fn from(s: Ptr<AverageHash>) -> Self

Converts to this type from the input type.

impl From<Ptr<BEBLID>> for Ptr<Algorithm>

fn from(s: Ptr<BEBLID>) -> Self

Converts to this type from the input type.

impl From<Ptr<BEBLID>> for Ptr<Feature2D>

fn from(s: Ptr<BEBLID>) -> Self

Converts to this type from the input type.

impl From<Ptr<BFMatcher>> for Ptr<Algorithm>

fn from(s: Ptr<BFMatcher>) -> Self

Converts to this type from the input type.

impl From<Ptr<BFMatcher>> for Ptr<DescriptorMatcher>

fn from(s: Ptr<BFMatcher>) -> Self

Converts to this type from the input type.

impl From<Ptr<BIF>> for Ptr<Algorithm>

fn from(s: Ptr<BIF>) -> Self

Converts to this type from the input type.

impl From<Ptr<BNLLLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<BNLLLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<BNLLLayer>> for Ptr<Algorithm>

fn from(s: Ptr<BNLLLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<BNLLLayer>> for Ptr<Layer>

fn from(s: Ptr<BNLLLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<BRISK>> for Ptr<Algorithm>

fn from(s: Ptr<BRISK>) -> Self

Converts to this type from the input type.

impl From<Ptr<BRISK>> for Ptr<Feature2D>

fn from(s: Ptr<BRISK>) -> Self

Converts to this type from the input type.

impl From<Ptr<BackgroundSubtractor>> for Ptr<Algorithm>

fn from(s: Ptr<BackgroundSubtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<BackgroundSubtractorCNT>> for Ptr<Algorithm>

fn from(s: Ptr<BackgroundSubtractorCNT>) -> Self

Converts to this type from the input type.

impl From<Ptr<BackgroundSubtractorCNT>> for Ptr<BackgroundSubtractor>

fn from(s: Ptr<BackgroundSubtractorCNT>) -> Self

Converts to this type from the input type.

impl From<Ptr<BackgroundSubtractorGMG>> for Ptr<Algorithm>

fn from(s: Ptr<BackgroundSubtractorGMG>) -> Self

Converts to this type from the input type.

impl From<Ptr<BackgroundSubtractorGMG>> for Ptr<BackgroundSubtractor>

fn from(s: Ptr<BackgroundSubtractorGMG>) -> Self

Converts to this type from the input type.

impl From<Ptr<BackgroundSubtractorGSOC>> for Ptr<Algorithm>

fn from(s: Ptr<BackgroundSubtractorGSOC>) -> Self

Converts to this type from the input type.

impl From<Ptr<BackgroundSubtractorGSOC>> for Ptr<BackgroundSubtractor>

fn from(s: Ptr<BackgroundSubtractorGSOC>) -> Self

Converts to this type from the input type.

impl From<Ptr<BackgroundSubtractorKNN>> for Ptr<Algorithm>

fn from(s: Ptr<BackgroundSubtractorKNN>) -> Self

Converts to this type from the input type.

impl From<Ptr<BackgroundSubtractorKNN>> for Ptr<BackgroundSubtractor>

fn from(s: Ptr<BackgroundSubtractorKNN>) -> Self

Converts to this type from the input type.

impl From<Ptr<BackgroundSubtractorLSBP>> for Ptr<Algorithm>

fn from(s: Ptr<BackgroundSubtractorLSBP>) -> Self

Converts to this type from the input type.

impl From<Ptr<BackgroundSubtractorLSBP>> for Ptr<BackgroundSubtractor>

fn from(s: Ptr<BackgroundSubtractorLSBP>) -> Self

Converts to this type from the input type.

impl From<Ptr<BackgroundSubtractorMOG>> for Ptr<Algorithm>

fn from(s: Ptr<BackgroundSubtractorMOG>) -> Self

Converts to this type from the input type.

impl From<Ptr<BackgroundSubtractorMOG>> for Ptr<BackgroundSubtractor>

fn from(s: Ptr<BackgroundSubtractorMOG>) -> Self

Converts to this type from the input type.

impl From<Ptr<BackgroundSubtractorMOG2>> for Ptr<Algorithm>

fn from(s: Ptr<BackgroundSubtractorMOG2>) -> Self

Converts to this type from the input type.

impl From<Ptr<BackgroundSubtractorMOG2>> for Ptr<BackgroundSubtractor>

fn from(s: Ptr<BackgroundSubtractorMOG2>) -> Self

Converts to this type from the input type.

impl From<Ptr<BaseCascadeClassifier>> for Ptr<Algorithm>

fn from(s: Ptr<BaseCascadeClassifier>) -> Self

Converts to this type from the input type.

impl From<Ptr<BaseConvolutionLayer>> for Ptr<Algorithm>

fn from(s: Ptr<BaseConvolutionLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<BaseConvolutionLayer>> for Ptr<Layer>

fn from(s: Ptr<BaseConvolutionLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<BasicFaceRecognizer>> for Ptr<Algorithm>

fn from(s: Ptr<BasicFaceRecognizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<BasicFaceRecognizer>> for Ptr<FaceRecognizer>

fn from(s: Ptr<BasicFaceRecognizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<BatchNormLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<BatchNormLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<BatchNormLayer>> for Ptr<Algorithm>

fn from(s: Ptr<BatchNormLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<BatchNormLayer>> for Ptr<Layer>

fn from(s: Ptr<BatchNormLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<BatchNormLayerInt8>> for Ptr<ActivationLayer>

fn from(s: Ptr<BatchNormLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<BatchNormLayerInt8>> for Ptr<Algorithm>

fn from(s: Ptr<BatchNormLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<BatchNormLayerInt8>> for Ptr<BatchNormLayer>

fn from(s: Ptr<BatchNormLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<BatchNormLayerInt8>> for Ptr<Layer>

fn from(s: Ptr<BatchNormLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<BinaryDescriptor>> for Ptr<Algorithm>

fn from(s: Ptr<BinaryDescriptor>) -> Self

Converts to this type from the input type.

impl From<Ptr<BinaryDescriptorMatcher>> for Ptr<Algorithm>

fn from(s: Ptr<BinaryDescriptorMatcher>) -> Self

Converts to this type from the input type.

impl From<Ptr<BlankLayer>> for Ptr<Algorithm>

fn from(s: Ptr<BlankLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<BlankLayer>> for Ptr<Layer>

fn from(s: Ptr<BlankLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<BlockMeanHash>> for Ptr<Algorithm>

fn from(s: Ptr<BlockMeanHash>) -> Self

Converts to this type from the input type.

impl From<Ptr<BlockMeanHash>> for Ptr<ImgHashBase>

fn from(s: Ptr<BlockMeanHash>) -> Self

Converts to this type from the input type.

impl From<Ptr<Boost>> for Ptr<Algorithm>

fn from(s: Ptr<Boost>) -> Self

Converts to this type from the input type.

impl From<Ptr<Boost>> for Ptr<DTrees>

fn from(s: Ptr<Boost>) -> Self

Converts to this type from the input type.

impl From<Ptr<Boost>> for Ptr<StatModel>

fn from(s: Ptr<Boost>) -> Self

Converts to this type from the input type.

impl From<Ptr<BoostDesc>> for Ptr<Algorithm>

fn from(s: Ptr<BoostDesc>) -> Self

Converts to this type from the input type.

impl From<Ptr<BoostDesc>> for Ptr<Feature2D>

fn from(s: Ptr<BoostDesc>) -> Self

Converts to this type from the input type.

impl From<Ptr<BriefDescriptorExtractor>> for Ptr<Algorithm>

fn from(s: Ptr<BriefDescriptorExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<BriefDescriptorExtractor>> for Ptr<Feature2D>

fn from(s: Ptr<BriefDescriptorExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<CLAHE>> for Ptr<Algorithm>

fn from(s: Ptr<CLAHE>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_BackgroundSubtractorMOG>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_BackgroundSubtractorMOG>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_BackgroundSubtractorMOG>> for Ptr<BackgroundSubtractor>

fn from(s: Ptr<CUDA_BackgroundSubtractorMOG>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_BackgroundSubtractorMOG2>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_BackgroundSubtractorMOG2>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_BackgroundSubtractorMOG2>> for Ptr<BackgroundSubtractor>

fn from(s: Ptr<CUDA_BackgroundSubtractorMOG2>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_BackgroundSubtractorMOG2>> for Ptr<BackgroundSubtractorMOG2>

fn from(s: Ptr<CUDA_BackgroundSubtractorMOG2>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_BroxOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_BroxOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_BroxOpticalFlow>> for Ptr<CUDA_DenseOpticalFlow>

fn from(s: Ptr<CUDA_BroxOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_CLAHE>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_CLAHE>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_CLAHE>> for Ptr<CLAHE>

fn from(s: Ptr<CUDA_CLAHE>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_CannyEdgeDetector>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_CannyEdgeDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_CascadeClassifier>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_CascadeClassifier>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_CornernessCriteria>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_CornernessCriteria>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_CornersDetector>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_CornersDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_DenseOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_DenseOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_DensePyrLKOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_DensePyrLKOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_DensePyrLKOpticalFlow>> for Ptr<CUDA_DenseOpticalFlow>

fn from(s: Ptr<CUDA_DensePyrLKOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_DescriptorMatcher>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_DescriptorMatcher>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_DisparityBilateralFilter>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_DisparityBilateralFilter>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_FarnebackOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_FarnebackOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_FarnebackOpticalFlow>> for Ptr<CUDA_DenseOpticalFlow>

fn from(s: Ptr<CUDA_FarnebackOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_FastFeatureDetector>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_FastFeatureDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_FastFeatureDetector>> for Ptr<CUDA_Feature2DAsync>

fn from(s: Ptr<CUDA_FastFeatureDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_FastFeatureDetector>> for Ptr<Feature2D>

fn from(s: Ptr<CUDA_FastFeatureDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_Feature2DAsync>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_Feature2DAsync>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_Feature2DAsync>> for Ptr<Feature2D>

fn from(s: Ptr<CUDA_Feature2DAsync>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_HOG>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_HOG>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_HoughCirclesDetector>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_HoughCirclesDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_HoughLinesDetector>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_HoughLinesDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_HoughSegmentDetector>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_HoughSegmentDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_NvidiaHWOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_NvidiaHWOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_NvidiaOpticalFlow_1_0>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_NvidiaOpticalFlow_1_0>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_NvidiaOpticalFlow_1_0>> for Ptr<CUDA_NvidiaHWOpticalFlow>

fn from(s: Ptr<CUDA_NvidiaOpticalFlow_1_0>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_NvidiaOpticalFlow_2_0>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_NvidiaOpticalFlow_2_0>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_NvidiaOpticalFlow_2_0>> for Ptr<CUDA_NvidiaHWOpticalFlow>

fn from(s: Ptr<CUDA_NvidiaOpticalFlow_2_0>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_ORB>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_ORB>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_ORB>> for Ptr<CUDA_Feature2DAsync>

fn from(s: Ptr<CUDA_ORB>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_ORB>> for Ptr<Feature2D>

fn from(s: Ptr<CUDA_ORB>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_OpticalFlowDual_TVL1>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_OpticalFlowDual_TVL1>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_OpticalFlowDual_TVL1>> for Ptr<CUDA_DenseOpticalFlow>

fn from(s: Ptr<CUDA_OpticalFlowDual_TVL1>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_SparseOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_SparseOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_SparsePyrLKOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_SparsePyrLKOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_SparsePyrLKOpticalFlow>> for Ptr<CUDA_SparseOpticalFlow>

fn from(s: Ptr<CUDA_SparsePyrLKOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_StereoBM>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_StereoBM>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_StereoBM>> for Ptr<StereoBM>

fn from(s: Ptr<CUDA_StereoBM>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_StereoBM>> for Ptr<StereoMatcher>

fn from(s: Ptr<CUDA_StereoBM>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_StereoBeliefPropagation>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_StereoBeliefPropagation>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_StereoBeliefPropagation>> for Ptr<StereoMatcher>

fn from(s: Ptr<CUDA_StereoBeliefPropagation>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_StereoConstantSpaceBP>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_StereoConstantSpaceBP>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_StereoConstantSpaceBP>> for Ptr<CUDA_StereoBeliefPropagation>

fn from(s: Ptr<CUDA_StereoConstantSpaceBP>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_StereoConstantSpaceBP>> for Ptr<StereoMatcher>

fn from(s: Ptr<CUDA_StereoConstantSpaceBP>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_StereoSGM>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_StereoSGM>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_StereoSGM>> for Ptr<StereoMatcher>

fn from(s: Ptr<CUDA_StereoSGM>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_StereoSGM>> for Ptr<StereoSGBM>

fn from(s: Ptr<CUDA_StereoSGM>) -> Self

Converts to this type from the input type.

impl From<Ptr<CUDA_TemplateMatching>> for Ptr<Algorithm>

fn from(s: Ptr<CUDA_TemplateMatching>) -> Self

Converts to this type from the input type.

impl From<Ptr<CalibrateCRF>> for Ptr<Algorithm>

fn from(s: Ptr<CalibrateCRF>) -> Self

Converts to this type from the input type.

impl From<Ptr<CalibrateDebevec>> for Ptr<Algorithm>

fn from(s: Ptr<CalibrateDebevec>) -> Self

Converts to this type from the input type.

impl From<Ptr<CalibrateDebevec>> for Ptr<CalibrateCRF>

fn from(s: Ptr<CalibrateDebevec>) -> Self

Converts to this type from the input type.

impl From<Ptr<CalibrateRobertson>> for Ptr<Algorithm>

fn from(s: Ptr<CalibrateRobertson>) -> Self

Converts to this type from the input type.

impl From<Ptr<CalibrateRobertson>> for Ptr<CalibrateCRF>

fn from(s: Ptr<CalibrateRobertson>) -> Self

Converts to this type from the input type.

impl From<Ptr<CeilLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<CeilLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CeilLayer>> for Ptr<Algorithm>

fn from(s: Ptr<CeilLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CeilLayer>> for Ptr<Layer>

fn from(s: Ptr<CeilLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CeluLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<CeluLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CeluLayer>> for Ptr<Algorithm>

fn from(s: Ptr<CeluLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CeluLayer>> for Ptr<Layer>

fn from(s: Ptr<CeluLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ChannelsPReLULayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<ChannelsPReLULayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ChannelsPReLULayer>> for Ptr<Algorithm>

fn from(s: Ptr<ChannelsPReLULayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ChannelsPReLULayer>> for Ptr<Layer>

fn from(s: Ptr<ChannelsPReLULayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CharucoBoard>> for Ptr<Board>

fn from(s: Ptr<CharucoBoard>) -> Self

Converts to this type from the input type.

impl From<Ptr<CharucoDetector>> for Ptr<Algorithm>

fn from(s: Ptr<CharucoDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<ChiHistogramCostExtractor>> for Ptr<Algorithm>

fn from(s: Ptr<ChiHistogramCostExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<ChiHistogramCostExtractor>> for Ptr<HistogramCostExtractor>

fn from(s: Ptr<ChiHistogramCostExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<ColorAverageInpainter>> for Ptr<InpainterBase>

fn from(s: Ptr<ColorAverageInpainter>) -> Self

Converts to this type from the input type.

impl From<Ptr<ColorInpainter>> for Ptr<InpainterBase>

fn from(s: Ptr<ColorInpainter>) -> Self

Converts to this type from the input type.

impl From<Ptr<ColorMomentHash>> for Ptr<Algorithm>

fn from(s: Ptr<ColorMomentHash>) -> Self

Converts to this type from the input type.

impl From<Ptr<ColorMomentHash>> for Ptr<ImgHashBase>

fn from(s: Ptr<ColorMomentHash>) -> Self

Converts to this type from the input type.

impl From<Ptr<CompareLayer>> for Ptr<Algorithm>

fn from(s: Ptr<CompareLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CompareLayer>> for Ptr<Layer>

fn from(s: Ptr<CompareLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CompositeIndexParams>> for Ptr<IndexParams>

fn from(s: Ptr<CompositeIndexParams>) -> Self

Converts to this type from the input type.

impl From<Ptr<CompressedRectilinearPortraitWarper>> for Ptr<WarperCreator>

fn from(s: Ptr<CompressedRectilinearPortraitWarper>) -> Self

Converts to this type from the input type.

impl From<Ptr<CompressedRectilinearWarper>> for Ptr<WarperCreator>

fn from(s: Ptr<CompressedRectilinearWarper>) -> Self

Converts to this type from the input type.

impl From<Ptr<ConcatLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ConcatLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ConcatLayer>> for Ptr<Layer>

fn from(s: Ptr<ConcatLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ConjGradSolver>> for Ptr<Algorithm>

fn from(s: Ptr<ConjGradSolver>) -> Self

Converts to this type from the input type.

impl From<Ptr<ConjGradSolver>> for Ptr<MinProblemSolver>

fn from(s: Ptr<ConjGradSolver>) -> Self

Converts to this type from the input type.

impl From<Ptr<ConsistentMosaicInpainter>> for Ptr<InpainterBase>

fn from(s: Ptr<ConsistentMosaicInpainter>) -> Self

Converts to this type from the input type.

impl From<Ptr<ConstLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ConstLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ConstLayer>> for Ptr<Layer>

fn from(s: Ptr<ConstLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ContourFitting>> for Ptr<Algorithm>

fn from(s: Ptr<ContourFitting>) -> Self

Converts to this type from the input type.

impl From<Ptr<Convolution>> for Ptr<Algorithm>

fn from(s: Ptr<Convolution>) -> Self

Converts to this type from the input type.

impl From<Ptr<ConvolutionLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ConvolutionLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ConvolutionLayer>> for Ptr<BaseConvolutionLayer>

fn from(s: Ptr<ConvolutionLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ConvolutionLayer>> for Ptr<Layer>

fn from(s: Ptr<ConvolutionLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ConvolutionLayerInt8>> for Ptr<Algorithm>

fn from(s: Ptr<ConvolutionLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<ConvolutionLayerInt8>> for Ptr<BaseConvolutionLayer>

fn from(s: Ptr<ConvolutionLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<ConvolutionLayerInt8>> for Ptr<Layer>

fn from(s: Ptr<ConvolutionLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<CorrelationLayer>> for Ptr<Algorithm>

fn from(s: Ptr<CorrelationLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CorrelationLayer>> for Ptr<Layer>

fn from(s: Ptr<CorrelationLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CosLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<CosLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CosLayer>> for Ptr<Algorithm>

fn from(s: Ptr<CosLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CosLayer>> for Ptr<Layer>

fn from(s: Ptr<CosLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CoshLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<CoshLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CoshLayer>> for Ptr<Algorithm>

fn from(s: Ptr<CoshLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CoshLayer>> for Ptr<Layer>

fn from(s: Ptr<CoshLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CropAndResizeLayer>> for Ptr<Algorithm>

fn from(s: Ptr<CropAndResizeLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CropAndResizeLayer>> for Ptr<Layer>

fn from(s: Ptr<CropAndResizeLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CropLayer>> for Ptr<Algorithm>

fn from(s: Ptr<CropLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CropLayer>> for Ptr<Layer>

fn from(s: Ptr<CropLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CumSumLayer>> for Ptr<Algorithm>

fn from(s: Ptr<CumSumLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CumSumLayer>> for Ptr<Layer>

fn from(s: Ptr<CumSumLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<CustomPattern>> for Ptr<Algorithm>

fn from(s: Ptr<CustomPattern>) -> Self

Converts to this type from the input type.

impl From<Ptr<CylindricalWarper>> for Ptr<WarperCreator>

fn from(s: Ptr<CylindricalWarper>) -> Self

Converts to this type from the input type.

impl From<Ptr<CylindricalWarperGpu>> for Ptr<WarperCreator>

fn from(s: Ptr<CylindricalWarperGpu>) -> Self

Converts to this type from the input type.

impl From<Ptr<DAISY>> for Ptr<Algorithm>

fn from(s: Ptr<DAISY>) -> Self

Converts to this type from the input type.

impl From<Ptr<DAISY>> for Ptr<Feature2D>

fn from(s: Ptr<DAISY>) -> Self

Converts to this type from the input type.

impl From<Ptr<DFT>> for Ptr<Algorithm>

fn from(s: Ptr<DFT>) -> Self

Converts to this type from the input type.

impl From<Ptr<DISOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<DISOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<DISOpticalFlow>> for Ptr<DenseOpticalFlow>

fn from(s: Ptr<DISOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<DTFilter>> for Ptr<Algorithm>

fn from(s: Ptr<DTFilter>) -> Self

Converts to this type from the input type.

impl From<Ptr<DTrees>> for Ptr<Algorithm>

fn from(s: Ptr<DTrees>) -> Self

Converts to this type from the input type.

impl From<Ptr<DTrees>> for Ptr<StatModel>

fn from(s: Ptr<DTrees>) -> Self

Converts to this type from the input type.

impl From<Ptr<DataAugmentationLayer>> for Ptr<Algorithm>

fn from(s: Ptr<DataAugmentationLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<DataAugmentationLayer>> for Ptr<Layer>

fn from(s: Ptr<DataAugmentationLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<DeconvolutionLayer>> for Ptr<Algorithm>

fn from(s: Ptr<DeconvolutionLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<DeconvolutionLayer>> for Ptr<BaseConvolutionLayer>

fn from(s: Ptr<DeconvolutionLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<DeconvolutionLayer>> for Ptr<Layer>

fn from(s: Ptr<DeconvolutionLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<DenseOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<DenseOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<DensePyrLkOptFlowEstimatorGpu>> for Ptr<IDenseOptFlowEstimator>

fn from(s: Ptr<DensePyrLkOptFlowEstimatorGpu>) -> Self

Converts to this type from the input type.

impl From<Ptr<DensePyrLkOptFlowEstimatorGpu>> for Ptr<PyrLkOptFlowEstimatorBase>

fn from(s: Ptr<DensePyrLkOptFlowEstimatorGpu>) -> Self

Converts to this type from the input type.

impl From<Ptr<DenseRLOFOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<DenseRLOFOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<DenseRLOFOpticalFlow>> for Ptr<DenseOpticalFlow>

fn from(s: Ptr<DenseRLOFOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<DepthCleaner>> for Ptr<Algorithm>

fn from(s: Ptr<DepthCleaner>) -> Self

Converts to this type from the input type.

impl From<Ptr<DequantizeLayer>> for Ptr<Algorithm>

fn from(s: Ptr<DequantizeLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<DequantizeLayer>> for Ptr<Layer>

fn from(s: Ptr<DequantizeLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<DescriptorMatcher>> for Ptr<Algorithm>

fn from(s: Ptr<DescriptorMatcher>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_AffineBasedEstimator>> for Ptr<Detail_Estimator>

fn from(s: Ptr<Detail_AffineBasedEstimator>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_AffineBestOf2NearestMatcher>> for Ptr<Detail_BestOf2NearestMatcher>

fn from(s: Ptr<Detail_AffineBestOf2NearestMatcher>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_AffineBestOf2NearestMatcher>> for Ptr<Detail_FeaturesMatcher>

fn from(s: Ptr<Detail_AffineBestOf2NearestMatcher>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BestOf2NearestMatcher>> for Ptr<Detail_FeaturesMatcher>

fn from(s: Ptr<Detail_BestOf2NearestMatcher>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BestOf2NearestRangeMatcher>> for Ptr<Detail_BestOf2NearestMatcher>

fn from(s: Ptr<Detail_BestOf2NearestRangeMatcher>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BestOf2NearestRangeMatcher>> for Ptr<Detail_FeaturesMatcher>

fn from(s: Ptr<Detail_BestOf2NearestRangeMatcher>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BlocksChannelsCompensator>> for Ptr<Detail_BlocksCompensator>

fn from(s: Ptr<Detail_BlocksChannelsCompensator>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BlocksChannelsCompensator>> for Ptr<Detail_ExposureCompensator>

fn from(s: Ptr<Detail_BlocksChannelsCompensator>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BlocksCompensator>> for Ptr<Detail_ExposureCompensator>

fn from(s: Ptr<Detail_BlocksCompensator>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BlocksGainCompensator>> for Ptr<Detail_BlocksCompensator>

fn from(s: Ptr<Detail_BlocksGainCompensator>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BlocksGainCompensator>> for Ptr<Detail_ExposureCompensator>

fn from(s: Ptr<Detail_BlocksGainCompensator>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BundleAdjusterAffine>> for Ptr<Detail_BundleAdjusterBase>

fn from(s: Ptr<Detail_BundleAdjusterAffine>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BundleAdjusterAffine>> for Ptr<Detail_Estimator>

fn from(s: Ptr<Detail_BundleAdjusterAffine>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BundleAdjusterAffinePartial>> for Ptr<Detail_BundleAdjusterBase>

fn from(s: Ptr<Detail_BundleAdjusterAffinePartial>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BundleAdjusterAffinePartial>> for Ptr<Detail_Estimator>

fn from(s: Ptr<Detail_BundleAdjusterAffinePartial>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BundleAdjusterBase>> for Ptr<Detail_Estimator>

fn from(s: Ptr<Detail_BundleAdjusterBase>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BundleAdjusterRay>> for Ptr<Detail_BundleAdjusterBase>

fn from(s: Ptr<Detail_BundleAdjusterRay>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BundleAdjusterRay>> for Ptr<Detail_Estimator>

fn from(s: Ptr<Detail_BundleAdjusterRay>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BundleAdjusterReproj>> for Ptr<Detail_BundleAdjusterBase>

fn from(s: Ptr<Detail_BundleAdjusterReproj>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_BundleAdjusterReproj>> for Ptr<Detail_Estimator>

fn from(s: Ptr<Detail_BundleAdjusterReproj>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_ChannelsCompensator>> for Ptr<Detail_ExposureCompensator>

fn from(s: Ptr<Detail_ChannelsCompensator>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_DpSeamFinder>> for Ptr<Detail_SeamFinder>

fn from(s: Ptr<Detail_DpSeamFinder>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_FeatherBlender>> for Ptr<Detail_Blender>

fn from(s: Ptr<Detail_FeatherBlender>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_GainCompensator>> for Ptr<Detail_ExposureCompensator>

fn from(s: Ptr<Detail_GainCompensator>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_GraphCutSeamFinder>> for Ptr<Detail_GraphCutSeamFinderBase>

fn from(s: Ptr<Detail_GraphCutSeamFinder>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_GraphCutSeamFinder>> for Ptr<Detail_SeamFinder>

fn from(s: Ptr<Detail_GraphCutSeamFinder>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_GraphCutSeamFinderGpu>> for Ptr<Detail_GraphCutSeamFinderBase>

fn from(s: Ptr<Detail_GraphCutSeamFinderGpu>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_GraphCutSeamFinderGpu>> for Ptr<Detail_PairwiseSeamFinder>

fn from(s: Ptr<Detail_GraphCutSeamFinderGpu>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_GraphCutSeamFinderGpu>> for Ptr<Detail_SeamFinder>

fn from(s: Ptr<Detail_GraphCutSeamFinderGpu>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_HomographyBasedEstimator>> for Ptr<Detail_Estimator>

fn from(s: Ptr<Detail_HomographyBasedEstimator>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_MultiBandBlender>> for Ptr<Detail_Blender>

fn from(s: Ptr<Detail_MultiBandBlender>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_NoBundleAdjuster>> for Ptr<Detail_BundleAdjusterBase>

fn from(s: Ptr<Detail_NoBundleAdjuster>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_NoBundleAdjuster>> for Ptr<Detail_Estimator>

fn from(s: Ptr<Detail_NoBundleAdjuster>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_NoExposureCompensator>> for Ptr<Detail_ExposureCompensator>

fn from(s: Ptr<Detail_NoExposureCompensator>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_NoSeamFinder>> for Ptr<Detail_SeamFinder>

fn from(s: Ptr<Detail_NoSeamFinder>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_PairwiseSeamFinder>> for Ptr<Detail_SeamFinder>

fn from(s: Ptr<Detail_PairwiseSeamFinder>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_VoronoiSeamFinder>> for Ptr<Detail_PairwiseSeamFinder>

fn from(s: Ptr<Detail_VoronoiSeamFinder>) -> Self

Converts to this type from the input type.

impl From<Ptr<Detail_VoronoiSeamFinder>> for Ptr<Detail_SeamFinder>

fn from(s: Ptr<Detail_VoronoiSeamFinder>) -> Self

Converts to this type from the input type.

impl From<Ptr<DetectionOutputLayer>> for Ptr<Algorithm>

fn from(s: Ptr<DetectionOutputLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<DetectionOutputLayer>> for Ptr<Layer>

fn from(s: Ptr<DetectionOutputLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<DisparityFilter>> for Ptr<Algorithm>

fn from(s: Ptr<DisparityFilter>) -> Self

Converts to this type from the input type.

impl From<Ptr<DisparityWLSFilter>> for Ptr<Algorithm>

fn from(s: Ptr<DisparityWLSFilter>) -> Self

Converts to this type from the input type.

impl From<Ptr<DisparityWLSFilter>> for Ptr<DisparityFilter>

fn from(s: Ptr<DisparityWLSFilter>) -> Self

Converts to this type from the input type.

impl From<Ptr<DownhillSolver>> for Ptr<Algorithm>

fn from(s: Ptr<DownhillSolver>) -> Self

Converts to this type from the input type.

impl From<Ptr<DownhillSolver>> for Ptr<MinProblemSolver>

fn from(s: Ptr<DownhillSolver>) -> Self

Converts to this type from the input type.

impl From<Ptr<DualTVL1OpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<DualTVL1OpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<DualTVL1OpticalFlow>> for Ptr<DenseOpticalFlow>

fn from(s: Ptr<DualTVL1OpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<ELULayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<ELULayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ELULayer>> for Ptr<Algorithm>

fn from(s: Ptr<ELULayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ELULayer>> for Ptr<Layer>

fn from(s: Ptr<ELULayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<EM>> for Ptr<Algorithm>

fn from(s: Ptr<EM>) -> Self

Converts to this type from the input type.

impl From<Ptr<EM>> for Ptr<StatModel>

fn from(s: Ptr<EM>) -> Self

Converts to this type from the input type.

impl From<Ptr<EMDHistogramCostExtractor>> for Ptr<Algorithm>

fn from(s: Ptr<EMDHistogramCostExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<EMDHistogramCostExtractor>> for Ptr<HistogramCostExtractor>

fn from(s: Ptr<EMDHistogramCostExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<EMDL1HistogramCostExtractor>> for Ptr<Algorithm>

fn from(s: Ptr<EMDL1HistogramCostExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<EMDL1HistogramCostExtractor>> for Ptr<HistogramCostExtractor>

fn from(s: Ptr<EMDL1HistogramCostExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<ERFilter>> for Ptr<Algorithm>

fn from(s: Ptr<ERFilter>) -> Self

Converts to this type from the input type.

impl From<Ptr<EdgeAwareInterpolator>> for Ptr<Algorithm>

fn from(s: Ptr<EdgeAwareInterpolator>) -> Self

Converts to this type from the input type.

impl From<Ptr<EdgeAwareInterpolator>> for Ptr<SparseMatchInterpolator>

fn from(s: Ptr<EdgeAwareInterpolator>) -> Self

Converts to this type from the input type.

impl From<Ptr<EdgeBoxes>> for Ptr<Algorithm>

fn from(s: Ptr<EdgeBoxes>) -> Self

Converts to this type from the input type.

impl From<Ptr<EdgeDrawing>> for Ptr<Algorithm>

fn from(s: Ptr<EdgeDrawing>) -> Self

Converts to this type from the input type.

impl From<Ptr<EigenFaceRecognizer>> for Ptr<Algorithm>

fn from(s: Ptr<EigenFaceRecognizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<EigenFaceRecognizer>> for Ptr<BasicFaceRecognizer>

fn from(s: Ptr<EigenFaceRecognizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<EigenFaceRecognizer>> for Ptr<FaceRecognizer>

fn from(s: Ptr<EigenFaceRecognizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<EinsumLayer>> for Ptr<Algorithm>

fn from(s: Ptr<EinsumLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<EinsumLayer>> for Ptr<Layer>

fn from(s: Ptr<EinsumLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<EltwiseLayer>> for Ptr<Algorithm>

fn from(s: Ptr<EltwiseLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<EltwiseLayer>> for Ptr<Layer>

fn from(s: Ptr<EltwiseLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<EltwiseLayerInt8>> for Ptr<Algorithm>

fn from(s: Ptr<EltwiseLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<EltwiseLayerInt8>> for Ptr<Layer>

fn from(s: Ptr<EltwiseLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<ErfLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<ErfLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ErfLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ErfLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ErfLayer>> for Ptr<Layer>

fn from(s: Ptr<ErfLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ExpLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<ExpLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ExpLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ExpLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ExpLayer>> for Ptr<Layer>

fn from(s: Ptr<ExpLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ExpandLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ExpandLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ExpandLayer>> for Ptr<Layer>

fn from(s: Ptr<ExpandLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<FREAK>> for Ptr<Algorithm>

fn from(s: Ptr<FREAK>) -> Self

Converts to this type from the input type.

impl From<Ptr<FREAK>> for Ptr<Feature2D>

fn from(s: Ptr<FREAK>) -> Self

Converts to this type from the input type.

impl From<Ptr<FaceRecognizer>> for Ptr<Algorithm>

fn from(s: Ptr<FaceRecognizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<Facemark>> for Ptr<Algorithm>

fn from(s: Ptr<Facemark>) -> Self

Converts to this type from the input type.

impl From<Ptr<FacemarkAAM>> for Ptr<Algorithm>

fn from(s: Ptr<FacemarkAAM>) -> Self

Converts to this type from the input type.

impl From<Ptr<FacemarkAAM>> for Ptr<Facemark>

fn from(s: Ptr<FacemarkAAM>) -> Self

Converts to this type from the input type.

impl From<Ptr<FacemarkAAM>> for Ptr<FacemarkTrain>

fn from(s: Ptr<FacemarkAAM>) -> Self

Converts to this type from the input type.

impl From<Ptr<FacemarkKazemi>> for Ptr<Algorithm>

fn from(s: Ptr<FacemarkKazemi>) -> Self

Converts to this type from the input type.

impl From<Ptr<FacemarkKazemi>> for Ptr<Facemark>

fn from(s: Ptr<FacemarkKazemi>) -> Self

Converts to this type from the input type.

impl From<Ptr<FacemarkLBF>> for Ptr<Algorithm>

fn from(s: Ptr<FacemarkLBF>) -> Self

Converts to this type from the input type.

impl From<Ptr<FacemarkLBF>> for Ptr<Facemark>

fn from(s: Ptr<FacemarkLBF>) -> Self

Converts to this type from the input type.

impl From<Ptr<FacemarkLBF>> for Ptr<FacemarkTrain>

fn from(s: Ptr<FacemarkLBF>) -> Self

Converts to this type from the input type.

impl From<Ptr<FacemarkTrain>> for Ptr<Algorithm>

fn from(s: Ptr<FacemarkTrain>) -> Self

Converts to this type from the input type.

impl From<Ptr<FacemarkTrain>> for Ptr<Facemark>

fn from(s: Ptr<FacemarkTrain>) -> Self

Converts to this type from the input type.

impl From<Ptr<FarnebackOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<FarnebackOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<FarnebackOpticalFlow>> for Ptr<DenseOpticalFlow>

fn from(s: Ptr<FarnebackOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<FastBilateralSolverFilter>> for Ptr<Algorithm>

fn from(s: Ptr<FastBilateralSolverFilter>) -> Self

Converts to this type from the input type.

impl From<Ptr<FastFeatureDetector>> for Ptr<Algorithm>

fn from(s: Ptr<FastFeatureDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<FastFeatureDetector>> for Ptr<Feature2D>

fn from(s: Ptr<FastFeatureDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<FastGlobalSmootherFilter>> for Ptr<Algorithm>

fn from(s: Ptr<FastGlobalSmootherFilter>) -> Self

Converts to this type from the input type.

impl From<Ptr<FastICPOdometry>> for Ptr<Algorithm>

fn from(s: Ptr<FastICPOdometry>) -> Self

Converts to this type from the input type.

impl From<Ptr<FastICPOdometry>> for Ptr<Odometry>

fn from(s: Ptr<FastICPOdometry>) -> Self

Converts to this type from the input type.

impl From<Ptr<FastLineDetector>> for Ptr<Algorithm>

fn from(s: Ptr<FastLineDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<Feature2D>> for Ptr<Algorithm>

fn from(s: Ptr<Feature2D>) -> Self

Converts to this type from the input type.

impl From<Ptr<Filter>> for Ptr<Algorithm>

fn from(s: Ptr<Filter>) -> Self

Converts to this type from the input type.

impl From<Ptr<FisherFaceRecognizer>> for Ptr<Algorithm>

fn from(s: Ptr<FisherFaceRecognizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<FisherFaceRecognizer>> for Ptr<BasicFaceRecognizer>

fn from(s: Ptr<FisherFaceRecognizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<FisherFaceRecognizer>> for Ptr<FaceRecognizer>

fn from(s: Ptr<FisherFaceRecognizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<FisheyeWarper>> for Ptr<WarperCreator>

fn from(s: Ptr<FisheyeWarper>) -> Self

Converts to this type from the input type.

impl From<Ptr<FlannBasedMatcher>> for Ptr<Algorithm>

fn from(s: Ptr<FlannBasedMatcher>) -> Self

Converts to this type from the input type.

impl From<Ptr<FlannBasedMatcher>> for Ptr<DescriptorMatcher>

fn from(s: Ptr<FlannBasedMatcher>) -> Self

Converts to this type from the input type.

impl From<Ptr<FlattenLayer>> for Ptr<Algorithm>

fn from(s: Ptr<FlattenLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<FlattenLayer>> for Ptr<Layer>

fn from(s: Ptr<FlattenLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<FloorLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<FloorLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<FloorLayer>> for Ptr<Algorithm>

fn from(s: Ptr<FloorLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<FloorLayer>> for Ptr<Layer>

fn from(s: Ptr<FloorLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<FlowWarpLayer>> for Ptr<Algorithm>

fn from(s: Ptr<FlowWarpLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<FlowWarpLayer>> for Ptr<Layer>

fn from(s: Ptr<FlowWarpLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<FreeType2>> for Ptr<Algorithm>

fn from(s: Ptr<FreeType2>) -> Self

Converts to this type from the input type.

impl From<Ptr<FromFileMotionReader>> for Ptr<ImageMotionEstimatorBase>

fn from(s: Ptr<FromFileMotionReader>) -> Self

Converts to this type from the input type.

impl From<Ptr<GFTTDetector>> for Ptr<Algorithm>

fn from(s: Ptr<GFTTDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<GFTTDetector>> for Ptr<Feature2D>

fn from(s: Ptr<GFTTDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<GPCTree>> for Ptr<Algorithm>

fn from(s: Ptr<GPCTree>) -> Self

Converts to this type from the input type.

impl From<Ptr<GRULayer>> for Ptr<Algorithm>

fn from(s: Ptr<GRULayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<GRULayer>> for Ptr<Layer>

fn from(s: Ptr<GRULayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<GatherElementsLayer>> for Ptr<Algorithm>

fn from(s: Ptr<GatherElementsLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<GatherElementsLayer>> for Ptr<Layer>

fn from(s: Ptr<GatherElementsLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<GatherLayer>> for Ptr<Algorithm>

fn from(s: Ptr<GatherLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<GatherLayer>> for Ptr<Layer>

fn from(s: Ptr<GatherLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<GaussianMotionFilter>> for Ptr<IMotionStabilizer>

fn from(s: Ptr<GaussianMotionFilter>) -> Self

Converts to this type from the input type.

impl From<Ptr<GaussianMotionFilter>> for Ptr<MotionFilterBase>

fn from(s: Ptr<GaussianMotionFilter>) -> Self

Converts to this type from the input type.

impl From<Ptr<GeluApproximationLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<GeluApproximationLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<GeluApproximationLayer>> for Ptr<Algorithm>

fn from(s: Ptr<GeluApproximationLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<GeluApproximationLayer>> for Ptr<Layer>

fn from(s: Ptr<GeluApproximationLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<GeluLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<GeluLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<GeluLayer>> for Ptr<Algorithm>

fn from(s: Ptr<GeluLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<GeluLayer>> for Ptr<Layer>

fn from(s: Ptr<GeluLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<GemmLayer>> for Ptr<Algorithm>

fn from(s: Ptr<GemmLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<GemmLayer>> for Ptr<Layer>

fn from(s: Ptr<GemmLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<GeneralizedHough>> for Ptr<Algorithm>

fn from(s: Ptr<GeneralizedHough>) -> Self

Converts to this type from the input type.

impl From<Ptr<GeneralizedHoughBallard>> for Ptr<Algorithm>

fn from(s: Ptr<GeneralizedHoughBallard>) -> Self

Converts to this type from the input type.

impl From<Ptr<GeneralizedHoughBallard>> for Ptr<GeneralizedHough>

fn from(s: Ptr<GeneralizedHoughBallard>) -> Self

Converts to this type from the input type.

impl From<Ptr<GeneralizedHoughGuil>> for Ptr<Algorithm>

fn from(s: Ptr<GeneralizedHoughGuil>) -> Self

Converts to this type from the input type.

impl From<Ptr<GeneralizedHoughGuil>> for Ptr<GeneralizedHough>

fn from(s: Ptr<GeneralizedHoughGuil>) -> Self

Converts to this type from the input type.

impl From<Ptr<GraphSegmentation>> for Ptr<Algorithm>

fn from(s: Ptr<GraphSegmentation>) -> Self

Converts to this type from the input type.

impl From<Ptr<GrayCodePattern>> for Ptr<Algorithm>

fn from(s: Ptr<GrayCodePattern>) -> Self

Converts to this type from the input type.

impl From<Ptr<GrayCodePattern>> for Ptr<StructuredLightPattern>

fn from(s: Ptr<GrayCodePattern>) -> Self

Converts to this type from the input type.

impl From<Ptr<GrayworldWB>> for Ptr<Algorithm>

fn from(s: Ptr<GrayworldWB>) -> Self

Converts to this type from the input type.

impl From<Ptr<GrayworldWB>> for Ptr<WhiteBalancer>

fn from(s: Ptr<GrayworldWB>) -> Self

Converts to this type from the input type.

impl From<Ptr<GridBoard>> for Ptr<Board>

fn from(s: Ptr<GridBoard>) -> Self

Converts to this type from the input type.

impl From<Ptr<GuidedFilter>> for Ptr<Algorithm>

fn from(s: Ptr<GuidedFilter>) -> Self

Converts to this type from the input type.

impl From<Ptr<HardSigmoidLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<HardSigmoidLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<HardSigmoidLayer>> for Ptr<Algorithm>

fn from(s: Ptr<HardSigmoidLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<HardSigmoidLayer>> for Ptr<Layer>

fn from(s: Ptr<HardSigmoidLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<HardSwishLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<HardSwishLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<HardSwishLayer>> for Ptr<Algorithm>

fn from(s: Ptr<HardSwishLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<HardSwishLayer>> for Ptr<Layer>

fn from(s: Ptr<HardSwishLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<HarrisLaplaceFeatureDetector>> for Ptr<Algorithm>

fn from(s: Ptr<HarrisLaplaceFeatureDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<HarrisLaplaceFeatureDetector>> for Ptr<Feature2D>

fn from(s: Ptr<HarrisLaplaceFeatureDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<HausdorffDistanceExtractor>> for Ptr<Algorithm>

fn from(s: Ptr<HausdorffDistanceExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<HausdorffDistanceExtractor>> for Ptr<ShapeDistanceExtractor>

fn from(s: Ptr<HausdorffDistanceExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<HfsSegment>> for Ptr<Algorithm>

fn from(s: Ptr<HfsSegment>) -> Self

Converts to this type from the input type.

impl From<Ptr<HierarchicalClusteringIndexParams>> for Ptr<IndexParams>

fn from(s: Ptr<HierarchicalClusteringIndexParams>) -> Self

Converts to this type from the input type.

impl From<Ptr<HistogramCostExtractor>> for Ptr<Algorithm>

fn from(s: Ptr<HistogramCostExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<HistogramPhaseUnwrapping>> for Ptr<Algorithm>

fn from(s: Ptr<HistogramPhaseUnwrapping>) -> Self

Converts to this type from the input type.

impl From<Ptr<HistogramPhaseUnwrapping>> for Ptr<PhaseUnwrapping>

fn from(s: Ptr<HistogramPhaseUnwrapping>) -> Self

Converts to this type from the input type.

impl From<Ptr<ICPOdometry>> for Ptr<Algorithm>

fn from(s: Ptr<ICPOdometry>) -> Self

Converts to this type from the input type.

impl From<Ptr<ICPOdometry>> for Ptr<Odometry>

fn from(s: Ptr<ICPOdometry>) -> Self

Converts to this type from the input type.

impl From<Ptr<ImgHashBase>> for Ptr<Algorithm>

fn from(s: Ptr<ImgHashBase>) -> Self

Converts to this type from the input type.

impl From<Ptr<InnerProductLayer>> for Ptr<Algorithm>

fn from(s: Ptr<InnerProductLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<InnerProductLayer>> for Ptr<Layer>

fn from(s: Ptr<InnerProductLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<InnerProductLayerInt8>> for Ptr<Algorithm>

fn from(s: Ptr<InnerProductLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<InnerProductLayerInt8>> for Ptr<InnerProductLayer>

fn from(s: Ptr<InnerProductLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<InnerProductLayerInt8>> for Ptr<Layer>

fn from(s: Ptr<InnerProductLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<InpaintingPipeline>> for Ptr<InpainterBase>

fn from(s: Ptr<InpaintingPipeline>) -> Self

Converts to this type from the input type.

impl From<Ptr<InstanceNormLayer>> for Ptr<Algorithm>

fn from(s: Ptr<InstanceNormLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<InstanceNormLayer>> for Ptr<Layer>

fn from(s: Ptr<InstanceNormLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<InterpLayer>> for Ptr<Algorithm>

fn from(s: Ptr<InterpLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<InterpLayer>> for Ptr<Layer>

fn from(s: Ptr<InterpLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<KAZE>> for Ptr<Algorithm>

fn from(s: Ptr<KAZE>) -> Self

Converts to this type from the input type.

impl From<Ptr<KAZE>> for Ptr<Feature2D>

fn from(s: Ptr<KAZE>) -> Self

Converts to this type from the input type.

impl From<Ptr<KDTreeIndexParams>> for Ptr<IndexParams>

fn from(s: Ptr<KDTreeIndexParams>) -> Self

Converts to this type from the input type.

impl From<Ptr<KMeansIndexParams>> for Ptr<IndexParams>

fn from(s: Ptr<KMeansIndexParams>) -> Self

Converts to this type from the input type.

impl From<Ptr<KNearest>> for Ptr<Algorithm>

fn from(s: Ptr<KNearest>) -> Self

Converts to this type from the input type.

impl From<Ptr<KNearest>> for Ptr<StatModel>

fn from(s: Ptr<KNearest>) -> Self

Converts to this type from the input type.

impl From<Ptr<KeypointBasedMotionEstimator>> for Ptr<ImageMotionEstimatorBase>

fn from(s: Ptr<KeypointBasedMotionEstimator>) -> Self

Converts to this type from the input type.

impl From<Ptr<KeypointBasedMotionEstimatorGpu>> for Ptr<ImageMotionEstimatorBase>

fn from(s: Ptr<KeypointBasedMotionEstimatorGpu>) -> Self

Converts to this type from the input type.

impl From<Ptr<LATCH>> for Ptr<Algorithm>

fn from(s: Ptr<LATCH>) -> Self

Converts to this type from the input type.

impl From<Ptr<LATCH>> for Ptr<Feature2D>

fn from(s: Ptr<LATCH>) -> Self

Converts to this type from the input type.

impl From<Ptr<LBPHFaceRecognizer>> for Ptr<Algorithm>

fn from(s: Ptr<LBPHFaceRecognizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<LBPHFaceRecognizer>> for Ptr<FaceRecognizer>

fn from(s: Ptr<LBPHFaceRecognizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<LMSolver>> for Ptr<Algorithm>

fn from(s: Ptr<LMSolver>) -> Self

Converts to this type from the input type.

impl From<Ptr<LRNLayer>> for Ptr<Algorithm>

fn from(s: Ptr<LRNLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<LRNLayer>> for Ptr<Layer>

fn from(s: Ptr<LRNLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<LSDDetector>> for Ptr<Algorithm>

fn from(s: Ptr<LSDDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<LSTMLayer>> for Ptr<Algorithm>

fn from(s: Ptr<LSTMLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<LSTMLayer>> for Ptr<Layer>

fn from(s: Ptr<LSTMLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<LUCID>> for Ptr<Algorithm>

fn from(s: Ptr<LUCID>) -> Self

Converts to this type from the input type.

impl From<Ptr<LUCID>> for Ptr<Feature2D>

fn from(s: Ptr<LUCID>) -> Self

Converts to this type from the input type.

impl From<Ptr<Layer>> for Ptr<Algorithm>

fn from(s: Ptr<Layer>) -> Self

Converts to this type from the input type.

impl From<Ptr<LayerNormLayer>> for Ptr<Algorithm>

fn from(s: Ptr<LayerNormLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<LayerNormLayer>> for Ptr<Layer>

fn from(s: Ptr<LayerNormLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<LearningBasedWB>> for Ptr<Algorithm>

fn from(s: Ptr<LearningBasedWB>) -> Self

Converts to this type from the input type.

impl From<Ptr<LearningBasedWB>> for Ptr<WhiteBalancer>

fn from(s: Ptr<LearningBasedWB>) -> Self

Converts to this type from the input type.

impl From<Ptr<LineMod_ColorGradient>> for Ptr<LineMod_Modality>

fn from(s: Ptr<LineMod_ColorGradient>) -> Self

Converts to this type from the input type.

impl From<Ptr<LineMod_DepthNormal>> for Ptr<LineMod_Modality>

fn from(s: Ptr<LineMod_DepthNormal>) -> Self

Converts to this type from the input type.

impl From<Ptr<LineSegmentDetector>> for Ptr<Algorithm>

fn from(s: Ptr<LineSegmentDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<LinearIndexParams>> for Ptr<IndexParams>

fn from(s: Ptr<LinearIndexParams>) -> Self

Converts to this type from the input type.

impl From<Ptr<LogLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<LogLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<LogLayer>> for Ptr<Algorithm>

fn from(s: Ptr<LogLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<LogLayer>> for Ptr<Layer>

fn from(s: Ptr<LogLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<LogToStdout>> for Ptr<ILog>

fn from(s: Ptr<LogToStdout>) -> Self

Converts to this type from the input type.

impl From<Ptr<LogisticRegression>> for Ptr<Algorithm>

fn from(s: Ptr<LogisticRegression>) -> Self

Converts to this type from the input type.

impl From<Ptr<LogisticRegression>> for Ptr<StatModel>

fn from(s: Ptr<LogisticRegression>) -> Self

Converts to this type from the input type.

impl From<Ptr<LookUpTable>> for Ptr<Algorithm>

fn from(s: Ptr<LookUpTable>) -> Self

Converts to this type from the input type.

impl From<Ptr<LpMotionStabilizer>> for Ptr<IMotionStabilizer>

fn from(s: Ptr<LpMotionStabilizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<LshIndexParams>> for Ptr<IndexParams>

fn from(s: Ptr<LshIndexParams>) -> Self

Converts to this type from the input type.

impl From<Ptr<MACE>> for Ptr<Algorithm>

fn from(s: Ptr<MACE>) -> Self

Converts to this type from the input type.

impl From<Ptr<MCC_CCheckerDetector>> for Ptr<Algorithm>

fn from(s: Ptr<MCC_CCheckerDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<MSDDetector>> for Ptr<Algorithm>

fn from(s: Ptr<MSDDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<MSDDetector>> for Ptr<Feature2D>

fn from(s: Ptr<MSDDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<MSER>> for Ptr<Algorithm>

fn from(s: Ptr<MSER>) -> Self

Converts to this type from the input type.

impl From<Ptr<MSER>> for Ptr<Feature2D>

fn from(s: Ptr<MSER>) -> Self

Converts to this type from the input type.

impl From<Ptr<MVNLayer>> for Ptr<Algorithm>

fn from(s: Ptr<MVNLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<MVNLayer>> for Ptr<Layer>

fn from(s: Ptr<MVNLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<MarrHildrethHash>> for Ptr<Algorithm>

fn from(s: Ptr<MarrHildrethHash>) -> Self

Converts to this type from the input type.

impl From<Ptr<MarrHildrethHash>> for Ptr<ImgHashBase>

fn from(s: Ptr<MarrHildrethHash>) -> Self

Converts to this type from the input type.

impl From<Ptr<MaskFrameSource>> for Ptr<IFrameSource>

fn from(s: Ptr<MaskFrameSource>) -> Self

Converts to this type from the input type.

impl From<Ptr<MatMulLayer>> for Ptr<Algorithm>

fn from(s: Ptr<MatMulLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<MatMulLayer>> for Ptr<Layer>

fn from(s: Ptr<MatMulLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<MaxUnpoolLayer>> for Ptr<Algorithm>

fn from(s: Ptr<MaxUnpoolLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<MaxUnpoolLayer>> for Ptr<Layer>

fn from(s: Ptr<MaxUnpoolLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<MercatorWarper>> for Ptr<WarperCreator>

fn from(s: Ptr<MercatorWarper>) -> Self

Converts to this type from the input type.

impl From<Ptr<MergeDebevec>> for Ptr<Algorithm>

fn from(s: Ptr<MergeDebevec>) -> Self

Converts to this type from the input type.

impl From<Ptr<MergeDebevec>> for Ptr<MergeExposures>

fn from(s: Ptr<MergeDebevec>) -> Self

Converts to this type from the input type.

impl From<Ptr<MergeExposures>> for Ptr<Algorithm>

fn from(s: Ptr<MergeExposures>) -> Self

Converts to this type from the input type.

impl From<Ptr<MergeMertens>> for Ptr<Algorithm>

fn from(s: Ptr<MergeMertens>) -> Self

Converts to this type from the input type.

impl From<Ptr<MergeMertens>> for Ptr<MergeExposures>

fn from(s: Ptr<MergeMertens>) -> Self

Converts to this type from the input type.

impl From<Ptr<MergeRobertson>> for Ptr<Algorithm>

fn from(s: Ptr<MergeRobertson>) -> Self

Converts to this type from the input type.

impl From<Ptr<MergeRobertson>> for Ptr<MergeExposures>

fn from(s: Ptr<MergeRobertson>) -> Self

Converts to this type from the input type.

impl From<Ptr<MinProblemSolver>> for Ptr<Algorithm>

fn from(s: Ptr<MinProblemSolver>) -> Self

Converts to this type from the input type.

impl From<Ptr<MishLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<MishLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<MishLayer>> for Ptr<Algorithm>

fn from(s: Ptr<MishLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<MishLayer>> for Ptr<Layer>

fn from(s: Ptr<MishLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<MoreAccurateMotionWobbleSuppressor>> for Ptr<MoreAccurateMotionWobbleSuppressorBase>

fn from(s: Ptr<MoreAccurateMotionWobbleSuppressor>) -> Self

Converts to this type from the input type.

impl From<Ptr<MoreAccurateMotionWobbleSuppressor>> for Ptr<WobbleSuppressorBase>

fn from(s: Ptr<MoreAccurateMotionWobbleSuppressor>) -> Self

Converts to this type from the input type.

impl From<Ptr<MoreAccurateMotionWobbleSuppressorBase>> for Ptr<WobbleSuppressorBase>

fn from(s: Ptr<MoreAccurateMotionWobbleSuppressorBase>) -> Self

Converts to this type from the input type.

impl From<Ptr<MoreAccurateMotionWobbleSuppressorGpu>> for Ptr<MoreAccurateMotionWobbleSuppressorBase>

fn from(s: Ptr<MoreAccurateMotionWobbleSuppressorGpu>) -> Self

Converts to this type from the input type.

impl From<Ptr<MoreAccurateMotionWobbleSuppressorGpu>> for Ptr<WobbleSuppressorBase>

fn from(s: Ptr<MoreAccurateMotionWobbleSuppressorGpu>) -> Self

Converts to this type from the input type.

impl From<Ptr<MotionEstimatorL1>> for Ptr<MotionEstimatorBase>

fn from(s: Ptr<MotionEstimatorL1>) -> Self

Converts to this type from the input type.

impl From<Ptr<MotionEstimatorRansacL2>> for Ptr<MotionEstimatorBase>

fn from(s: Ptr<MotionEstimatorRansacL2>) -> Self

Converts to this type from the input type.

impl From<Ptr<MotionFilterBase>> for Ptr<IMotionStabilizer>

fn from(s: Ptr<MotionFilterBase>) -> Self

Converts to this type from the input type.

impl From<Ptr<MotionInpainter>> for Ptr<InpainterBase>

fn from(s: Ptr<MotionInpainter>) -> Self

Converts to this type from the input type.

impl From<Ptr<MotionSaliency>> for Ptr<Algorithm>

fn from(s: Ptr<MotionSaliency>) -> Self

Converts to this type from the input type.

impl From<Ptr<MotionSaliency>> for Ptr<Saliency>

fn from(s: Ptr<MotionSaliency>) -> Self

Converts to this type from the input type.

impl From<Ptr<MotionSaliencyBinWangApr2014>> for Ptr<Algorithm>

fn from(s: Ptr<MotionSaliencyBinWangApr2014>) -> Self

Converts to this type from the input type.

impl From<Ptr<MotionSaliencyBinWangApr2014>> for Ptr<MotionSaliency>

fn from(s: Ptr<MotionSaliencyBinWangApr2014>) -> Self

Converts to this type from the input type.

impl From<Ptr<MotionSaliencyBinWangApr2014>> for Ptr<Saliency>

fn from(s: Ptr<MotionSaliencyBinWangApr2014>) -> Self

Converts to this type from the input type.

impl From<Ptr<MotionStabilizationPipeline>> for Ptr<IMotionStabilizer>

fn from(s: Ptr<MotionStabilizationPipeline>) -> Self

Converts to this type from the input type.

impl From<Ptr<NaryEltwiseLayer>> for Ptr<Algorithm>

fn from(s: Ptr<NaryEltwiseLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<NaryEltwiseLayer>> for Ptr<Layer>

fn from(s: Ptr<NaryEltwiseLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<NormHistogramCostExtractor>> for Ptr<Algorithm>

fn from(s: Ptr<NormHistogramCostExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<NormHistogramCostExtractor>> for Ptr<HistogramCostExtractor>

fn from(s: Ptr<NormHistogramCostExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<NormalBayesClassifier>> for Ptr<Algorithm>

fn from(s: Ptr<NormalBayesClassifier>) -> Self

Converts to this type from the input type.

impl From<Ptr<NormalBayesClassifier>> for Ptr<StatModel>

fn from(s: Ptr<NormalBayesClassifier>) -> Self

Converts to this type from the input type.

impl From<Ptr<NormalizeBBoxLayer>> for Ptr<Algorithm>

fn from(s: Ptr<NormalizeBBoxLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<NormalizeBBoxLayer>> for Ptr<Layer>

fn from(s: Ptr<NormalizeBBoxLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<NotLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<NotLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<NotLayer>> for Ptr<Algorithm>

fn from(s: Ptr<NotLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<NotLayer>> for Ptr<Layer>

fn from(s: Ptr<NotLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<NullDeblurer>> for Ptr<DeblurerBase>

fn from(s: Ptr<NullDeblurer>) -> Self

Converts to this type from the input type.

impl From<Ptr<NullFrameSource>> for Ptr<IFrameSource>

fn from(s: Ptr<NullFrameSource>) -> Self

Converts to this type from the input type.

impl From<Ptr<NullInpainter>> for Ptr<InpainterBase>

fn from(s: Ptr<NullInpainter>) -> Self

Converts to this type from the input type.

impl From<Ptr<NullLog>> for Ptr<ILog>

fn from(s: Ptr<NullLog>) -> Self

Converts to this type from the input type.

impl From<Ptr<NullOutlierRejector>> for Ptr<IOutlierRejector>

fn from(s: Ptr<NullOutlierRejector>) -> Self

Converts to this type from the input type.

impl From<Ptr<NullWobbleSuppressor>> for Ptr<WobbleSuppressorBase>

fn from(s: Ptr<NullWobbleSuppressor>) -> Self

Converts to this type from the input type.

impl From<Ptr<OCRBeamSearchDecoder>> for Ptr<BaseOCR>

fn from(s: Ptr<OCRBeamSearchDecoder>) -> Self

Converts to this type from the input type.

impl From<Ptr<OCRHMMDecoder>> for Ptr<BaseOCR>

fn from(s: Ptr<OCRHMMDecoder>) -> Self

Converts to this type from the input type.

impl From<Ptr<OCRHolisticWordRecognizer>> for Ptr<BaseOCR>

fn from(s: Ptr<OCRHolisticWordRecognizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<OCRTesseract>> for Ptr<BaseOCR>

fn from(s: Ptr<OCRTesseract>) -> Self

Converts to this type from the input type.

impl From<Ptr<ORB>> for Ptr<Algorithm>

fn from(s: Ptr<ORB>) -> Self

Converts to this type from the input type.

impl From<Ptr<ORB>> for Ptr<Feature2D>

fn from(s: Ptr<ORB>) -> Self

Converts to this type from the input type.

impl From<Ptr<Objectness>> for Ptr<Algorithm>

fn from(s: Ptr<Objectness>) -> Self

Converts to this type from the input type.

impl From<Ptr<Objectness>> for Ptr<Saliency>

fn from(s: Ptr<Objectness>) -> Self

Converts to this type from the input type.

impl From<Ptr<ObjectnessBING>> for Ptr<Algorithm>

fn from(s: Ptr<ObjectnessBING>) -> Self

Converts to this type from the input type.

impl From<Ptr<ObjectnessBING>> for Ptr<Objectness>

fn from(s: Ptr<ObjectnessBING>) -> Self

Converts to this type from the input type.

impl From<Ptr<ObjectnessBING>> for Ptr<Saliency>

fn from(s: Ptr<ObjectnessBING>) -> Self

Converts to this type from the input type.

impl From<Ptr<Odometry>> for Ptr<Algorithm>

fn from(s: Ptr<Odometry>) -> Self

Converts to this type from the input type.

impl From<Ptr<OdometryFrame>> for Ptr<RgbdFrame>

fn from(s: Ptr<OdometryFrame>) -> Self

Converts to this type from the input type.

impl From<Ptr<OnePassStabilizer>> for Ptr<IFrameSource>

fn from(s: Ptr<OnePassStabilizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<OnePassStabilizer>> for Ptr<StabilizerBase>

fn from(s: Ptr<OnePassStabilizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<OpticalFlowPCAFlow>> for Ptr<Algorithm>

fn from(s: Ptr<OpticalFlowPCAFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<OpticalFlowPCAFlow>> for Ptr<DenseOpticalFlow>

fn from(s: Ptr<OpticalFlowPCAFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<PCTSignatures>> for Ptr<Algorithm>

fn from(s: Ptr<PCTSignatures>) -> Self

Converts to this type from the input type.

impl From<Ptr<PCTSignaturesSQFD>> for Ptr<Algorithm>

fn from(s: Ptr<PCTSignaturesSQFD>) -> Self

Converts to this type from the input type.

impl From<Ptr<PHash>> for Ptr<Algorithm>

fn from(s: Ptr<PHash>) -> Self

Converts to this type from the input type.

impl From<Ptr<PHash>> for Ptr<ImgHashBase>

fn from(s: Ptr<PHash>) -> Self

Converts to this type from the input type.

impl From<Ptr<PaddingLayer>> for Ptr<Algorithm>

fn from(s: Ptr<PaddingLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<PaddingLayer>> for Ptr<Layer>

fn from(s: Ptr<PaddingLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<PaniniPortraitWarper>> for Ptr<WarperCreator>

fn from(s: Ptr<PaniniPortraitWarper>) -> Self

Converts to this type from the input type.

impl From<Ptr<PaniniWarper>> for Ptr<WarperCreator>

fn from(s: Ptr<PaniniWarper>) -> Self

Converts to this type from the input type.

impl From<Ptr<PermuteLayer>> for Ptr<Algorithm>

fn from(s: Ptr<PermuteLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<PermuteLayer>> for Ptr<Layer>

fn from(s: Ptr<PermuteLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<PhaseUnwrapping>> for Ptr<Algorithm>

fn from(s: Ptr<PhaseUnwrapping>) -> Self

Converts to this type from the input type.

impl From<Ptr<PlaneWarper>> for Ptr<WarperCreator>

fn from(s: Ptr<PlaneWarper>) -> Self

Converts to this type from the input type.

impl From<Ptr<PlaneWarperGpu>> for Ptr<WarperCreator>

fn from(s: Ptr<PlaneWarperGpu>) -> Self

Converts to this type from the input type.

impl From<Ptr<Plot2d>> for Ptr<Algorithm>

fn from(s: Ptr<Plot2d>) -> Self

Converts to this type from the input type.

impl From<Ptr<PoolingLayer>> for Ptr<Algorithm>

fn from(s: Ptr<PoolingLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<PoolingLayer>> for Ptr<Layer>

fn from(s: Ptr<PoolingLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<PoolingLayerInt8>> for Ptr<Algorithm>

fn from(s: Ptr<PoolingLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<PoolingLayerInt8>> for Ptr<Layer>

fn from(s: Ptr<PoolingLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<PoolingLayerInt8>> for Ptr<PoolingLayer>

fn from(s: Ptr<PoolingLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<PowerLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<PowerLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<PowerLayer>> for Ptr<Algorithm>

fn from(s: Ptr<PowerLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<PowerLayer>> for Ptr<Layer>

fn from(s: Ptr<PowerLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<PriorBoxLayer>> for Ptr<Algorithm>

fn from(s: Ptr<PriorBoxLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<PriorBoxLayer>> for Ptr<Layer>

fn from(s: Ptr<PriorBoxLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ProposalLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ProposalLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ProposalLayer>> for Ptr<Layer>

fn from(s: Ptr<ProposalLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<QualityBRISQUE>> for Ptr<Algorithm>

fn from(s: Ptr<QualityBRISQUE>) -> Self

Converts to this type from the input type.

impl From<Ptr<QualityBRISQUE>> for Ptr<QualityBase>

fn from(s: Ptr<QualityBRISQUE>) -> Self

Converts to this type from the input type.

impl From<Ptr<QualityBase>> for Ptr<Algorithm>

fn from(s: Ptr<QualityBase>) -> Self

Converts to this type from the input type.

impl From<Ptr<QualityGMSD>> for Ptr<Algorithm>

fn from(s: Ptr<QualityGMSD>) -> Self

Converts to this type from the input type.

impl From<Ptr<QualityGMSD>> for Ptr<QualityBase>

fn from(s: Ptr<QualityGMSD>) -> Self

Converts to this type from the input type.

impl From<Ptr<QualityMSE>> for Ptr<Algorithm>

fn from(s: Ptr<QualityMSE>) -> Self

Converts to this type from the input type.

impl From<Ptr<QualityMSE>> for Ptr<QualityBase>

fn from(s: Ptr<QualityMSE>) -> Self

Converts to this type from the input type.

impl From<Ptr<QualityPSNR>> for Ptr<Algorithm>

fn from(s: Ptr<QualityPSNR>) -> Self

Converts to this type from the input type.

impl From<Ptr<QualityPSNR>> for Ptr<QualityBase>

fn from(s: Ptr<QualityPSNR>) -> Self

Converts to this type from the input type.

impl From<Ptr<QualitySSIM>> for Ptr<Algorithm>

fn from(s: Ptr<QualitySSIM>) -> Self

Converts to this type from the input type.

impl From<Ptr<QualitySSIM>> for Ptr<QualityBase>

fn from(s: Ptr<QualitySSIM>) -> Self

Converts to this type from the input type.

impl From<Ptr<QuantizeLayer>> for Ptr<Algorithm>

fn from(s: Ptr<QuantizeLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<QuantizeLayer>> for Ptr<Layer>

fn from(s: Ptr<QuantizeLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<RFFeatureGetter>> for Ptr<Algorithm>

fn from(s: Ptr<RFFeatureGetter>) -> Self

Converts to this type from the input type.

impl From<Ptr<RICInterpolator>> for Ptr<Algorithm>

fn from(s: Ptr<RICInterpolator>) -> Self

Converts to this type from the input type.

impl From<Ptr<RICInterpolator>> for Ptr<SparseMatchInterpolator>

fn from(s: Ptr<RICInterpolator>) -> Self

Converts to this type from the input type.

impl From<Ptr<RNNLayer>> for Ptr<Algorithm>

fn from(s: Ptr<RNNLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<RNNLayer>> for Ptr<Layer>

fn from(s: Ptr<RNNLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<RTrees>> for Ptr<Algorithm>

fn from(s: Ptr<RTrees>) -> Self

Converts to this type from the input type.

impl From<Ptr<RTrees>> for Ptr<DTrees>

fn from(s: Ptr<RTrees>) -> Self

Converts to this type from the input type.

impl From<Ptr<RTrees>> for Ptr<StatModel>

fn from(s: Ptr<RTrees>) -> Self

Converts to this type from the input type.

impl From<Ptr<RadialVarianceHash>> for Ptr<Algorithm>

fn from(s: Ptr<RadialVarianceHash>) -> Self

Converts to this type from the input type.

impl From<Ptr<RadialVarianceHash>> for Ptr<ImgHashBase>

fn from(s: Ptr<RadialVarianceHash>) -> Self

Converts to this type from the input type.

impl From<Ptr<Rapid_GOSTracker>> for Ptr<Algorithm>

fn from(s: Ptr<Rapid_GOSTracker>) -> Self

Converts to this type from the input type.

impl From<Ptr<Rapid_GOSTracker>> for Ptr<Rapid_Tracker>

fn from(s: Ptr<Rapid_GOSTracker>) -> Self

Converts to this type from the input type.

impl From<Ptr<Rapid_OLSTracker>> for Ptr<Algorithm>

fn from(s: Ptr<Rapid_OLSTracker>) -> Self

Converts to this type from the input type.

impl From<Ptr<Rapid_OLSTracker>> for Ptr<Rapid_Tracker>

fn from(s: Ptr<Rapid_OLSTracker>) -> Self

Converts to this type from the input type.

impl From<Ptr<Rapid_Rapid>> for Ptr<Algorithm>

fn from(s: Ptr<Rapid_Rapid>) -> Self

Converts to this type from the input type.

impl From<Ptr<Rapid_Rapid>> for Ptr<Rapid_Tracker>

fn from(s: Ptr<Rapid_Rapid>) -> Self

Converts to this type from the input type.

impl From<Ptr<Rapid_Tracker>> for Ptr<Algorithm>

fn from(s: Ptr<Rapid_Tracker>) -> Self

Converts to this type from the input type.

impl From<Ptr<ReLU6Layer>> for Ptr<ActivationLayer>

fn from(s: Ptr<ReLU6Layer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ReLU6Layer>> for Ptr<Algorithm>

fn from(s: Ptr<ReLU6Layer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ReLU6Layer>> for Ptr<Layer>

fn from(s: Ptr<ReLU6Layer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ReLULayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<ReLULayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ReLULayer>> for Ptr<Algorithm>

fn from(s: Ptr<ReLULayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ReLULayer>> for Ptr<Layer>

fn from(s: Ptr<ReLULayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ReciprocalLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<ReciprocalLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ReciprocalLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ReciprocalLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ReciprocalLayer>> for Ptr<Layer>

fn from(s: Ptr<ReciprocalLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ReduceLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ReduceLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ReduceLayer>> for Ptr<Layer>

fn from(s: Ptr<ReduceLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<RegionLayer>> for Ptr<Algorithm>

fn from(s: Ptr<RegionLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<RegionLayer>> for Ptr<Layer>

fn from(s: Ptr<RegionLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ReorgLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ReorgLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ReorgLayer>> for Ptr<Layer>

fn from(s: Ptr<ReorgLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<RequantizeLayer>> for Ptr<Algorithm>

fn from(s: Ptr<RequantizeLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<RequantizeLayer>> for Ptr<Layer>

fn from(s: Ptr<RequantizeLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ReshapeLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ReshapeLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ReshapeLayer>> for Ptr<Layer>

fn from(s: Ptr<ReshapeLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ResizeLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ResizeLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ResizeLayer>> for Ptr<Layer>

fn from(s: Ptr<ResizeLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<Retina>> for Ptr<Algorithm>

fn from(s: Ptr<Retina>) -> Self

Converts to this type from the input type.

impl From<Ptr<RetinaFastToneMapping>> for Ptr<Algorithm>

fn from(s: Ptr<RetinaFastToneMapping>) -> Self

Converts to this type from the input type.

impl From<Ptr<RgbdICPOdometry>> for Ptr<Algorithm>

fn from(s: Ptr<RgbdICPOdometry>) -> Self

Converts to this type from the input type.

impl From<Ptr<RgbdICPOdometry>> for Ptr<Odometry>

fn from(s: Ptr<RgbdICPOdometry>) -> Self

Converts to this type from the input type.

impl From<Ptr<RgbdNormals>> for Ptr<Algorithm>

fn from(s: Ptr<RgbdNormals>) -> Self

Converts to this type from the input type.

impl From<Ptr<RgbdOdometry>> for Ptr<Algorithm>

fn from(s: Ptr<RgbdOdometry>) -> Self

Converts to this type from the input type.

impl From<Ptr<RgbdOdometry>> for Ptr<Odometry>

fn from(s: Ptr<RgbdOdometry>) -> Self

Converts to this type from the input type.

impl From<Ptr<RgbdPlane>> for Ptr<Algorithm>

fn from(s: Ptr<RgbdPlane>) -> Self

Converts to this type from the input type.

impl From<Ptr<RidgeDetectionFilter>> for Ptr<Algorithm>

fn from(s: Ptr<RidgeDetectionFilter>) -> Self

Converts to this type from the input type.

impl From<Ptr<RoundLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<RoundLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<RoundLayer>> for Ptr<Algorithm>

fn from(s: Ptr<RoundLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<RoundLayer>> for Ptr<Layer>

fn from(s: Ptr<RoundLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SFMLibmvEuclideanReconstruction>> for Ptr<BaseSFM>

fn from(s: Ptr<SFMLibmvEuclideanReconstruction>) -> Self

Converts to this type from the input type.

impl From<Ptr<SIFT>> for Ptr<Algorithm>

fn from(s: Ptr<SIFT>) -> Self

Converts to this type from the input type.

impl From<Ptr<SIFT>> for Ptr<Feature2D>

fn from(s: Ptr<SIFT>) -> Self

Converts to this type from the input type.

impl From<Ptr<SURF>> for Ptr<Algorithm>

fn from(s: Ptr<SURF>) -> Self

Converts to this type from the input type.

impl From<Ptr<SURF>> for Ptr<Feature2D>

fn from(s: Ptr<SURF>) -> Self

Converts to this type from the input type.

impl From<Ptr<SVM>> for Ptr<Algorithm>

fn from(s: Ptr<SVM>) -> Self

Converts to this type from the input type.

impl From<Ptr<SVM>> for Ptr<StatModel>

fn from(s: Ptr<SVM>) -> Self

Converts to this type from the input type.

impl From<Ptr<SVMSGD>> for Ptr<Algorithm>

fn from(s: Ptr<SVMSGD>) -> Self

Converts to this type from the input type.

impl From<Ptr<SVMSGD>> for Ptr<StatModel>

fn from(s: Ptr<SVMSGD>) -> Self

Converts to this type from the input type.

impl From<Ptr<SVM_Kernel>> for Ptr<Algorithm>

fn from(s: Ptr<SVM_Kernel>) -> Self

Converts to this type from the input type.

impl From<Ptr<Saliency>> for Ptr<Algorithm>

fn from(s: Ptr<Saliency>) -> Self

Converts to this type from the input type.

impl From<Ptr<SavedIndexParams>> for Ptr<IndexParams>

fn from(s: Ptr<SavedIndexParams>) -> Self

Converts to this type from the input type.

impl From<Ptr<ScaleLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ScaleLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ScaleLayer>> for Ptr<Layer>

fn from(s: Ptr<ScaleLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ScaleLayerInt8>> for Ptr<Algorithm>

fn from(s: Ptr<ScaleLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<ScaleLayerInt8>> for Ptr<Layer>

fn from(s: Ptr<ScaleLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<ScaleLayerInt8>> for Ptr<ScaleLayer>

fn from(s: Ptr<ScaleLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<ScanSegment>> for Ptr<Algorithm>

fn from(s: Ptr<ScanSegment>) -> Self

Converts to this type from the input type.

impl From<Ptr<ScatterLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ScatterLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ScatterLayer>> for Ptr<Layer>

fn from(s: Ptr<ScatterLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ScatterNDLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ScatterNDLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ScatterNDLayer>> for Ptr<Layer>

fn from(s: Ptr<ScatterNDLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SearchParams>> for Ptr<IndexParams>

fn from(s: Ptr<SearchParams>) -> Self

Converts to this type from the input type.

impl From<Ptr<SelectiveSearchSegmentation>> for Ptr<Algorithm>

fn from(s: Ptr<SelectiveSearchSegmentation>) -> Self

Converts to this type from the input type.

impl From<Ptr<SelectiveSearchSegmentationStrategy>> for Ptr<Algorithm>

fn from(s: Ptr<SelectiveSearchSegmentationStrategy>) -> Self

Converts to this type from the input type.

impl From<Ptr<SelectiveSearchSegmentationStrategyColor>> for Ptr<Algorithm>

fn from(s: Ptr<SelectiveSearchSegmentationStrategyColor>) -> Self

Converts to this type from the input type.

impl From<Ptr<SelectiveSearchSegmentationStrategyColor>> for Ptr<SelectiveSearchSegmentationStrategy>

fn from(s: Ptr<SelectiveSearchSegmentationStrategyColor>) -> Self

Converts to this type from the input type.

impl From<Ptr<SelectiveSearchSegmentationStrategyFill>> for Ptr<Algorithm>

fn from(s: Ptr<SelectiveSearchSegmentationStrategyFill>) -> Self

Converts to this type from the input type.

impl From<Ptr<SelectiveSearchSegmentationStrategyFill>> for Ptr<SelectiveSearchSegmentationStrategy>

fn from(s: Ptr<SelectiveSearchSegmentationStrategyFill>) -> Self

Converts to this type from the input type.

impl From<Ptr<SelectiveSearchSegmentationStrategyMultiple>> for Ptr<Algorithm>

fn from(s: Ptr<SelectiveSearchSegmentationStrategyMultiple>) -> Self

Converts to this type from the input type.

impl From<Ptr<SelectiveSearchSegmentationStrategyMultiple>> for Ptr<SelectiveSearchSegmentationStrategy>

fn from(s: Ptr<SelectiveSearchSegmentationStrategyMultiple>) -> Self

Converts to this type from the input type.

impl From<Ptr<SelectiveSearchSegmentationStrategySize>> for Ptr<Algorithm>

fn from(s: Ptr<SelectiveSearchSegmentationStrategySize>) -> Self

Converts to this type from the input type.

impl From<Ptr<SelectiveSearchSegmentationStrategySize>> for Ptr<SelectiveSearchSegmentationStrategy>

fn from(s: Ptr<SelectiveSearchSegmentationStrategySize>) -> Self

Converts to this type from the input type.

impl From<Ptr<SelectiveSearchSegmentationStrategyTexture>> for Ptr<Algorithm>

fn from(s: Ptr<SelectiveSearchSegmentationStrategyTexture>) -> Self

Converts to this type from the input type.

impl From<Ptr<SelectiveSearchSegmentationStrategyTexture>> for Ptr<SelectiveSearchSegmentationStrategy>

fn from(s: Ptr<SelectiveSearchSegmentationStrategyTexture>) -> Self

Converts to this type from the input type.

impl From<Ptr<SeluLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<SeluLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SeluLayer>> for Ptr<Algorithm>

fn from(s: Ptr<SeluLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SeluLayer>> for Ptr<Layer>

fn from(s: Ptr<SeluLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ShapeContextDistanceExtractor>> for Ptr<Algorithm>

fn from(s: Ptr<ShapeContextDistanceExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<ShapeContextDistanceExtractor>> for Ptr<ShapeDistanceExtractor>

fn from(s: Ptr<ShapeContextDistanceExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<ShapeDistanceExtractor>> for Ptr<Algorithm>

fn from(s: Ptr<ShapeDistanceExtractor>) -> Self

Converts to this type from the input type.

impl From<Ptr<ShapeTransformer>> for Ptr<Algorithm>

fn from(s: Ptr<ShapeTransformer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ShiftLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ShiftLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ShiftLayer>> for Ptr<Layer>

fn from(s: Ptr<ShiftLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ShiftLayerInt8>> for Ptr<Algorithm>

fn from(s: Ptr<ShiftLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<ShiftLayerInt8>> for Ptr<Layer>

fn from(s: Ptr<ShiftLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<ShrinkLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<ShrinkLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ShrinkLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ShrinkLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ShrinkLayer>> for Ptr<Layer>

fn from(s: Ptr<ShrinkLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ShuffleChannelLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ShuffleChannelLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ShuffleChannelLayer>> for Ptr<Layer>

fn from(s: Ptr<ShuffleChannelLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SigmoidLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<SigmoidLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SigmoidLayer>> for Ptr<Algorithm>

fn from(s: Ptr<SigmoidLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SigmoidLayer>> for Ptr<Layer>

fn from(s: Ptr<SigmoidLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SignLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<SignLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SignLayer>> for Ptr<Algorithm>

fn from(s: Ptr<SignLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SignLayer>> for Ptr<Layer>

fn from(s: Ptr<SignLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SimpleBlobDetector>> for Ptr<Algorithm>

fn from(s: Ptr<SimpleBlobDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<SimpleBlobDetector>> for Ptr<Feature2D>

fn from(s: Ptr<SimpleBlobDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<SimpleWB>> for Ptr<Algorithm>

fn from(s: Ptr<SimpleWB>) -> Self

Converts to this type from the input type.

impl From<Ptr<SimpleWB>> for Ptr<WhiteBalancer>

fn from(s: Ptr<SimpleWB>) -> Self

Converts to this type from the input type.

impl From<Ptr<SinLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<SinLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SinLayer>> for Ptr<Algorithm>

fn from(s: Ptr<SinLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SinLayer>> for Ptr<Layer>

fn from(s: Ptr<SinLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SinhLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<SinhLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SinhLayer>> for Ptr<Algorithm>

fn from(s: Ptr<SinhLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SinhLayer>> for Ptr<Layer>

fn from(s: Ptr<SinhLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SinusoidalPattern>> for Ptr<Algorithm>

fn from(s: Ptr<SinusoidalPattern>) -> Self

Converts to this type from the input type.

impl From<Ptr<SinusoidalPattern>> for Ptr<StructuredLightPattern>

fn from(s: Ptr<SinusoidalPattern>) -> Self

Converts to this type from the input type.

impl From<Ptr<SliceLayer>> for Ptr<Algorithm>

fn from(s: Ptr<SliceLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SliceLayer>> for Ptr<Layer>

fn from(s: Ptr<SliceLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SoftmaxLayer>> for Ptr<Algorithm>

fn from(s: Ptr<SoftmaxLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SoftmaxLayer>> for Ptr<Layer>

fn from(s: Ptr<SoftmaxLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SoftmaxLayerInt8>> for Ptr<Algorithm>

fn from(s: Ptr<SoftmaxLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<SoftmaxLayerInt8>> for Ptr<Layer>

fn from(s: Ptr<SoftmaxLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<SoftmaxLayerInt8>> for Ptr<SoftmaxLayer>

fn from(s: Ptr<SoftmaxLayerInt8>) -> Self

Converts to this type from the input type.

impl From<Ptr<SoftplusLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<SoftplusLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SoftplusLayer>> for Ptr<Algorithm>

fn from(s: Ptr<SoftplusLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SoftplusLayer>> for Ptr<Layer>

fn from(s: Ptr<SoftplusLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SoftsignLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<SoftsignLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SoftsignLayer>> for Ptr<Algorithm>

fn from(s: Ptr<SoftsignLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SoftsignLayer>> for Ptr<Layer>

fn from(s: Ptr<SoftsignLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SparseMatchInterpolator>> for Ptr<Algorithm>

fn from(s: Ptr<SparseMatchInterpolator>) -> Self

Converts to this type from the input type.

impl From<Ptr<SparseOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<SparseOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<SparsePyrLKOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<SparsePyrLKOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<SparsePyrLKOpticalFlow>> for Ptr<SparseOpticalFlow>

fn from(s: Ptr<SparsePyrLKOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<SparsePyrLkOptFlowEstimator>> for Ptr<ISparseOptFlowEstimator>

fn from(s: Ptr<SparsePyrLkOptFlowEstimator>) -> Self

Converts to this type from the input type.

impl From<Ptr<SparsePyrLkOptFlowEstimator>> for Ptr<PyrLkOptFlowEstimatorBase>

fn from(s: Ptr<SparsePyrLkOptFlowEstimator>) -> Self

Converts to this type from the input type.

impl From<Ptr<SparsePyrLkOptFlowEstimatorGpu>> for Ptr<ISparseOptFlowEstimator>

fn from(s: Ptr<SparsePyrLkOptFlowEstimatorGpu>) -> Self

Converts to this type from the input type.

impl From<Ptr<SparsePyrLkOptFlowEstimatorGpu>> for Ptr<PyrLkOptFlowEstimatorBase>

fn from(s: Ptr<SparsePyrLkOptFlowEstimatorGpu>) -> Self

Converts to this type from the input type.

impl From<Ptr<SparseRLOFOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<SparseRLOFOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<SparseRLOFOpticalFlow>> for Ptr<SparseOpticalFlow>

fn from(s: Ptr<SparseRLOFOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<SphericalWarper>> for Ptr<WarperCreator>

fn from(s: Ptr<SphericalWarper>) -> Self

Converts to this type from the input type.

impl From<Ptr<SphericalWarperGpu>> for Ptr<WarperCreator>

fn from(s: Ptr<SphericalWarperGpu>) -> Self

Converts to this type from the input type.

impl From<Ptr<SplitLayer>> for Ptr<Algorithm>

fn from(s: Ptr<SplitLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SplitLayer>> for Ptr<Layer>

fn from(s: Ptr<SplitLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SqrtLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<SqrtLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SqrtLayer>> for Ptr<Algorithm>

fn from(s: Ptr<SqrtLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SqrtLayer>> for Ptr<Layer>

fn from(s: Ptr<SqrtLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<StandardCollector>> for Ptr<PredictCollector>

fn from(s: Ptr<StandardCollector>) -> Self

Converts to this type from the input type.

impl From<Ptr<StarDetector>> for Ptr<Algorithm>

fn from(s: Ptr<StarDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<StarDetector>> for Ptr<Feature2D>

fn from(s: Ptr<StarDetector>) -> Self

Converts to this type from the input type.

impl From<Ptr<StatModel>> for Ptr<Algorithm>

fn from(s: Ptr<StatModel>) -> Self

Converts to this type from the input type.

impl From<Ptr<StaticSaliency>> for Ptr<Algorithm>

fn from(s: Ptr<StaticSaliency>) -> Self

Converts to this type from the input type.

impl From<Ptr<StaticSaliency>> for Ptr<Saliency>

fn from(s: Ptr<StaticSaliency>) -> Self

Converts to this type from the input type.

impl From<Ptr<StaticSaliencyFineGrained>> for Ptr<Algorithm>

fn from(s: Ptr<StaticSaliencyFineGrained>) -> Self

Converts to this type from the input type.

impl From<Ptr<StaticSaliencyFineGrained>> for Ptr<Saliency>

fn from(s: Ptr<StaticSaliencyFineGrained>) -> Self

Converts to this type from the input type.

impl From<Ptr<StaticSaliencyFineGrained>> for Ptr<StaticSaliency>

fn from(s: Ptr<StaticSaliencyFineGrained>) -> Self

Converts to this type from the input type.

impl From<Ptr<StaticSaliencySpectralResidual>> for Ptr<Algorithm>

fn from(s: Ptr<StaticSaliencySpectralResidual>) -> Self

Converts to this type from the input type.

impl From<Ptr<StaticSaliencySpectralResidual>> for Ptr<Saliency>

fn from(s: Ptr<StaticSaliencySpectralResidual>) -> Self

Converts to this type from the input type.

impl From<Ptr<StaticSaliencySpectralResidual>> for Ptr<StaticSaliency>

fn from(s: Ptr<StaticSaliencySpectralResidual>) -> Self

Converts to this type from the input type.

impl From<Ptr<StereoBM>> for Ptr<Algorithm>

fn from(s: Ptr<StereoBM>) -> Self

Converts to this type from the input type.

impl From<Ptr<StereoBM>> for Ptr<StereoMatcher>

fn from(s: Ptr<StereoBM>) -> Self

Converts to this type from the input type.

impl From<Ptr<StereoMatcher>> for Ptr<Algorithm>

fn from(s: Ptr<StereoMatcher>) -> Self

Converts to this type from the input type.

impl From<Ptr<StereoSGBM>> for Ptr<Algorithm>

fn from(s: Ptr<StereoSGBM>) -> Self

Converts to this type from the input type.

impl From<Ptr<StereoSGBM>> for Ptr<StereoMatcher>

fn from(s: Ptr<StereoSGBM>) -> Self

Converts to this type from the input type.

impl From<Ptr<StereographicWarper>> for Ptr<WarperCreator>

fn from(s: Ptr<StereographicWarper>) -> Self

Converts to this type from the input type.

impl From<Ptr<StructuredEdgeDetection>> for Ptr<Algorithm>

fn from(s: Ptr<StructuredEdgeDetection>) -> Self

Converts to this type from the input type.

impl From<Ptr<StructuredLightPattern>> for Ptr<Algorithm>

fn from(s: Ptr<StructuredLightPattern>) -> Self

Converts to this type from the input type.

impl From<Ptr<SuperRes_BroxOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<SuperRes_BroxOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<SuperRes_BroxOpticalFlow>> for Ptr<SuperRes_DenseOpticalFlowExt>

fn from(s: Ptr<SuperRes_BroxOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<SuperRes_DenseOpticalFlowExt>> for Ptr<Algorithm>

fn from(s: Ptr<SuperRes_DenseOpticalFlowExt>) -> Self

Converts to this type from the input type.

impl From<Ptr<SuperRes_DualTVL1OpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<SuperRes_DualTVL1OpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<SuperRes_DualTVL1OpticalFlow>> for Ptr<SuperRes_DenseOpticalFlowExt>

fn from(s: Ptr<SuperRes_DualTVL1OpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<SuperRes_FarnebackOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<SuperRes_FarnebackOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<SuperRes_FarnebackOpticalFlow>> for Ptr<SuperRes_DenseOpticalFlowExt>

fn from(s: Ptr<SuperRes_FarnebackOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<SuperRes_PyrLKOpticalFlow>> for Ptr<Algorithm>

fn from(s: Ptr<SuperRes_PyrLKOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<SuperRes_PyrLKOpticalFlow>> for Ptr<SuperRes_DenseOpticalFlowExt>

fn from(s: Ptr<SuperRes_PyrLKOpticalFlow>) -> Self

Converts to this type from the input type.

impl From<Ptr<SuperRes_SuperResolution>> for Ptr<Algorithm>

fn from(s: Ptr<SuperRes_SuperResolution>) -> Self

Converts to this type from the input type.

impl From<Ptr<SuperRes_SuperResolution>> for Ptr<SuperRes_FrameSource>

fn from(s: Ptr<SuperRes_SuperResolution>) -> Self

Converts to this type from the input type.

impl From<Ptr<SuperpixelLSC>> for Ptr<Algorithm>

fn from(s: Ptr<SuperpixelLSC>) -> Self

Converts to this type from the input type.

impl From<Ptr<SuperpixelSEEDS>> for Ptr<Algorithm>

fn from(s: Ptr<SuperpixelSEEDS>) -> Self

Converts to this type from the input type.

impl From<Ptr<SuperpixelSLIC>> for Ptr<Algorithm>

fn from(s: Ptr<SuperpixelSLIC>) -> Self

Converts to this type from the input type.

impl From<Ptr<SwishLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<SwishLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SwishLayer>> for Ptr<Algorithm>

fn from(s: Ptr<SwishLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SwishLayer>> for Ptr<Layer>

fn from(s: Ptr<SwishLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<SyntheticSequenceGenerator>> for Ptr<Algorithm>

fn from(s: Ptr<SyntheticSequenceGenerator>) -> Self

Converts to this type from the input type.

impl From<Ptr<TBMR>> for Ptr<AffineFeature2D>

fn from(s: Ptr<TBMR>) -> Self

Converts to this type from the input type.

impl From<Ptr<TBMR>> for Ptr<Algorithm>

fn from(s: Ptr<TBMR>) -> Self

Converts to this type from the input type.

impl From<Ptr<TBMR>> for Ptr<Feature2D>

fn from(s: Ptr<TBMR>) -> Self

Converts to this type from the input type.

impl From<Ptr<TEBLID>> for Ptr<Algorithm>

fn from(s: Ptr<TEBLID>) -> Self

Converts to this type from the input type.

impl From<Ptr<TEBLID>> for Ptr<Feature2D>

fn from(s: Ptr<TEBLID>) -> Self

Converts to this type from the input type.

impl From<Ptr<TanHLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<TanHLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<TanHLayer>> for Ptr<Algorithm>

fn from(s: Ptr<TanHLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<TanHLayer>> for Ptr<Layer>

fn from(s: Ptr<TanHLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<TanLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<TanLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<TanLayer>> for Ptr<Algorithm>

fn from(s: Ptr<TanLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<TanLayer>> for Ptr<Layer>

fn from(s: Ptr<TanLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<TextDetectorCNN>> for Ptr<TextDetector>

fn from(s: Ptr<TextDetectorCNN>) -> Self

Converts to this type from the input type.

impl From<Ptr<ThinPlateSplineShapeTransformer>> for Ptr<Algorithm>

fn from(s: Ptr<ThinPlateSplineShapeTransformer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ThinPlateSplineShapeTransformer>> for Ptr<ShapeTransformer>

fn from(s: Ptr<ThinPlateSplineShapeTransformer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ThresholdedReluLayer>> for Ptr<ActivationLayer>

fn from(s: Ptr<ThresholdedReluLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ThresholdedReluLayer>> for Ptr<Algorithm>

fn from(s: Ptr<ThresholdedReluLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ThresholdedReluLayer>> for Ptr<Layer>

fn from(s: Ptr<ThresholdedReluLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<TileLayer>> for Ptr<Algorithm>

fn from(s: Ptr<TileLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<TileLayer>> for Ptr<Layer>

fn from(s: Ptr<TileLayer>) -> Self

Converts to this type from the input type.

impl From<Ptr<ToFileMotionWriter>> for Ptr<ImageMotionEstimatorBase>

fn from(s: Ptr<ToFileMotionWriter>) -> Self

Converts to this type from the input type.

impl From<Ptr<Tonemap>> for Ptr<Algorithm>

fn from(s: Ptr<Tonemap>) -> Self

Converts to this type from the input type.

impl From<Ptr<TonemapDrago>> for Ptr<Algorithm>

fn from(s: Ptr<TonemapDrago>) -> Self

Converts to this type from the input type.

impl From<Ptr<TonemapDrago>> for Ptr<Tonemap>

fn from(s: Ptr<TonemapDrago>) -> Self

Converts to this type from the input type.

impl From<Ptr<TonemapDurand>> for Ptr<Algorithm>

fn from(s: Ptr<TonemapDurand>) -> Self

Converts to this type from the input type.

impl From<Ptr<TonemapDurand>> for Ptr<Tonemap>

fn from(s: Ptr<TonemapDurand>) -> Self

Converts to this type from the input type.

impl From<Ptr<TonemapMantiuk>> for Ptr<Algorithm>

fn from(s: Ptr<TonemapMantiuk>) -> Self

Converts to this type from the input type.

impl From<Ptr<TonemapMantiuk>> for Ptr<Tonemap>

fn from(s: Ptr<TonemapMantiuk>) -> Self

Converts to this type from the input type.

impl From<Ptr<TonemapReinhard>> for Ptr<Algorithm>

fn from(s: Ptr<TonemapReinhard>) -> Self

Converts to this type from the input type.

impl From<Ptr<TonemapReinhard>> for Ptr<Tonemap>

fn from(s: Ptr<TonemapReinhard>) -> Self

Converts to this type from the input type.

impl From<Ptr<TrackerCSRT>> for Ptr<Tracker>

fn from(s: Ptr<TrackerCSRT>) -> Self

Converts to this type from the input type.

impl From<Ptr<TrackerDaSiamRPN>> for Ptr<Tracker>

fn from(s: Ptr<TrackerDaSiamRPN>) -> Self

Converts to this type from the input type.

impl From<Ptr<TrackerGOTURN>> for Ptr<Tracker>

fn from(s: Ptr<TrackerGOTURN>) -> Self

Converts to this type from the input type.

impl From<Ptr<TrackerKCF>> for Ptr<Tracker>

fn from(s: Ptr<TrackerKCF>) -> Self

Converts to this type from the input type.

impl From<Ptr<TrackerMIL>> for Ptr<Tracker>

fn from(s: Ptr<TrackerMIL>) -> Self

Converts to this type from the input type.

impl From<Ptr<TrackerNano>> for Ptr<Tracker>

fn from(s: Ptr<TrackerNano>) -> Self

Converts to this type from the input type.

impl From<Ptr<TrackerVit>> for Ptr<Tracker>

fn from(s: Ptr<TrackerVit>) -> Self

Converts to this type from the input type.

impl From<Ptr<TransientAreasSegmentationModule>> for Ptr<Algorithm>

fn from(s: Ptr<TransientAreasSegmentationModule>) -> Self

Converts to this type from the input type.

impl From<Ptr<TranslationBasedLocalOutlierRejector>> for Ptr<IOutlierRejector>

fn from(s: Ptr<TranslationBasedLocalOutlierRejector>) -> Self

Converts to this type from the input type.

impl From<Ptr<TransverseMercatorWarper>> for Ptr<WarperCreator>

fn from(s: Ptr<TransverseMercatorWarper>) -> Self

Converts to this type from the input type.

impl From<Ptr<TwoPassStabilizer>> for Ptr<IFrameSource>

fn from(s: Ptr<TwoPassStabilizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<TwoPassStabilizer>> for Ptr<StabilizerBase>

fn from(s: Ptr<TwoPassStabilizer>) -> Self

Converts to this type from the input type.

impl From<Ptr<VGG>> for Ptr<Algorithm>

fn from(s: Ptr<VGG>) -> Self

Converts to this type from the input type.

impl From<Ptr<VGG>> for Ptr<Feature2D>

fn from(s: Ptr<VGG>) -> Self

Converts to this type from the input type.

impl From<Ptr<VariationalRefinement>> for Ptr<Algorithm>

fn from(s: Ptr<VariationalRefinement>) -> Self

Converts to this type from the input type.

impl From<Ptr<VariationalRefinement>> for Ptr<DenseOpticalFlow>

fn from(s: Ptr<VariationalRefinement>) -> Self

Converts to this type from the input type.

impl From<Ptr<VideoFileSource>> for Ptr<IFrameSource>

fn from(s: Ptr<VideoFileSource>) -> Self

Converts to this type from the input type.

impl From<Ptr<WeightingDeblurer>> for Ptr<DeblurerBase>

fn from(s: Ptr<WeightingDeblurer>) -> Self

Converts to this type from the input type.

impl From<Ptr<WhiteBalancer>> for Ptr<Algorithm>

fn from(s: Ptr<WhiteBalancer>) -> Self

Converts to this type from the input type.

impl FromFileMotionReaderTrait for Ptr<FromFileMotionReader>

fn as_raw_mut_FromFileMotionReader(&mut self) -> *mut c_void

fn estimate( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst, ok: &mut bool ) -> Result<Mat>

C++ default parameters

fn estimate_def( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst ) -> Result<Mat>

Note

impl FromFileMotionReaderTraitConst for Ptr<FromFileMotionReader>

fn as_raw_FromFileMotionReader(&self) -> *const c_void

impl GFTTDetectorTrait for Ptr<GFTTDetector>

fn as_raw_mut_GFTTDetector(&mut self) -> *mut c_void

fn set_max_features(&mut self, max_features: i32) -> Result<()>

fn set_quality_level(&mut self, qlevel: f64) -> Result<()>

fn set_min_distance(&mut self, min_distance: f64) -> Result<()>

fn set_block_size(&mut self, block_size: i32) -> Result<()>

fn set_gradient_size(&mut self, gradient_size_: i32) -> Result<()>

fn get_gradient_size(&mut self) -> Result<i32>

fn set_harris_detector(&mut self, val: bool) -> Result<()>

fn set_k(&mut self, k: f64) -> Result<()>

impl GFTTDetectorTraitConst for Ptr<GFTTDetector>

fn as_raw_GFTTDetector(&self) -> *const c_void

fn get_max_features(&self) -> Result<i32>

fn get_quality_level(&self) -> Result<f64>

fn get_min_distance(&self) -> Result<f64>

fn get_block_size(&self) -> Result<i32>

fn get_harris_detector(&self) -> Result<bool>

fn get_k(&self) -> Result<f64>

fn get_default_name(&self) -> Result<String>

impl GPCTrainingSamplesTrait for Ptr<GPCTrainingSamples>

fn as_raw_mut_GPCTrainingSamples(&mut self) -> *mut c_void

impl GPCTrainingSamplesTraitConst for Ptr<GPCTrainingSamples>

fn as_raw_GPCTrainingSamples(&self) -> *const c_void

fn size(&self) -> Result<size_t>

fn typ(&self) -> Result<i32>

impl GPCTreeTrait for Ptr<GPCTree>

fn as_raw_mut_GPCTree(&mut self) -> *mut c_void

fn train( &mut self, samples: &mut impl GPCTrainingSamplesTrait, params: GPCTrainingParams ) -> Result<()>

C++ default parameters

fn train_def( &mut self, samples: &mut impl GPCTrainingSamplesTrait ) -> Result<()>

Note

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

impl GPCTreeTraitConst for Ptr<GPCTree>

fn as_raw_GPCTree(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

fn find_leaf_for_patch( &self, descr: &impl GPCPatchDescriptorTraitConst ) -> Result<u32>

fn equals(&self, t: &impl GPCTreeTraitConst) -> Result<bool>

fn get_descriptor_type(&self) -> Result<i32>

impl GRULayerTrait for Ptr<GRULayer>

fn as_raw_mut_GRULayer(&mut self) -> *mut c_void

impl GRULayerTraitConst for Ptr<GRULayer>

fn as_raw_GRULayer(&self) -> *const c_void

impl GatherElementsLayerTrait for Ptr<GatherElementsLayer>

fn as_raw_mut_GatherElementsLayer(&mut self) -> *mut c_void

impl GatherElementsLayerTraitConst for Ptr<GatherElementsLayer>

fn as_raw_GatherElementsLayer(&self) -> *const c_void

impl GatherLayerTrait for Ptr<GatherLayer>

fn as_raw_mut_GatherLayer(&mut self) -> *mut c_void

impl GatherLayerTraitConst for Ptr<GatherLayer>

fn as_raw_GatherLayer(&self) -> *const c_void

impl GaussianMotionFilterTrait for Ptr<GaussianMotionFilter>

fn as_raw_mut_GaussianMotionFilter(&mut self) -> *mut c_void

fn set_params(&mut self, radius: i32, stdev: f32) -> Result<()>

C++ default parameters

fn set_params_def(&mut self, radius: i32) -> Result<()>

Note

fn stabilize( &mut self, idx: i32, motions: &Vector<Mat>, range: &impl RangeTraitConst ) -> Result<Mat>

impl GaussianMotionFilterTraitConst for Ptr<GaussianMotionFilter>

fn as_raw_GaussianMotionFilter(&self) -> *const c_void

fn radius(&self) -> Result<i32>

fn stdev(&self) -> Result<f32>

impl GeluApproximationLayerTrait for Ptr<GeluApproximationLayer>

fn as_raw_mut_GeluApproximationLayer(&mut self) -> *mut c_void

impl GeluApproximationLayerTraitConst for Ptr<GeluApproximationLayer>

fn as_raw_GeluApproximationLayer(&self) -> *const c_void

impl GeluLayerTrait for Ptr<GeluLayer>

fn as_raw_mut_GeluLayer(&mut self) -> *mut c_void

impl GeluLayerTraitConst for Ptr<GeluLayer>

fn as_raw_GeluLayer(&self) -> *const c_void

impl GemmLayerTrait for Ptr<GemmLayer>

fn as_raw_mut_GemmLayer(&mut self) -> *mut c_void

fn set_trans_a(&mut self, val: bool)

fn set_trans_b(&mut self, val: bool)

fn set_alpha(&mut self, val: f32)

fn set_beta(&mut self, val: f32)

impl GemmLayerTraitConst for Ptr<GemmLayer>

fn as_raw_GemmLayer(&self) -> *const c_void

fn trans_a(&self) -> bool

fn trans_b(&self) -> bool

fn alpha(&self) -> f32

fn beta(&self) -> f32

impl GeneralizedHoughBallardTrait for Ptr<GeneralizedHoughBallard>

fn as_raw_mut_GeneralizedHoughBallard(&mut self) -> *mut c_void

fn set_levels(&mut self, levels: i32) -> Result<()>

R-Table levels.

fn set_votes_threshold(&mut self, votes_threshold: i32) -> Result<()>

The accumulator threshold for the template centers at the detection stage. The smaller it is, the more false positions may be detected.

impl GeneralizedHoughBallardTraitConst for Ptr<GeneralizedHoughBallard>

fn as_raw_GeneralizedHoughBallard(&self) -> *const c_void

fn get_levels(&self) -> Result<i32>

fn get_votes_threshold(&self) -> Result<i32>

impl GeneralizedHoughGuilTrait for Ptr<GeneralizedHoughGuil>

fn as_raw_mut_GeneralizedHoughGuil(&mut self) -> *mut c_void

fn set_xi(&mut self, xi: f64) -> Result<()>

Angle difference in degrees between two points in feature.

fn set_levels(&mut self, levels: i32) -> Result<()>

Feature table levels.

fn set_angle_epsilon(&mut self, angle_epsilon: f64) -> Result<()>

Maximal difference between angles that treated as equal.

fn set_min_angle(&mut self, min_angle: f64) -> Result<()>

Minimal rotation angle to detect in degrees.

fn set_max_angle(&mut self, max_angle: f64) -> Result<()>

Maximal rotation angle to detect in degrees.

fn set_angle_step(&mut self, angle_step: f64) -> Result<()>

Angle step in degrees.

fn set_angle_thresh(&mut self, angle_thresh: i32) -> Result<()>

Angle votes threshold.

fn set_min_scale(&mut self, min_scale: f64) -> Result<()>

Minimal scale to detect.

fn set_max_scale(&mut self, max_scale: f64) -> Result<()>

Maximal scale to detect.

fn set_scale_step(&mut self, scale_step: f64) -> Result<()>

Scale step.

fn set_scale_thresh(&mut self, scale_thresh: i32) -> Result<()>

Scale votes threshold.

fn set_pos_thresh(&mut self, pos_thresh: i32) -> Result<()>

Position votes threshold.

impl GeneralizedHoughGuilTraitConst for Ptr<GeneralizedHoughGuil>

fn as_raw_GeneralizedHoughGuil(&self) -> *const c_void

fn get_xi(&self) -> Result<f64>

fn get_levels(&self) -> Result<i32>

fn get_angle_epsilon(&self) -> Result<f64>

fn get_min_angle(&self) -> Result<f64>

fn get_max_angle(&self) -> Result<f64>

fn get_angle_step(&self) -> Result<f64>

fn get_angle_thresh(&self) -> Result<i32>

fn get_min_scale(&self) -> Result<f64>

fn get_max_scale(&self) -> Result<f64>

fn get_scale_step(&self) -> Result<f64>

fn get_scale_thresh(&self) -> Result<i32>

fn get_pos_thresh(&self) -> Result<i32>

impl GeneralizedHoughTrait for Ptr<GeneralizedHough>

fn as_raw_mut_GeneralizedHough(&mut self) -> *mut c_void

fn set_template( &mut self, templ: &impl ToInputArray, templ_center: Point ) -> Result<()>

set template to search

fn set_template_def(&mut self, templ: &impl ToInputArray) -> Result<()>

set template to search

fn set_template_1( &mut self, edges: &impl ToInputArray, dx: &impl ToInputArray, dy: &impl ToInputArray, templ_center: Point ) -> Result<()>

C++ default parameters

fn set_template_def_1( &mut self, edges: &impl ToInputArray, dx: &impl ToInputArray, dy: &impl ToInputArray ) -> Result<()>

Note

fn detect( &mut self, image: &impl ToInputArray, positions: &mut impl ToOutputArray, votes: &mut impl ToOutputArray ) -> Result<()>

find template on image

fn detect_def( &mut self, image: &impl ToInputArray, positions: &mut impl ToOutputArray ) -> Result<()>

find template on image

fn detect_with_edges( &mut self, edges: &impl ToInputArray, dx: &impl ToInputArray, dy: &impl ToInputArray, positions: &mut impl ToOutputArray, votes: &mut impl ToOutputArray ) -> Result<()>

C++ default parameters

fn detect_with_edges_def( &mut self, edges: &impl ToInputArray, dx: &impl ToInputArray, dy: &impl ToInputArray, positions: &mut impl ToOutputArray ) -> Result<()>

Note

fn set_canny_low_thresh(&mut self, canny_low_thresh: i32) -> Result<()>

Canny low threshold.

fn set_canny_high_thresh(&mut self, canny_high_thresh: i32) -> Result<()>

Canny high threshold.

fn set_min_dist(&mut self, min_dist: f64) -> Result<()>

Minimum distance between the centers of the detected objects.

fn set_dp(&mut self, dp: f64) -> Result<()>

Inverse ratio of the accumulator resolution to the image resolution.

fn set_max_buffer_size(&mut self, max_buffer_size: i32) -> Result<()>

Maximal size of inner buffers.

impl GeneralizedHoughTrait for Ptr<GeneralizedHoughBallard>

fn as_raw_mut_GeneralizedHough(&mut self) -> *mut c_void

fn set_template( &mut self, templ: &impl ToInputArray, templ_center: Point ) -> Result<()>

set template to search

fn set_template_def(&mut self, templ: &impl ToInputArray) -> Result<()>

set template to search

fn set_template_1( &mut self, edges: &impl ToInputArray, dx: &impl ToInputArray, dy: &impl ToInputArray, templ_center: Point ) -> Result<()>

C++ default parameters

fn set_template_def_1( &mut self, edges: &impl ToInputArray, dx: &impl ToInputArray, dy: &impl ToInputArray ) -> Result<()>

Note

fn detect( &mut self, image: &impl ToInputArray, positions: &mut impl ToOutputArray, votes: &mut impl ToOutputArray ) -> Result<()>

find template on image

fn detect_def( &mut self, image: &impl ToInputArray, positions: &mut impl ToOutputArray ) -> Result<()>

find template on image

fn detect_with_edges( &mut self, edges: &impl ToInputArray, dx: &impl ToInputArray, dy: &impl ToInputArray, positions: &mut impl ToOutputArray, votes: &mut impl ToOutputArray ) -> Result<()>

C++ default parameters

fn detect_with_edges_def( &mut self, edges: &impl ToInputArray, dx: &impl ToInputArray, dy: &impl ToInputArray, positions: &mut impl ToOutputArray ) -> Result<()>

Note

fn set_canny_low_thresh(&mut self, canny_low_thresh: i32) -> Result<()>

Canny low threshold.

fn set_canny_high_thresh(&mut self, canny_high_thresh: i32) -> Result<()>

Canny high threshold.

fn set_min_dist(&mut self, min_dist: f64) -> Result<()>

Minimum distance between the centers of the detected objects.

fn set_dp(&mut self, dp: f64) -> Result<()>

Inverse ratio of the accumulator resolution to the image resolution.

fn set_max_buffer_size(&mut self, max_buffer_size: i32) -> Result<()>

Maximal size of inner buffers.

impl GeneralizedHoughTrait for Ptr<GeneralizedHoughGuil>

fn as_raw_mut_GeneralizedHough(&mut self) -> *mut c_void

fn set_template( &mut self, templ: &impl ToInputArray, templ_center: Point ) -> Result<()>

set template to search

fn set_template_def(&mut self, templ: &impl ToInputArray) -> Result<()>

set template to search

fn set_template_1( &mut self, edges: &impl ToInputArray, dx: &impl ToInputArray, dy: &impl ToInputArray, templ_center: Point ) -> Result<()>

C++ default parameters

fn set_template_def_1( &mut self, edges: &impl ToInputArray, dx: &impl ToInputArray, dy: &impl ToInputArray ) -> Result<()>

Note

fn detect( &mut self, image: &impl ToInputArray, positions: &mut impl ToOutputArray, votes: &mut impl ToOutputArray ) -> Result<()>

find template on image

fn detect_def( &mut self, image: &impl ToInputArray, positions: &mut impl ToOutputArray ) -> Result<()>

find template on image

fn detect_with_edges( &mut self, edges: &impl ToInputArray, dx: &impl ToInputArray, dy: &impl ToInputArray, positions: &mut impl ToOutputArray, votes: &mut impl ToOutputArray ) -> Result<()>

C++ default parameters

fn detect_with_edges_def( &mut self, edges: &impl ToInputArray, dx: &impl ToInputArray, dy: &impl ToInputArray, positions: &mut impl ToOutputArray ) -> Result<()>

Note

fn set_canny_low_thresh(&mut self, canny_low_thresh: i32) -> Result<()>

Canny low threshold.

fn set_canny_high_thresh(&mut self, canny_high_thresh: i32) -> Result<()>

Canny high threshold.

fn set_min_dist(&mut self, min_dist: f64) -> Result<()>

Minimum distance between the centers of the detected objects.

fn set_dp(&mut self, dp: f64) -> Result<()>

Inverse ratio of the accumulator resolution to the image resolution.

fn set_max_buffer_size(&mut self, max_buffer_size: i32) -> Result<()>

Maximal size of inner buffers.

impl GeneralizedHoughTraitConst for Ptr<GeneralizedHough>

fn as_raw_GeneralizedHough(&self) -> *const c_void

fn get_canny_low_thresh(&self) -> Result<i32>

fn get_canny_high_thresh(&self) -> Result<i32>

fn get_min_dist(&self) -> Result<f64>

fn get_dp(&self) -> Result<f64>

fn get_max_buffer_size(&self) -> Result<i32>

impl GeneralizedHoughTraitConst for Ptr<GeneralizedHoughBallard>

fn as_raw_GeneralizedHough(&self) -> *const c_void

fn get_canny_low_thresh(&self) -> Result<i32>

fn get_canny_high_thresh(&self) -> Result<i32>

fn get_min_dist(&self) -> Result<f64>

fn get_dp(&self) -> Result<f64>

fn get_max_buffer_size(&self) -> Result<i32>

impl GeneralizedHoughTraitConst for Ptr<GeneralizedHoughGuil>

fn as_raw_GeneralizedHough(&self) -> *const c_void

fn get_canny_low_thresh(&self) -> Result<i32>

fn get_canny_high_thresh(&self) -> Result<i32>

fn get_min_dist(&self) -> Result<f64>

fn get_dp(&self) -> Result<f64>

fn get_max_buffer_size(&self) -> Result<i32>

impl GpuMat_AllocatorTrait for Ptr<GpuMat_Allocator>

fn as_raw_mut_GpuMat_Allocator(&mut self) -> *mut c_void

fn allocate( &mut self, mat: &mut impl GpuMatTrait, rows: i32, cols: i32, elem_size: size_t ) -> Result<bool>

fn free(&mut self, mat: &mut impl GpuMatTrait) -> Result<()>

impl GpuMat_AllocatorTraitConst for Ptr<GpuMat_Allocator>

fn as_raw_GpuMat_Allocator(&self) -> *const c_void

impl GraphSegmentationTrait for Ptr<GraphSegmentation>

fn as_raw_mut_GraphSegmentation(&mut self) -> *mut c_void

fn process_image( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Segment an image and store output in dst

fn set_sigma(&mut self, sigma: f64) -> Result<()>

fn get_sigma(&mut self) -> Result<f64>

fn set_k(&mut self, k: f32) -> Result<()>

fn get_k(&mut self) -> Result<f32>

fn set_min_size(&mut self, min_size: i32) -> Result<()>

fn get_min_size(&mut self) -> Result<i32>

impl GraphSegmentationTraitConst for Ptr<GraphSegmentation>

fn as_raw_GraphSegmentation(&self) -> *const c_void

impl GrayCodePatternTrait for Ptr<GrayCodePattern>

fn as_raw_mut_GrayCodePattern(&mut self) -> *mut c_void

fn set_white_threshold(&mut self, value: size_t) -> Result<()>

Sets the value for white threshold, needed for decoding.

fn set_black_threshold(&mut self, value: size_t) -> Result<()>

Sets the value for black threshold, needed for decoding (shadowsmasks computation).

impl GrayCodePatternTraitConst for Ptr<GrayCodePattern>

fn as_raw_GrayCodePattern(&self) -> *const c_void

fn get_number_of_pattern_images(&self) -> Result<size_t>

Get the number of pattern images needed for the graycode pattern.

fn get_images_for_shadow_masks( &self, black_image: &mut impl ToInputOutputArray, white_image: &mut impl ToInputOutputArray ) -> Result<()>

Generates the all-black and all-white images needed for shadowMasks computation.

fn get_proj_pixel( &self, pattern_images: &impl ToInputArray, x: i32, y: i32, proj_pix: &mut Point ) -> Result<bool>

For a (x,y) pixel of a camera returns the corresponding projector pixel.

impl GrayworldWBTrait for Ptr<GrayworldWB>

fn as_raw_mut_GrayworldWB(&mut self) -> *mut c_void

fn set_saturation_threshold(&mut self, val: f32) -> Result<()>

Maximum saturation for a pixel to be included in the gray-world assumption

impl GrayworldWBTraitConst for Ptr<GrayworldWB>

fn as_raw_GrayworldWB(&self) -> *const c_void

fn get_saturation_threshold(&self) -> Result<f32>

Maximum saturation for a pixel to be included in the gray-world assumption

impl GridBoardTrait for Ptr<GridBoard>

fn as_raw_mut_GridBoard(&mut self) -> *mut c_void

impl GridBoardTraitConst for Ptr<GridBoard>

fn as_raw_GridBoard(&self) -> *const c_void

fn get_grid_size(&self) -> Result<Size>

fn get_marker_length(&self) -> Result<f32>

fn get_marker_separation(&self) -> Result<f32>

impl GuidedFilterTrait for Ptr<GuidedFilter>

fn as_raw_mut_GuidedFilter(&mut self) -> *mut c_void

fn filter( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, d_depth: i32 ) -> Result<()>

Apply Guided Filter to the filtering image.

fn filter_def( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Apply Guided Filter to the filtering image.

impl GuidedFilterTraitConst for Ptr<GuidedFilter>

fn as_raw_GuidedFilter(&self) -> *const c_void

impl HDF5Trait for Ptr<HDF5>

fn as_raw_mut_HDF5(&mut self) -> *mut c_void

fn close(&mut self) -> Result<()>

Close and release hdf5 object.

fn grcreate(&mut self, grlabel: &str) -> Result<()>

Create a group.

fn atdelete(&mut self, atlabel: &str) -> Result<()>

Delete an attribute from the root group.

fn atwrite_i32(&mut self, value: i32, atlabel: &str) -> Result<()>

Write an attribute inside the root group.

fn atread_i32(&mut self, value: &mut i32, atlabel: &str) -> Result<()>

Read an attribute from the root group.

fn atwrite_f64(&mut self, value: f64, atlabel: &str) -> Result<()>

Write an attribute inside the root group.

fn atread_f64(&mut self, value: &mut f64, atlabel: &str) -> Result<()>

Read an attribute from the root group.

fn atwrite_str(&mut self, value: &str, atlabel: &str) -> Result<()>

Write an attribute inside the root group.

fn atread_str(&mut self, value: &mut String, atlabel: &str) -> Result<()>

Read an attribute from the root group.

fn atwrite(&mut self, value: &impl ToInputArray, atlabel: &str) -> Result<()>

Write an attribute into the root group.

fn atread( &mut self, value: &mut impl ToOutputArray, atlabel: &str ) -> Result<()>

Read an attribute from the root group.

impl HDF5TraitConst for Ptr<HDF5>

fn as_raw_HDF5(&self) -> *const c_void

fn hlexists(&self, label: &str) -> Result<bool>

Check if label exists or not.

fn atexists(&self, atlabel: &str) -> Result<bool>

Check whether a given attribute exits or not in the root group.

fn dscreate(&self, rows: i32, cols: i32, typ: i32, dslabel: &str) -> Result<()>

Create and allocate storage for two dimensional single or multi channel dataset.

fn dscreate_compress( &self, rows: i32, cols: i32, typ: i32, dslabel: &str, compresslevel: i32 ) -> Result<()>

Create and allocate storage for two dimensional single or multi channel dataset.

fn dscreate_compress_dims( &self, rows: i32, cols: i32, typ: i32, dslabel: &str, compresslevel: i32, dims_chunks: &Vector<i32> ) -> Result<()>

Create and allocate storage for two dimensional single or multi channel dataset.

fn dscreate_nd(&self, sizes: &[i32], typ: i32, dslabel: &str) -> Result<()>

fn dscreate_nd_compress( &self, sizes: &[i32], typ: i32, dslabel: &str, compresslevel: i32 ) -> Result<()>

fn dscreate_nd_vec_compress_dims( &self, sizes: &Vector<i32>, typ: i32, dslabel: &str, compresslevel: i32, dims_chunks: &Vector<i32> ) -> Result<()>

C++ default parameters

fn dscreate_nd_vec_compress_dims_def( &self, sizes: &Vector<i32>, typ: i32, dslabel: &str ) -> Result<()>

Note

fn dscreate_nd_compress_dims( &self, sizes: &[i32], typ: i32, dslabel: &str, compresslevel: i32, dims_chunks: &i32 ) -> Result<()>

Create and allocate storage for n-dimensional dataset, single or multichannel type.

fn dsgetsize(&self, dslabel: &str, dims_flag: i32) -> Result<Vector<i32>>

Fetch dataset sizes

fn dsgetsize_def(&self, dslabel: &str) -> Result<Vector<i32>>

Fetch dataset sizes

fn dsgettype(&self, dslabel: &str) -> Result<i32>

Fetch dataset type

fn dswrite(&self, array: &impl ToInputArray, dslabel: &str) -> Result<()>

fn dswrite_offset( &self, array: &impl ToInputArray, dslabel: &str, dims_offset: &Vector<i32>, dims_counts: &Vector<i32> ) -> Result<()>

C++ default parameters

fn dswrite_offset_def( &self, array: &impl ToInputArray, dslabel: &str, dims_offset: &Vector<i32> ) -> Result<()>

Note

fn dsinsert(&self, array: &impl ToInputArray, dslabel: &str) -> Result<()>

fn dsinsert_offset( &self, array: &impl ToInputArray, dslabel: &str, dims_offset: &Vector<i32>, dims_counts: &Vector<i32> ) -> Result<()>

C++ default parameters

fn dsinsert_offset_def( &self, array: &impl ToInputArray, dslabel: &str, dims_offset: &Vector<i32> ) -> Result<()>

Note

fn dsread(&self, array: &mut impl ToOutputArray, dslabel: &str) -> Result<()>

fn dsread_offset( &self, array: &mut impl ToOutputArray, dslabel: &str, dims_offset: &Vector<i32>, dims_counts: &Vector<i32> ) -> Result<()>

C++ default parameters

fn dsread_offset_def( &self, array: &mut impl ToOutputArray, dslabel: &str, dims_offset: &Vector<i32> ) -> Result<()>

Note

fn kpgetsize(&self, kplabel: &str, dims_flag: i32) -> Result<i32>

Fetch keypoint dataset size

fn kpgetsize_def(&self, kplabel: &str) -> Result<i32>

Fetch keypoint dataset size

fn kpcreate( &self, size: i32, kplabel: &str, compresslevel: i32, chunks: i32 ) -> Result<()>

Create and allocate special storage for cv::KeyPoint dataset.

fn kpcreate_def(&self, size: i32, kplabel: &str) -> Result<()>

Create and allocate special storage for cv::KeyPoint dataset.

fn kpwrite( &self, keypoints: Vector<KeyPoint>, kplabel: &str, offset: i32, counts: i32 ) -> Result<()>

Write or overwrite list of KeyPoint into specified dataset of hdf5 file.

fn kpwrite_def(&self, keypoints: Vector<KeyPoint>, kplabel: &str) -> Result<()>

Write or overwrite list of KeyPoint into specified dataset of hdf5 file.

fn kpinsert( &self, keypoints: Vector<KeyPoint>, kplabel: &str, offset: i32, counts: i32 ) -> Result<()>

Insert or overwrite list of KeyPoint into specified dataset and autoexpand dataset size if unlimited property allows.

fn kpinsert_def(&self, keypoints: Vector<KeyPoint>, kplabel: &str) -> Result<()>

Insert or overwrite list of KeyPoint into specified dataset and autoexpand dataset size if unlimited property allows.

fn kpread( &self, keypoints: &mut Vector<KeyPoint>, kplabel: &str, offset: i32, counts: i32 ) -> Result<()>

Read specific keypoint dataset from hdf5 file into vector object.

fn kpread_def( &self, keypoints: &mut Vector<KeyPoint>, kplabel: &str ) -> Result<()>

Read specific keypoint dataset from hdf5 file into vector object.

impl HardSigmoidLayerTrait for Ptr<HardSigmoidLayer>

fn as_raw_mut_HardSigmoidLayer(&mut self) -> *mut c_void

fn set_alpha(&mut self, val: f32)

fn set_beta(&mut self, val: f32)

impl HardSigmoidLayerTraitConst for Ptr<HardSigmoidLayer>

fn as_raw_HardSigmoidLayer(&self) -> *const c_void

fn alpha(&self) -> f32

fn beta(&self) -> f32

impl HardSwishLayerTrait for Ptr<HardSwishLayer>

fn as_raw_mut_HardSwishLayer(&mut self) -> *mut c_void

impl HardSwishLayerTraitConst for Ptr<HardSwishLayer>

fn as_raw_HardSwishLayer(&self) -> *const c_void

impl HarrisLaplaceFeatureDetectorTrait for Ptr<HarrisLaplaceFeatureDetector>

fn as_raw_mut_HarrisLaplaceFeatureDetector(&mut self) -> *mut c_void

fn set_num_octaves(&mut self, num_octaves_: i32) -> Result<()>

fn set_corn_thresh(&mut self, corn_thresh_: f32) -> Result<()>

fn set_dog_thresh(&mut self, dog_thresh_: f32) -> Result<()>

fn set_max_corners(&mut self, max_corners_: i32) -> Result<()>

fn set_num_layers(&mut self, num_layers_: i32) -> Result<()>

impl HarrisLaplaceFeatureDetectorTraitConst for Ptr<HarrisLaplaceFeatureDetector>

fn as_raw_HarrisLaplaceFeatureDetector(&self) -> *const c_void

fn get_num_octaves(&self) -> Result<i32>

fn get_corn_thresh(&self) -> Result<f32>

fn get_dog_thresh(&self) -> Result<f32>

fn get_max_corners(&self) -> Result<i32>

fn get_num_layers(&self) -> Result<i32>

fn get_default_name(&self) -> Result<String>

impl HausdorffDistanceExtractorTrait for Ptr<HausdorffDistanceExtractor>

fn as_raw_mut_HausdorffDistanceExtractor(&mut self) -> *mut c_void

fn set_distance_flag(&mut self, distance_flag: i32) -> Result<()>

Set the norm used to compute the Hausdorff value between two shapes. It can be L1 or L2 norm.

fn set_rank_proportion(&mut self, rank_proportion: f32) -> Result<()>

This method sets the rank proportion (or fractional value) that establish the Kth ranked value of the partial Hausdorff distance. Experimentally had been shown that 0.6 is a good value to compare shapes.

impl HausdorffDistanceExtractorTraitConst for Ptr<HausdorffDistanceExtractor>

fn as_raw_HausdorffDistanceExtractor(&self) -> *const c_void

fn get_distance_flag(&self) -> Result<i32>

fn get_rank_proportion(&self) -> Result<f32>

impl HfsSegmentTrait for Ptr<HfsSegment>

fn as_raw_mut_HfsSegment(&mut self) -> *mut c_void

fn set_seg_egb_threshold_i(&mut self, c: f32) -> Result<()>

set and get the parameter segEgbThresholdI. This parameter is used in the second stage mentioned above. It is a constant used to threshold weights of the edge when merging adjacent nodes when applying EGB algorithm. The segmentation result tends to have more regions remained if this value is large and vice versa.

fn get_seg_egb_threshold_i(&mut self) -> Result<f32>

fn set_min_region_size_i(&mut self, n: i32) -> Result<()>

set and get the parameter minRegionSizeI. This parameter is used in the second stage mentioned above. After the EGB segmentation, regions that have fewer pixels then this parameter will be merged into it’s adjacent region.

fn get_min_region_size_i(&mut self) -> Result<i32>

fn set_seg_egb_threshold_ii(&mut self, c: f32) -> Result<()>

set and get the parameter segEgbThresholdII. This parameter is used in the third stage mentioned above. It serves the same purpose as segEgbThresholdI. The segmentation result tends to have more regions remained if this value is large and vice versa.

fn get_seg_egb_threshold_ii(&mut self) -> Result<f32>

fn set_min_region_size_ii(&mut self, n: i32) -> Result<()>

set and get the parameter minRegionSizeII. This parameter is used in the third stage mentioned above. It serves the same purpose as minRegionSizeI

fn get_min_region_size_ii(&mut self) -> Result<i32>

fn set_spatial_weight(&mut self, w: f32) -> Result<()>

set and get the parameter spatialWeight. This parameter is used in the first stage mentioned above(the SLIC stage). It describes how important is the role of position when calculating the distance between each pixel and it’s center. The exact formula to calculate the distance is inline formula. The segmentation result tends to have more local consistency if this value is larger.

fn get_spatial_weight(&mut self) -> Result<f32>

fn set_slic_spixel_size(&mut self, n: i32) -> Result<()>

set and get the parameter slicSpixelSize. This parameter is used in the first stage mentioned above(the SLIC stage). It describes the size of each superpixel when initializing SLIC. Every superpixel approximately has inline formula pixels in the beginning.

fn get_slic_spixel_size(&mut self) -> Result<i32>

fn set_num_slic_iter(&mut self, n: i32) -> Result<()>

set and get the parameter numSlicIter. This parameter is used in the first stage. It describes how many iteration to perform when executing SLIC.

fn get_num_slic_iter(&mut self) -> Result<i32>

fn perform_segment_gpu( &mut self, src: &impl ToInputArray, if_draw: bool ) -> Result<Mat>

do segmentation gpu

fn perform_segment_gpu_def(&mut self, src: &impl ToInputArray) -> Result<Mat>

do segmentation gpu

fn perform_segment_cpu( &mut self, src: &impl ToInputArray, if_draw: bool ) -> Result<Mat>

do segmentation with cpu This method is only implemented for reference. It is highly NOT recommanded to use it.

fn perform_segment_cpu_def(&mut self, src: &impl ToInputArray) -> Result<Mat>

do segmentation with cpu This method is only implemented for reference. It is highly NOT recommanded to use it.

impl HfsSegmentTraitConst for Ptr<HfsSegment>

fn as_raw_HfsSegment(&self) -> *const c_void

impl HierarchicalClusteringIndexParamsTrait for Ptr<HierarchicalClusteringIndexParams>

fn as_raw_mut_HierarchicalClusteringIndexParams(&mut self) -> *mut c_void

impl HierarchicalClusteringIndexParamsTraitConst for Ptr<HierarchicalClusteringIndexParams>

fn as_raw_HierarchicalClusteringIndexParams(&self) -> *const c_void

impl HistogramCostExtractorTrait for Ptr<ChiHistogramCostExtractor>

fn as_raw_mut_HistogramCostExtractor(&mut self) -> *mut c_void

fn build_cost_matrix( &mut self, descriptors1: &impl ToInputArray, descriptors2: &impl ToInputArray, cost_matrix: &mut impl ToOutputArray ) -> Result<()>

fn set_n_dummies(&mut self, n_dummies: i32) -> Result<()>

fn set_default_cost(&mut self, default_cost: f32) -> Result<()>

impl HistogramCostExtractorTrait for Ptr<EMDHistogramCostExtractor>

fn as_raw_mut_HistogramCostExtractor(&mut self) -> *mut c_void

fn build_cost_matrix( &mut self, descriptors1: &impl ToInputArray, descriptors2: &impl ToInputArray, cost_matrix: &mut impl ToOutputArray ) -> Result<()>

fn set_n_dummies(&mut self, n_dummies: i32) -> Result<()>

fn set_default_cost(&mut self, default_cost: f32) -> Result<()>

impl HistogramCostExtractorTrait for Ptr<EMDL1HistogramCostExtractor>

fn as_raw_mut_HistogramCostExtractor(&mut self) -> *mut c_void

fn build_cost_matrix( &mut self, descriptors1: &impl ToInputArray, descriptors2: &impl ToInputArray, cost_matrix: &mut impl ToOutputArray ) -> Result<()>

fn set_n_dummies(&mut self, n_dummies: i32) -> Result<()>

fn set_default_cost(&mut self, default_cost: f32) -> Result<()>

impl HistogramCostExtractorTrait for Ptr<HistogramCostExtractor>

fn as_raw_mut_HistogramCostExtractor(&mut self) -> *mut c_void

fn build_cost_matrix( &mut self, descriptors1: &impl ToInputArray, descriptors2: &impl ToInputArray, cost_matrix: &mut impl ToOutputArray ) -> Result<()>

fn set_n_dummies(&mut self, n_dummies: i32) -> Result<()>

fn set_default_cost(&mut self, default_cost: f32) -> Result<()>

impl HistogramCostExtractorTrait for Ptr<NormHistogramCostExtractor>

fn as_raw_mut_HistogramCostExtractor(&mut self) -> *mut c_void

fn build_cost_matrix( &mut self, descriptors1: &impl ToInputArray, descriptors2: &impl ToInputArray, cost_matrix: &mut impl ToOutputArray ) -> Result<()>

fn set_n_dummies(&mut self, n_dummies: i32) -> Result<()>

fn set_default_cost(&mut self, default_cost: f32) -> Result<()>

impl HistogramCostExtractorTraitConst for Ptr<ChiHistogramCostExtractor>

fn as_raw_HistogramCostExtractor(&self) -> *const c_void

fn get_n_dummies(&self) -> Result<i32>

fn get_default_cost(&self) -> Result<f32>

impl HistogramCostExtractorTraitConst for Ptr<EMDHistogramCostExtractor>

fn as_raw_HistogramCostExtractor(&self) -> *const c_void

fn get_n_dummies(&self) -> Result<i32>

fn get_default_cost(&self) -> Result<f32>

impl HistogramCostExtractorTraitConst for Ptr<EMDL1HistogramCostExtractor>

fn as_raw_HistogramCostExtractor(&self) -> *const c_void

fn get_n_dummies(&self) -> Result<i32>

fn get_default_cost(&self) -> Result<f32>

impl HistogramCostExtractorTraitConst for Ptr<HistogramCostExtractor>

fn as_raw_HistogramCostExtractor(&self) -> *const c_void

fn get_n_dummies(&self) -> Result<i32>

fn get_default_cost(&self) -> Result<f32>

impl HistogramCostExtractorTraitConst for Ptr<NormHistogramCostExtractor>

fn as_raw_HistogramCostExtractor(&self) -> *const c_void

fn get_n_dummies(&self) -> Result<i32>

fn get_default_cost(&self) -> Result<f32>

impl HistogramPhaseUnwrappingTrait for Ptr<HistogramPhaseUnwrapping>

fn as_raw_mut_HistogramPhaseUnwrapping(&mut self) -> *mut c_void

fn get_inverse_reliability_map( &mut self, reliability_map: &mut impl ToOutputArray ) -> Result<()>

Get the reliability map computed from the wrapped phase map.

impl HistogramPhaseUnwrappingTraitConst for Ptr<HistogramPhaseUnwrapping>

fn as_raw_HistogramPhaseUnwrapping(&self) -> *const c_void

impl ICPOdometryTrait for Ptr<ICPOdometry>

fn as_raw_mut_ICPOdometry(&mut self) -> *mut c_void

fn set_camera_matrix(&mut self, val: &impl MatTraitConst) -> Result<()>

fn set_min_depth(&mut self, val: f64) -> Result<()>

fn set_max_depth(&mut self, val: f64) -> Result<()>

fn set_max_depth_diff(&mut self, val: f64) -> Result<()>

fn set_iteration_counts(&mut self, val: &impl MatTraitConst) -> Result<()>

fn set_max_points_part(&mut self, val: f64) -> Result<()>

fn set_transform_type(&mut self, val: i32) -> Result<()>

fn set_max_translation(&mut self, val: f64) -> Result<()>

fn set_max_rotation(&mut self, val: f64) -> Result<()>

impl ICPOdometryTraitConst for Ptr<ICPOdometry>

fn as_raw_ICPOdometry(&self) -> *const c_void

fn prepare_frame_cache( &self, frame: &mut Ptr<OdometryFrame>, cache_type: i32 ) -> Result<Size>

fn get_camera_matrix(&self) -> Result<Mat>

fn get_min_depth(&self) -> Result<f64>

fn get_max_depth(&self) -> Result<f64>

fn get_max_depth_diff(&self) -> Result<f64>

fn get_iteration_counts(&self) -> Result<Mat>

fn get_max_points_part(&self) -> Result<f64>

fn get_transform_type(&self) -> Result<i32>

fn get_max_translation(&self) -> Result<f64>

fn get_max_rotation(&self) -> Result<f64>

fn get_normals_computer(&self) -> Result<Ptr<RgbdNormals>>

impl IDenseOptFlowEstimatorTrait for Ptr<DensePyrLkOptFlowEstimatorGpu>

fn as_raw_mut_IDenseOptFlowEstimator(&mut self) -> *mut c_void

fn run( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, flow_x: &mut impl ToInputOutputArray, flow_y: &mut impl ToInputOutputArray, errors: &mut impl ToOutputArray ) -> Result<()>

impl IDenseOptFlowEstimatorTrait for Ptr<IDenseOptFlowEstimator>

fn as_raw_mut_IDenseOptFlowEstimator(&mut self) -> *mut c_void

fn run( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, flow_x: &mut impl ToInputOutputArray, flow_y: &mut impl ToInputOutputArray, errors: &mut impl ToOutputArray ) -> Result<()>

impl IDenseOptFlowEstimatorTraitConst for Ptr<DensePyrLkOptFlowEstimatorGpu>

fn as_raw_IDenseOptFlowEstimator(&self) -> *const c_void

impl IDenseOptFlowEstimatorTraitConst for Ptr<IDenseOptFlowEstimator>

fn as_raw_IDenseOptFlowEstimator(&self) -> *const c_void

impl IFrameSourceTrait for Ptr<IFrameSource>

fn as_raw_mut_IFrameSource(&mut self) -> *mut c_void

fn reset(&mut self) -> Result<()>

fn next_frame(&mut self) -> Result<Mat>

impl IFrameSourceTrait for Ptr<MaskFrameSource>

fn as_raw_mut_IFrameSource(&mut self) -> *mut c_void

fn reset(&mut self) -> Result<()>

fn next_frame(&mut self) -> Result<Mat>

impl IFrameSourceTrait for Ptr<NullFrameSource>

fn as_raw_mut_IFrameSource(&mut self) -> *mut c_void

fn reset(&mut self) -> Result<()>

fn next_frame(&mut self) -> Result<Mat>

impl IFrameSourceTrait for Ptr<OnePassStabilizer>

fn as_raw_mut_IFrameSource(&mut self) -> *mut c_void

fn reset(&mut self) -> Result<()>

fn next_frame(&mut self) -> Result<Mat>

impl IFrameSourceTrait for Ptr<TwoPassStabilizer>

fn as_raw_mut_IFrameSource(&mut self) -> *mut c_void

fn reset(&mut self) -> Result<()>

fn next_frame(&mut self) -> Result<Mat>

impl IFrameSourceTrait for Ptr<VideoFileSource>

fn as_raw_mut_IFrameSource(&mut self) -> *mut c_void

fn reset(&mut self) -> Result<()>

fn next_frame(&mut self) -> Result<Mat>

impl IFrameSourceTraitConst for Ptr<IFrameSource>

fn as_raw_IFrameSource(&self) -> *const c_void

impl IFrameSourceTraitConst for Ptr<MaskFrameSource>

fn as_raw_IFrameSource(&self) -> *const c_void

impl IFrameSourceTraitConst for Ptr<NullFrameSource>

fn as_raw_IFrameSource(&self) -> *const c_void

impl IFrameSourceTraitConst for Ptr<OnePassStabilizer>

fn as_raw_IFrameSource(&self) -> *const c_void

impl IFrameSourceTraitConst for Ptr<TwoPassStabilizer>

fn as_raw_IFrameSource(&self) -> *const c_void

impl IFrameSourceTraitConst for Ptr<VideoFileSource>

fn as_raw_IFrameSource(&self) -> *const c_void

impl ILogTrait for Ptr<ILog>

fn as_raw_mut_ILog(&mut self) -> *mut c_void

fn print(&mut self, format: &str) -> Result<()>

impl ILogTrait for Ptr<LogToStdout>

fn as_raw_mut_ILog(&mut self) -> *mut c_void

fn print(&mut self, format: &str) -> Result<()>

impl ILogTrait for Ptr<NullLog>

fn as_raw_mut_ILog(&mut self) -> *mut c_void

fn print(&mut self, format: &str) -> Result<()>

impl ILogTraitConst for Ptr<ILog>

fn as_raw_ILog(&self) -> *const c_void

impl ILogTraitConst for Ptr<LogToStdout>

fn as_raw_ILog(&self) -> *const c_void

impl ILogTraitConst for Ptr<NullLog>

fn as_raw_ILog(&self) -> *const c_void

impl IMotionStabilizerTrait for Ptr<GaussianMotionFilter>

fn as_raw_mut_IMotionStabilizer(&mut self) -> *mut c_void

fn stabilize( &mut self, size: i32, motions: &Vector<Mat>, range: &impl RangeTraitConst, stabilization_motions: &mut impl MatTrait ) -> Result<()>

assumes that [0, size-1) is in or equals to [range.first, range.second)

impl IMotionStabilizerTrait for Ptr<IMotionStabilizer>

fn as_raw_mut_IMotionStabilizer(&mut self) -> *mut c_void

fn stabilize( &mut self, size: i32, motions: &Vector<Mat>, range: &impl RangeTraitConst, stabilization_motions: &mut impl MatTrait ) -> Result<()>

assumes that [0, size-1) is in or equals to [range.first, range.second)

impl IMotionStabilizerTrait for Ptr<LpMotionStabilizer>

fn as_raw_mut_IMotionStabilizer(&mut self) -> *mut c_void

fn stabilize( &mut self, size: i32, motions: &Vector<Mat>, range: &impl RangeTraitConst, stabilization_motions: &mut impl MatTrait ) -> Result<()>

assumes that [0, size-1) is in or equals to [range.first, range.second)

impl IMotionStabilizerTrait for Ptr<MotionFilterBase>

fn as_raw_mut_IMotionStabilizer(&mut self) -> *mut c_void

fn stabilize( &mut self, size: i32, motions: &Vector<Mat>, range: &impl RangeTraitConst, stabilization_motions: &mut impl MatTrait ) -> Result<()>

assumes that [0, size-1) is in or equals to [range.first, range.second)

impl IMotionStabilizerTrait for Ptr<MotionStabilizationPipeline>

fn as_raw_mut_IMotionStabilizer(&mut self) -> *mut c_void

fn stabilize( &mut self, size: i32, motions: &Vector<Mat>, range: &impl RangeTraitConst, stabilization_motions: &mut impl MatTrait ) -> Result<()>

assumes that [0, size-1) is in or equals to [range.first, range.second)

impl IMotionStabilizerTraitConst for Ptr<GaussianMotionFilter>

fn as_raw_IMotionStabilizer(&self) -> *const c_void

impl IMotionStabilizerTraitConst for Ptr<IMotionStabilizer>

fn as_raw_IMotionStabilizer(&self) -> *const c_void

impl IMotionStabilizerTraitConst for Ptr<LpMotionStabilizer>

fn as_raw_IMotionStabilizer(&self) -> *const c_void

impl IMotionStabilizerTraitConst for Ptr<MotionFilterBase>

fn as_raw_IMotionStabilizer(&self) -> *const c_void

impl IMotionStabilizerTraitConst for Ptr<MotionStabilizationPipeline>

fn as_raw_IMotionStabilizer(&self) -> *const c_void

impl IOutlierRejectorTrait for Ptr<IOutlierRejector>

fn as_raw_mut_IOutlierRejector(&mut self) -> *mut c_void

fn process( &mut self, frame_size: Size, points0: &impl ToInputArray, points1: &impl ToInputArray, mask: &mut impl ToOutputArray ) -> Result<()>

impl IOutlierRejectorTrait for Ptr<NullOutlierRejector>

fn as_raw_mut_IOutlierRejector(&mut self) -> *mut c_void

fn process( &mut self, frame_size: Size, points0: &impl ToInputArray, points1: &impl ToInputArray, mask: &mut impl ToOutputArray ) -> Result<()>

impl IOutlierRejectorTrait for Ptr<TranslationBasedLocalOutlierRejector>

fn as_raw_mut_IOutlierRejector(&mut self) -> *mut c_void

fn process( &mut self, frame_size: Size, points0: &impl ToInputArray, points1: &impl ToInputArray, mask: &mut impl ToOutputArray ) -> Result<()>

impl IOutlierRejectorTraitConst for Ptr<IOutlierRejector>

fn as_raw_IOutlierRejector(&self) -> *const c_void

impl IOutlierRejectorTraitConst for Ptr<NullOutlierRejector>

fn as_raw_IOutlierRejector(&self) -> *const c_void

impl IOutlierRejectorTraitConst for Ptr<TranslationBasedLocalOutlierRejector>

fn as_raw_IOutlierRejector(&self) -> *const c_void

impl ISparseOptFlowEstimatorTrait for Ptr<ISparseOptFlowEstimator>

fn as_raw_mut_ISparseOptFlowEstimator(&mut self) -> *mut c_void

fn run( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, points0: &impl ToInputArray, points1: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray, errors: &mut impl ToOutputArray ) -> Result<()>

impl ISparseOptFlowEstimatorTrait for Ptr<SparsePyrLkOptFlowEstimator>

fn as_raw_mut_ISparseOptFlowEstimator(&mut self) -> *mut c_void

fn run( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, points0: &impl ToInputArray, points1: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray, errors: &mut impl ToOutputArray ) -> Result<()>

impl ISparseOptFlowEstimatorTrait for Ptr<SparsePyrLkOptFlowEstimatorGpu>

fn as_raw_mut_ISparseOptFlowEstimator(&mut self) -> *mut c_void

fn run( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, points0: &impl ToInputArray, points1: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray, errors: &mut impl ToOutputArray ) -> Result<()>

impl ISparseOptFlowEstimatorTraitConst for Ptr<ISparseOptFlowEstimator>

fn as_raw_ISparseOptFlowEstimator(&self) -> *const c_void

impl ISparseOptFlowEstimatorTraitConst for Ptr<SparsePyrLkOptFlowEstimator>

fn as_raw_ISparseOptFlowEstimator(&self) -> *const c_void

impl ISparseOptFlowEstimatorTraitConst for Ptr<SparsePyrLkOptFlowEstimatorGpu>

fn as_raw_ISparseOptFlowEstimator(&self) -> *const c_void

impl ImageMotionEstimatorBaseTrait for Ptr<FromFileMotionReader>

fn as_raw_mut_ImageMotionEstimatorBase(&mut self) -> *mut c_void

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn set_frame_mask(&mut self, mask: &impl ToInputArray) -> Result<()>

fn estimate( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst, ok: &mut bool ) -> Result<Mat>

C++ default parameters

fn estimate_def( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst ) -> Result<Mat>

Note

impl ImageMotionEstimatorBaseTrait for Ptr<ImageMotionEstimatorBase>

fn as_raw_mut_ImageMotionEstimatorBase(&mut self) -> *mut c_void

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn set_frame_mask(&mut self, mask: &impl ToInputArray) -> Result<()>

fn estimate( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst, ok: &mut bool ) -> Result<Mat>

C++ default parameters

fn estimate_def( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst ) -> Result<Mat>

Note

impl ImageMotionEstimatorBaseTrait for Ptr<KeypointBasedMotionEstimator>

fn as_raw_mut_ImageMotionEstimatorBase(&mut self) -> *mut c_void

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn set_frame_mask(&mut self, mask: &impl ToInputArray) -> Result<()>

fn estimate( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst, ok: &mut bool ) -> Result<Mat>

C++ default parameters

fn estimate_def( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst ) -> Result<Mat>

Note

impl ImageMotionEstimatorBaseTrait for Ptr<KeypointBasedMotionEstimatorGpu>

fn as_raw_mut_ImageMotionEstimatorBase(&mut self) -> *mut c_void

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn set_frame_mask(&mut self, mask: &impl ToInputArray) -> Result<()>

fn estimate( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst, ok: &mut bool ) -> Result<Mat>

C++ default parameters

fn estimate_def( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst ) -> Result<Mat>

Note

impl ImageMotionEstimatorBaseTrait for Ptr<ToFileMotionWriter>

fn as_raw_mut_ImageMotionEstimatorBase(&mut self) -> *mut c_void

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn set_frame_mask(&mut self, mask: &impl ToInputArray) -> Result<()>

fn estimate( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst, ok: &mut bool ) -> Result<Mat>

C++ default parameters

fn estimate_def( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst ) -> Result<Mat>

Note

impl ImageMotionEstimatorBaseTraitConst for Ptr<FromFileMotionReader>

fn as_raw_ImageMotionEstimatorBase(&self) -> *const c_void

fn motion_model(&self) -> Result<MotionModel>

impl ImageMotionEstimatorBaseTraitConst for Ptr<ImageMotionEstimatorBase>

fn as_raw_ImageMotionEstimatorBase(&self) -> *const c_void

fn motion_model(&self) -> Result<MotionModel>

impl ImageMotionEstimatorBaseTraitConst for Ptr<KeypointBasedMotionEstimator>

fn as_raw_ImageMotionEstimatorBase(&self) -> *const c_void

fn motion_model(&self) -> Result<MotionModel>

impl ImageMotionEstimatorBaseTraitConst for Ptr<KeypointBasedMotionEstimatorGpu>

fn as_raw_ImageMotionEstimatorBase(&self) -> *const c_void

fn motion_model(&self) -> Result<MotionModel>

impl ImageMotionEstimatorBaseTraitConst for Ptr<ToFileMotionWriter>

fn as_raw_ImageMotionEstimatorBase(&self) -> *const c_void

fn motion_model(&self) -> Result<MotionModel>

impl ImgHashBaseTrait for Ptr<AverageHash>

fn as_raw_mut_ImgHashBase(&mut self) -> *mut c_void

fn compute( &mut self, input_arr: &impl ToInputArray, output_arr: &mut impl ToOutputArray ) -> Result<()>

Computes hash of the input image

impl ImgHashBaseTrait for Ptr<BlockMeanHash>

fn as_raw_mut_ImgHashBase(&mut self) -> *mut c_void

fn compute( &mut self, input_arr: &impl ToInputArray, output_arr: &mut impl ToOutputArray ) -> Result<()>

Computes hash of the input image

impl ImgHashBaseTrait for Ptr<ColorMomentHash>

fn as_raw_mut_ImgHashBase(&mut self) -> *mut c_void

fn compute( &mut self, input_arr: &impl ToInputArray, output_arr: &mut impl ToOutputArray ) -> Result<()>

Computes hash of the input image

impl ImgHashBaseTrait for Ptr<ImgHashBase>

fn as_raw_mut_ImgHashBase(&mut self) -> *mut c_void

fn compute( &mut self, input_arr: &impl ToInputArray, output_arr: &mut impl ToOutputArray ) -> Result<()>

Computes hash of the input image

impl ImgHashBaseTrait for Ptr<MarrHildrethHash>

fn as_raw_mut_ImgHashBase(&mut self) -> *mut c_void

fn compute( &mut self, input_arr: &impl ToInputArray, output_arr: &mut impl ToOutputArray ) -> Result<()>

Computes hash of the input image

impl ImgHashBaseTrait for Ptr<PHash>

fn as_raw_mut_ImgHashBase(&mut self) -> *mut c_void

fn compute( &mut self, input_arr: &impl ToInputArray, output_arr: &mut impl ToOutputArray ) -> Result<()>

Computes hash of the input image

impl ImgHashBaseTrait for Ptr<RadialVarianceHash>

fn as_raw_mut_ImgHashBase(&mut self) -> *mut c_void

fn compute( &mut self, input_arr: &impl ToInputArray, output_arr: &mut impl ToOutputArray ) -> Result<()>

Computes hash of the input image

impl ImgHashBaseTraitConst for Ptr<AverageHash>

fn as_raw_ImgHashBase(&self) -> *const c_void

fn compare( &self, hash_one: &impl ToInputArray, hash_two: &impl ToInputArray ) -> Result<f64>

Compare the hash value between inOne and inTwo

impl ImgHashBaseTraitConst for Ptr<BlockMeanHash>

fn as_raw_ImgHashBase(&self) -> *const c_void

fn compare( &self, hash_one: &impl ToInputArray, hash_two: &impl ToInputArray ) -> Result<f64>

Compare the hash value between inOne and inTwo

impl ImgHashBaseTraitConst for Ptr<ColorMomentHash>

fn as_raw_ImgHashBase(&self) -> *const c_void

fn compare( &self, hash_one: &impl ToInputArray, hash_two: &impl ToInputArray ) -> Result<f64>

Compare the hash value between inOne and inTwo

impl ImgHashBaseTraitConst for Ptr<ImgHashBase>

fn as_raw_ImgHashBase(&self) -> *const c_void

fn compare( &self, hash_one: &impl ToInputArray, hash_two: &impl ToInputArray ) -> Result<f64>

Compare the hash value between inOne and inTwo

impl ImgHashBaseTraitConst for Ptr<MarrHildrethHash>

fn as_raw_ImgHashBase(&self) -> *const c_void

fn compare( &self, hash_one: &impl ToInputArray, hash_two: &impl ToInputArray ) -> Result<f64>

Compare the hash value between inOne and inTwo

impl ImgHashBaseTraitConst for Ptr<PHash>

fn as_raw_ImgHashBase(&self) -> *const c_void

fn compare( &self, hash_one: &impl ToInputArray, hash_two: &impl ToInputArray ) -> Result<f64>

Compare the hash value between inOne and inTwo

impl ImgHashBaseTraitConst for Ptr<RadialVarianceHash>

fn as_raw_ImgHashBase(&self) -> *const c_void

fn compare( &self, hash_one: &impl ToInputArray, hash_two: &impl ToInputArray ) -> Result<f64>

Compare the hash value between inOne and inTwo

impl IndexParamsTrait for Ptr<AutotunedIndexParams>

fn as_raw_mut_IndexParams(&mut self) -> *mut c_void

fn params(&mut self) -> *mut c_void

unsafe fn set_params(&mut self, val: *const c_void)

fn set_string(&mut self, key: &str, value: &str) -> Result<()>

fn set_int(&mut self, key: &str, value: i32) -> Result<()>

fn set_double(&mut self, key: &str, value: f64) -> Result<()>

fn set_float(&mut self, key: &str, value: f32) -> Result<()>

fn set_bool(&mut self, key: &str, value: bool) -> Result<()>

fn set_algorithm(&mut self, value: i32) -> Result<()>

impl IndexParamsTrait for Ptr<CompositeIndexParams>

fn as_raw_mut_IndexParams(&mut self) -> *mut c_void

fn params(&mut self) -> *mut c_void

unsafe fn set_params(&mut self, val: *const c_void)

fn set_string(&mut self, key: &str, value: &str) -> Result<()>

fn set_int(&mut self, key: &str, value: i32) -> Result<()>

fn set_double(&mut self, key: &str, value: f64) -> Result<()>

fn set_float(&mut self, key: &str, value: f32) -> Result<()>

fn set_bool(&mut self, key: &str, value: bool) -> Result<()>

fn set_algorithm(&mut self, value: i32) -> Result<()>

impl IndexParamsTrait for Ptr<HierarchicalClusteringIndexParams>

fn as_raw_mut_IndexParams(&mut self) -> *mut c_void

fn params(&mut self) -> *mut c_void

unsafe fn set_params(&mut self, val: *const c_void)

fn set_string(&mut self, key: &str, value: &str) -> Result<()>

fn set_int(&mut self, key: &str, value: i32) -> Result<()>

fn set_double(&mut self, key: &str, value: f64) -> Result<()>

fn set_float(&mut self, key: &str, value: f32) -> Result<()>

fn set_bool(&mut self, key: &str, value: bool) -> Result<()>

fn set_algorithm(&mut self, value: i32) -> Result<()>

impl IndexParamsTrait for Ptr<IndexParams>

fn as_raw_mut_IndexParams(&mut self) -> *mut c_void

fn params(&mut self) -> *mut c_void

unsafe fn set_params(&mut self, val: *const c_void)

fn set_string(&mut self, key: &str, value: &str) -> Result<()>

fn set_int(&mut self, key: &str, value: i32) -> Result<()>

fn set_double(&mut self, key: &str, value: f64) -> Result<()>

fn set_float(&mut self, key: &str, value: f32) -> Result<()>

fn set_bool(&mut self, key: &str, value: bool) -> Result<()>

fn set_algorithm(&mut self, value: i32) -> Result<()>

impl IndexParamsTrait for Ptr<KDTreeIndexParams>

fn as_raw_mut_IndexParams(&mut self) -> *mut c_void

fn params(&mut self) -> *mut c_void

unsafe fn set_params(&mut self, val: *const c_void)

fn set_string(&mut self, key: &str, value: &str) -> Result<()>

fn set_int(&mut self, key: &str, value: i32) -> Result<()>

fn set_double(&mut self, key: &str, value: f64) -> Result<()>

fn set_float(&mut self, key: &str, value: f32) -> Result<()>

fn set_bool(&mut self, key: &str, value: bool) -> Result<()>

fn set_algorithm(&mut self, value: i32) -> Result<()>

impl IndexParamsTrait for Ptr<KMeansIndexParams>

fn as_raw_mut_IndexParams(&mut self) -> *mut c_void

fn params(&mut self) -> *mut c_void

unsafe fn set_params(&mut self, val: *const c_void)

fn set_string(&mut self, key: &str, value: &str) -> Result<()>

fn set_int(&mut self, key: &str, value: i32) -> Result<()>

fn set_double(&mut self, key: &str, value: f64) -> Result<()>

fn set_float(&mut self, key: &str, value: f32) -> Result<()>

fn set_bool(&mut self, key: &str, value: bool) -> Result<()>

fn set_algorithm(&mut self, value: i32) -> Result<()>

impl IndexParamsTrait for Ptr<LinearIndexParams>

fn as_raw_mut_IndexParams(&mut self) -> *mut c_void

fn params(&mut self) -> *mut c_void

unsafe fn set_params(&mut self, val: *const c_void)

fn set_string(&mut self, key: &str, value: &str) -> Result<()>

fn set_int(&mut self, key: &str, value: i32) -> Result<()>

fn set_double(&mut self, key: &str, value: f64) -> Result<()>

fn set_float(&mut self, key: &str, value: f32) -> Result<()>

fn set_bool(&mut self, key: &str, value: bool) -> Result<()>

fn set_algorithm(&mut self, value: i32) -> Result<()>

impl IndexParamsTrait for Ptr<LshIndexParams>

fn as_raw_mut_IndexParams(&mut self) -> *mut c_void

fn params(&mut self) -> *mut c_void

unsafe fn set_params(&mut self, val: *const c_void)

fn set_string(&mut self, key: &str, value: &str) -> Result<()>

fn set_int(&mut self, key: &str, value: i32) -> Result<()>

fn set_double(&mut self, key: &str, value: f64) -> Result<()>

fn set_float(&mut self, key: &str, value: f32) -> Result<()>

fn set_bool(&mut self, key: &str, value: bool) -> Result<()>

fn set_algorithm(&mut self, value: i32) -> Result<()>

impl IndexParamsTrait for Ptr<SavedIndexParams>

fn as_raw_mut_IndexParams(&mut self) -> *mut c_void

fn params(&mut self) -> *mut c_void

unsafe fn set_params(&mut self, val: *const c_void)

fn set_string(&mut self, key: &str, value: &str) -> Result<()>

fn set_int(&mut self, key: &str, value: i32) -> Result<()>

fn set_double(&mut self, key: &str, value: f64) -> Result<()>

fn set_float(&mut self, key: &str, value: f32) -> Result<()>

fn set_bool(&mut self, key: &str, value: bool) -> Result<()>

fn set_algorithm(&mut self, value: i32) -> Result<()>

impl IndexParamsTrait for Ptr<SearchParams>

fn as_raw_mut_IndexParams(&mut self) -> *mut c_void

fn params(&mut self) -> *mut c_void

unsafe fn set_params(&mut self, val: *const c_void)

fn set_string(&mut self, key: &str, value: &str) -> Result<()>

fn set_int(&mut self, key: &str, value: i32) -> Result<()>

fn set_double(&mut self, key: &str, value: f64) -> Result<()>

fn set_float(&mut self, key: &str, value: f32) -> Result<()>

fn set_bool(&mut self, key: &str, value: bool) -> Result<()>

fn set_algorithm(&mut self, value: i32) -> Result<()>

impl IndexParamsTraitConst for Ptr<AutotunedIndexParams>

fn as_raw_IndexParams(&self) -> *const c_void

fn get_string(&self, key: &str, default_val: &str) -> Result<String>

C++ default parameters

fn get_string_def(&self, key: &str) -> Result<String>

Note

fn get_int(&self, key: &str, default_val: i32) -> Result<i32>

C++ default parameters

fn get_int_def(&self, key: &str) -> Result<i32>

Note

fn get_double(&self, key: &str, default_val: f64) -> Result<f64>

C++ default parameters

fn get_double_def(&self, key: &str) -> Result<f64>

Note

fn get_all( &self, names: &mut Vector<String>, types: &mut Vector<FlannIndexType>, str_values: &mut Vector<String>, num_values: &mut Vector<f64> ) -> Result<()>

impl IndexParamsTraitConst for Ptr<CompositeIndexParams>

fn as_raw_IndexParams(&self) -> *const c_void

fn get_string(&self, key: &str, default_val: &str) -> Result<String>

C++ default parameters

fn get_string_def(&self, key: &str) -> Result<String>

Note

fn get_int(&self, key: &str, default_val: i32) -> Result<i32>

C++ default parameters

fn get_int_def(&self, key: &str) -> Result<i32>

Note

fn get_double(&self, key: &str, default_val: f64) -> Result<f64>

C++ default parameters

fn get_double_def(&self, key: &str) -> Result<f64>

Note

fn get_all( &self, names: &mut Vector<String>, types: &mut Vector<FlannIndexType>, str_values: &mut Vector<String>, num_values: &mut Vector<f64> ) -> Result<()>

impl IndexParamsTraitConst for Ptr<HierarchicalClusteringIndexParams>

fn as_raw_IndexParams(&self) -> *const c_void

fn get_string(&self, key: &str, default_val: &str) -> Result<String>

C++ default parameters

fn get_string_def(&self, key: &str) -> Result<String>

Note

fn get_int(&self, key: &str, default_val: i32) -> Result<i32>

C++ default parameters

fn get_int_def(&self, key: &str) -> Result<i32>

Note

fn get_double(&self, key: &str, default_val: f64) -> Result<f64>

C++ default parameters

fn get_double_def(&self, key: &str) -> Result<f64>

Note

fn get_all( &self, names: &mut Vector<String>, types: &mut Vector<FlannIndexType>, str_values: &mut Vector<String>, num_values: &mut Vector<f64> ) -> Result<()>

impl IndexParamsTraitConst for Ptr<IndexParams>

fn as_raw_IndexParams(&self) -> *const c_void

fn get_string(&self, key: &str, default_val: &str) -> Result<String>

C++ default parameters

fn get_string_def(&self, key: &str) -> Result<String>

Note

fn get_int(&self, key: &str, default_val: i32) -> Result<i32>

C++ default parameters

fn get_int_def(&self, key: &str) -> Result<i32>

Note

fn get_double(&self, key: &str, default_val: f64) -> Result<f64>

C++ default parameters

fn get_double_def(&self, key: &str) -> Result<f64>

Note

fn get_all( &self, names: &mut Vector<String>, types: &mut Vector<FlannIndexType>, str_values: &mut Vector<String>, num_values: &mut Vector<f64> ) -> Result<()>

impl IndexParamsTraitConst for Ptr<KDTreeIndexParams>

fn as_raw_IndexParams(&self) -> *const c_void

fn get_string(&self, key: &str, default_val: &str) -> Result<String>

C++ default parameters

fn get_string_def(&self, key: &str) -> Result<String>

Note

fn get_int(&self, key: &str, default_val: i32) -> Result<i32>

C++ default parameters

fn get_int_def(&self, key: &str) -> Result<i32>

Note

fn get_double(&self, key: &str, default_val: f64) -> Result<f64>

C++ default parameters

fn get_double_def(&self, key: &str) -> Result<f64>

Note

fn get_all( &self, names: &mut Vector<String>, types: &mut Vector<FlannIndexType>, str_values: &mut Vector<String>, num_values: &mut Vector<f64> ) -> Result<()>

impl IndexParamsTraitConst for Ptr<KMeansIndexParams>

fn as_raw_IndexParams(&self) -> *const c_void

fn get_string(&self, key: &str, default_val: &str) -> Result<String>

C++ default parameters

fn get_string_def(&self, key: &str) -> Result<String>

Note

fn get_int(&self, key: &str, default_val: i32) -> Result<i32>

C++ default parameters

fn get_int_def(&self, key: &str) -> Result<i32>

Note

fn get_double(&self, key: &str, default_val: f64) -> Result<f64>

C++ default parameters

fn get_double_def(&self, key: &str) -> Result<f64>

Note

fn get_all( &self, names: &mut Vector<String>, types: &mut Vector<FlannIndexType>, str_values: &mut Vector<String>, num_values: &mut Vector<f64> ) -> Result<()>

impl IndexParamsTraitConst for Ptr<LinearIndexParams>

fn as_raw_IndexParams(&self) -> *const c_void

fn get_string(&self, key: &str, default_val: &str) -> Result<String>

C++ default parameters

fn get_string_def(&self, key: &str) -> Result<String>

Note

fn get_int(&self, key: &str, default_val: i32) -> Result<i32>

C++ default parameters

fn get_int_def(&self, key: &str) -> Result<i32>

Note

fn get_double(&self, key: &str, default_val: f64) -> Result<f64>

C++ default parameters

fn get_double_def(&self, key: &str) -> Result<f64>

Note

fn get_all( &self, names: &mut Vector<String>, types: &mut Vector<FlannIndexType>, str_values: &mut Vector<String>, num_values: &mut Vector<f64> ) -> Result<()>

impl IndexParamsTraitConst for Ptr<LshIndexParams>

fn as_raw_IndexParams(&self) -> *const c_void

fn get_string(&self, key: &str, default_val: &str) -> Result<String>

C++ default parameters

fn get_string_def(&self, key: &str) -> Result<String>

Note

fn get_int(&self, key: &str, default_val: i32) -> Result<i32>

C++ default parameters

fn get_int_def(&self, key: &str) -> Result<i32>

Note

fn get_double(&self, key: &str, default_val: f64) -> Result<f64>

C++ default parameters

fn get_double_def(&self, key: &str) -> Result<f64>

Note

fn get_all( &self, names: &mut Vector<String>, types: &mut Vector<FlannIndexType>, str_values: &mut Vector<String>, num_values: &mut Vector<f64> ) -> Result<()>

impl IndexParamsTraitConst for Ptr<SavedIndexParams>

fn as_raw_IndexParams(&self) -> *const c_void

fn get_string(&self, key: &str, default_val: &str) -> Result<String>

C++ default parameters

fn get_string_def(&self, key: &str) -> Result<String>

Note

fn get_int(&self, key: &str, default_val: i32) -> Result<i32>

C++ default parameters

fn get_int_def(&self, key: &str) -> Result<i32>

Note

fn get_double(&self, key: &str, default_val: f64) -> Result<f64>

C++ default parameters

fn get_double_def(&self, key: &str) -> Result<f64>

Note

fn get_all( &self, names: &mut Vector<String>, types: &mut Vector<FlannIndexType>, str_values: &mut Vector<String>, num_values: &mut Vector<f64> ) -> Result<()>

impl IndexParamsTraitConst for Ptr<SearchParams>

fn as_raw_IndexParams(&self) -> *const c_void

fn get_string(&self, key: &str, default_val: &str) -> Result<String>

C++ default parameters

fn get_string_def(&self, key: &str) -> Result<String>

Note

fn get_int(&self, key: &str, default_val: i32) -> Result<i32>

C++ default parameters

fn get_int_def(&self, key: &str) -> Result<i32>

Note

fn get_double(&self, key: &str, default_val: f64) -> Result<f64>

C++ default parameters

fn get_double_def(&self, key: &str) -> Result<f64>

Note

fn get_all( &self, names: &mut Vector<String>, types: &mut Vector<FlannIndexType>, str_values: &mut Vector<String>, num_values: &mut Vector<f64> ) -> Result<()>

impl InnerProductLayerInt8Trait for Ptr<InnerProductLayerInt8>

fn as_raw_mut_InnerProductLayerInt8(&mut self) -> *mut c_void

fn set_input_zp(&mut self, val: i32)

fn set_output_zp(&mut self, val: i32)

fn set_input_sc(&mut self, val: f32)

fn set_output_sc(&mut self, val: f32)

fn set_per_channel(&mut self, val: bool)

impl InnerProductLayerInt8TraitConst for Ptr<InnerProductLayerInt8>

fn as_raw_InnerProductLayerInt8(&self) -> *const c_void

fn input_zp(&self) -> i32

fn output_zp(&self) -> i32

fn input_sc(&self) -> f32

fn output_sc(&self) -> f32

fn per_channel(&self) -> bool

impl InnerProductLayerTrait for Ptr<InnerProductLayer>

fn as_raw_mut_InnerProductLayer(&mut self) -> *mut c_void

fn set_axis(&mut self, val: i32)

impl InnerProductLayerTrait for Ptr<InnerProductLayerInt8>

fn as_raw_mut_InnerProductLayer(&mut self) -> *mut c_void

fn set_axis(&mut self, val: i32)

impl InnerProductLayerTraitConst for Ptr<InnerProductLayer>

fn as_raw_InnerProductLayer(&self) -> *const c_void

fn axis(&self) -> i32

impl InnerProductLayerTraitConst for Ptr<InnerProductLayerInt8>

fn as_raw_InnerProductLayer(&self) -> *const c_void

fn axis(&self) -> i32

impl InpainterBaseTrait for Ptr<ColorAverageInpainter>

fn as_raw_mut_InpainterBase(&mut self) -> *mut c_void

fn set_radius(&mut self, val: i32) -> Result<()>

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn inpaint( &mut self, idx: i32, frame: &mut impl MatTrait, mask: &mut impl MatTrait ) -> Result<()>

fn set_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilized_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilization_motions(&mut self, val: &Vector<Mat>) -> Result<()>

impl InpainterBaseTrait for Ptr<ColorInpainter>

fn as_raw_mut_InpainterBase(&mut self) -> *mut c_void

fn set_radius(&mut self, val: i32) -> Result<()>

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn inpaint( &mut self, idx: i32, frame: &mut impl MatTrait, mask: &mut impl MatTrait ) -> Result<()>

fn set_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilized_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilization_motions(&mut self, val: &Vector<Mat>) -> Result<()>

impl InpainterBaseTrait for Ptr<ConsistentMosaicInpainter>

fn as_raw_mut_InpainterBase(&mut self) -> *mut c_void

fn set_radius(&mut self, val: i32) -> Result<()>

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn inpaint( &mut self, idx: i32, frame: &mut impl MatTrait, mask: &mut impl MatTrait ) -> Result<()>

fn set_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilized_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilization_motions(&mut self, val: &Vector<Mat>) -> Result<()>

impl InpainterBaseTrait for Ptr<InpainterBase>

fn as_raw_mut_InpainterBase(&mut self) -> *mut c_void

fn set_radius(&mut self, val: i32) -> Result<()>

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn inpaint( &mut self, idx: i32, frame: &mut impl MatTrait, mask: &mut impl MatTrait ) -> Result<()>

fn set_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilized_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilization_motions(&mut self, val: &Vector<Mat>) -> Result<()>

impl InpainterBaseTrait for Ptr<InpaintingPipeline>

fn as_raw_mut_InpainterBase(&mut self) -> *mut c_void

fn set_radius(&mut self, val: i32) -> Result<()>

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn inpaint( &mut self, idx: i32, frame: &mut impl MatTrait, mask: &mut impl MatTrait ) -> Result<()>

fn set_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilized_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilization_motions(&mut self, val: &Vector<Mat>) -> Result<()>

impl InpainterBaseTrait for Ptr<MotionInpainter>

fn as_raw_mut_InpainterBase(&mut self) -> *mut c_void

fn set_radius(&mut self, val: i32) -> Result<()>

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn inpaint( &mut self, idx: i32, frame: &mut impl MatTrait, mask: &mut impl MatTrait ) -> Result<()>

fn set_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilized_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilization_motions(&mut self, val: &Vector<Mat>) -> Result<()>

impl InpainterBaseTrait for Ptr<NullInpainter>

fn as_raw_mut_InpainterBase(&mut self) -> *mut c_void

fn set_radius(&mut self, val: i32) -> Result<()>

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn inpaint( &mut self, idx: i32, frame: &mut impl MatTrait, mask: &mut impl MatTrait ) -> Result<()>

fn set_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilized_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilization_motions(&mut self, val: &Vector<Mat>) -> Result<()>

impl InpainterBaseTraitConst for Ptr<ColorAverageInpainter>

fn as_raw_InpainterBase(&self) -> *const c_void

fn radius(&self) -> Result<i32>

fn motion_model(&self) -> Result<MotionModel>

fn frames(&self) -> Result<Vector<Mat>>

fn motions(&self) -> Result<Vector<Mat>>

fn stabilized_frames(&self) -> Result<Vector<Mat>>

fn stabilization_motions(&self) -> Result<Vector<Mat>>

impl InpainterBaseTraitConst for Ptr<ColorInpainter>

fn as_raw_InpainterBase(&self) -> *const c_void

fn radius(&self) -> Result<i32>

fn motion_model(&self) -> Result<MotionModel>

fn frames(&self) -> Result<Vector<Mat>>

fn motions(&self) -> Result<Vector<Mat>>

fn stabilized_frames(&self) -> Result<Vector<Mat>>

fn stabilization_motions(&self) -> Result<Vector<Mat>>

impl InpainterBaseTraitConst for Ptr<ConsistentMosaicInpainter>

fn as_raw_InpainterBase(&self) -> *const c_void

fn radius(&self) -> Result<i32>

fn motion_model(&self) -> Result<MotionModel>

fn frames(&self) -> Result<Vector<Mat>>

fn motions(&self) -> Result<Vector<Mat>>

fn stabilized_frames(&self) -> Result<Vector<Mat>>

fn stabilization_motions(&self) -> Result<Vector<Mat>>

impl InpainterBaseTraitConst for Ptr<InpainterBase>

fn as_raw_InpainterBase(&self) -> *const c_void

fn radius(&self) -> Result<i32>

fn motion_model(&self) -> Result<MotionModel>

fn frames(&self) -> Result<Vector<Mat>>

fn motions(&self) -> Result<Vector<Mat>>

fn stabilized_frames(&self) -> Result<Vector<Mat>>

fn stabilization_motions(&self) -> Result<Vector<Mat>>

impl InpainterBaseTraitConst for Ptr<InpaintingPipeline>

fn as_raw_InpainterBase(&self) -> *const c_void

fn radius(&self) -> Result<i32>

fn motion_model(&self) -> Result<MotionModel>

fn frames(&self) -> Result<Vector<Mat>>

fn motions(&self) -> Result<Vector<Mat>>

fn stabilized_frames(&self) -> Result<Vector<Mat>>

fn stabilization_motions(&self) -> Result<Vector<Mat>>

impl InpainterBaseTraitConst for Ptr<MotionInpainter>

fn as_raw_InpainterBase(&self) -> *const c_void

fn radius(&self) -> Result<i32>

fn motion_model(&self) -> Result<MotionModel>

fn frames(&self) -> Result<Vector<Mat>>

fn motions(&self) -> Result<Vector<Mat>>

fn stabilized_frames(&self) -> Result<Vector<Mat>>

fn stabilization_motions(&self) -> Result<Vector<Mat>>

impl InpainterBaseTraitConst for Ptr<NullInpainter>

fn as_raw_InpainterBase(&self) -> *const c_void

fn radius(&self) -> Result<i32>

fn motion_model(&self) -> Result<MotionModel>

fn frames(&self) -> Result<Vector<Mat>>

fn motions(&self) -> Result<Vector<Mat>>

fn stabilized_frames(&self) -> Result<Vector<Mat>>

fn stabilization_motions(&self) -> Result<Vector<Mat>>

impl InpaintingPipelineTrait for Ptr<InpaintingPipeline>

fn as_raw_mut_InpaintingPipeline(&mut self) -> *mut c_void

fn push_back(&mut self, inpainter: Ptr<InpainterBase>) -> Result<()>

fn set_radius(&mut self, val: i32) -> Result<()>

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn set_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilized_frames(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilization_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn inpaint( &mut self, idx: i32, frame: &mut impl MatTrait, mask: &mut impl MatTrait ) -> Result<()>

impl InpaintingPipelineTraitConst for Ptr<InpaintingPipeline>

fn as_raw_InpaintingPipeline(&self) -> *const c_void

fn empty(&self) -> Result<bool>

impl InstanceNormLayerTrait for Ptr<InstanceNormLayer>

fn as_raw_mut_InstanceNormLayer(&mut self) -> *mut c_void

fn set_epsilon(&mut self, val: f32)

impl InstanceNormLayerTraitConst for Ptr<InstanceNormLayer>

fn as_raw_InstanceNormLayer(&self) -> *const c_void

fn epsilon(&self) -> f32

impl InterpLayerTrait for Ptr<InterpLayer>

fn as_raw_mut_InterpLayer(&mut self) -> *mut c_void

impl InterpLayerTraitConst for Ptr<InterpLayer>

fn as_raw_InterpLayer(&self) -> *const c_void

impl KAZETrait for Ptr<KAZE>

fn as_raw_mut_KAZE(&mut self) -> *mut c_void

fn set_extended(&mut self, extended: bool) -> Result<()>

fn set_upright(&mut self, upright: bool) -> Result<()>

fn set_threshold(&mut self, threshold: f64) -> Result<()>

fn set_n_octaves(&mut self, octaves: i32) -> Result<()>

fn set_n_octave_layers(&mut self, octave_layers: i32) -> Result<()>

fn set_diffusivity(&mut self, diff: KAZE_DiffusivityType) -> Result<()>

impl KAZETraitConst for Ptr<KAZE>

fn as_raw_KAZE(&self) -> *const c_void

fn get_extended(&self) -> Result<bool>

fn get_upright(&self) -> Result<bool>

fn get_threshold(&self) -> Result<f64>

fn get_n_octaves(&self) -> Result<i32>

fn get_n_octave_layers(&self) -> Result<i32>

fn get_diffusivity(&self) -> Result<KAZE_DiffusivityType>

fn get_default_name(&self) -> Result<String>

impl KDTreeIndexParamsTrait for Ptr<KDTreeIndexParams>

fn as_raw_mut_KDTreeIndexParams(&mut self) -> *mut c_void

impl KDTreeIndexParamsTraitConst for Ptr<KDTreeIndexParams>

fn as_raw_KDTreeIndexParams(&self) -> *const c_void

impl KMeansIndexParamsTrait for Ptr<KMeansIndexParams>

fn as_raw_mut_KMeansIndexParams(&mut self) -> *mut c_void

impl KMeansIndexParamsTraitConst for Ptr<KMeansIndexParams>

fn as_raw_KMeansIndexParams(&self) -> *const c_void

impl KNearestTrait for Ptr<KNearest>

fn as_raw_mut_KNearest(&mut self) -> *mut c_void

fn set_default_k(&mut self, val: i32) -> Result<()>

Default number of neighbors to use in predict method.

fn set_is_classifier(&mut self, val: bool) -> Result<()>

Whether classification or regression model should be trained.

fn set_emax(&mut self, val: i32) -> Result<()>

Parameter for KDTree implementation.

fn set_algorithm_type(&mut self, val: i32) -> Result<()>

%Algorithm type, one of KNearest::Types.

impl KNearestTraitConst for Ptr<KNearest>

fn as_raw_KNearest(&self) -> *const c_void

fn get_default_k(&self) -> Result<i32>

Default number of neighbors to use in predict method.

fn get_is_classifier(&self) -> Result<bool>

Whether classification or regression model should be trained.

fn get_emax(&self) -> Result<i32>

Parameter for KDTree implementation.

fn get_algorithm_type(&self) -> Result<i32>

%Algorithm type, one of KNearest::Types.

fn find_nearest( &self, samples: &impl ToInputArray, k: i32, results: &mut impl ToOutputArray, neighbor_responses: &mut impl ToOutputArray, dist: &mut impl ToOutputArray ) -> Result<f32>

Finds the neighbors and predicts responses for input vectors.

fn find_nearest_def( &self, samples: &impl ToInputArray, k: i32, results: &mut impl ToOutputArray ) -> Result<f32>

Finds the neighbors and predicts responses for input vectors.

impl KeypointBasedMotionEstimatorGpuTrait for Ptr<KeypointBasedMotionEstimatorGpu>

fn as_raw_mut_KeypointBasedMotionEstimatorGpu(&mut self) -> *mut c_void

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn set_outlier_rejector(&mut self, val: Ptr<IOutlierRejector>) -> Result<()>

fn estimate( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst, ok: &mut bool ) -> Result<Mat>

C++ default parameters

fn estimate_def( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst ) -> Result<Mat>

Note

fn estimate_1( &mut self, frame0: &impl GpuMatTraitConst, frame1: &impl GpuMatTraitConst, ok: &mut bool ) -> Result<Mat>

C++ default parameters

fn estimate_def_1( &mut self, frame0: &impl GpuMatTraitConst, frame1: &impl GpuMatTraitConst ) -> Result<Mat>

Note

impl KeypointBasedMotionEstimatorGpuTraitConst for Ptr<KeypointBasedMotionEstimatorGpu>

fn as_raw_KeypointBasedMotionEstimatorGpu(&self) -> *const c_void

fn motion_model(&self) -> Result<MotionModel>

fn outlier_rejector(&self) -> Result<Ptr<IOutlierRejector>>

impl KeypointBasedMotionEstimatorTrait for Ptr<KeypointBasedMotionEstimator>

fn as_raw_mut_KeypointBasedMotionEstimator(&mut self) -> *mut c_void

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn set_detector(&mut self, val: Ptr<Feature2D>) -> Result<()>

fn set_optical_flow_estimator( &mut self, val: Ptr<ISparseOptFlowEstimator> ) -> Result<()>

fn set_outlier_rejector(&mut self, val: Ptr<IOutlierRejector>) -> Result<()>

fn set_frame_mask(&mut self, mask: &impl ToInputArray) -> Result<()>

fn estimate_mat( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst, ok: &mut bool ) -> Result<Mat>

C++ default parameters

fn estimate_mat_def( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst ) -> Result<Mat>

Note

fn estimate( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, ok: &mut bool ) -> Result<Mat>

C++ default parameters

fn estimate_def( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray ) -> Result<Mat>

Note

impl KeypointBasedMotionEstimatorTraitConst for Ptr<KeypointBasedMotionEstimator>

fn as_raw_KeypointBasedMotionEstimator(&self) -> *const c_void

fn motion_model(&self) -> Result<MotionModel>

fn detector(&self) -> Result<Ptr<Feature2D>>

fn optical_flow_estimator(&self) -> Result<Ptr<ISparseOptFlowEstimator>>

fn outlier_rejector(&self) -> Result<Ptr<IOutlierRejector>>

impl Kinfu_Detail_PoseGraphTrait for Ptr<Kinfu_Detail_PoseGraph>

fn as_raw_mut_Kinfu_Detail_PoseGraph(&mut self) -> *mut c_void

fn add_node( &mut self, _node_id: size_t, _pose: Affine3d, fixed: bool ) -> Result<()>

fn set_node_fixed(&mut self, node_id: size_t, fixed: bool) -> Result<bool>

fn add_edge( &mut self, _source_node_id: size_t, _target_node_id: size_t, _transformation: Affine3f, _information: Matx66f ) -> Result<()>

C++ default parameters

fn add_edge_def( &mut self, _source_node_id: size_t, _target_node_id: size_t, _transformation: Affine3f ) -> Result<()>

Note

fn optimize(&mut self, tc: TermCriteria) -> Result<i32>

C++ default parameters

fn optimize_def(&mut self) -> Result<i32>

Note

impl Kinfu_Detail_PoseGraphTraitConst for Ptr<Kinfu_Detail_PoseGraph>

fn as_raw_Kinfu_Detail_PoseGraph(&self) -> *const c_void

fn is_node_exist(&self, node_id: size_t) -> Result<bool>

fn is_node_fixed(&self, node_id: size_t) -> Result<bool>

fn get_node_pose(&self, node_id: size_t) -> Result<Affine3d>

fn get_nodes_ids(&self) -> Result<Vector<size_t>>

fn get_num_nodes(&self) -> Result<size_t>

fn get_edge_start(&self, i: size_t) -> Result<size_t>

fn get_edge_end(&self, i: size_t) -> Result<size_t>

fn get_num_edges(&self) -> Result<size_t>

fn is_valid(&self) -> Result<bool>

fn calc_energy(&self) -> Result<f64>

impl Kinfu_KinFuTrait for Ptr<Kinfu_KinFu>

fn as_raw_mut_Kinfu_KinFu(&mut self) -> *mut c_void

fn reset(&mut self) -> Result<()>

Resets the algorithm

fn update(&mut self, depth: &impl ToInputArray) -> Result<bool>

Process next depth frame

impl Kinfu_KinFuTraitConst for Ptr<Kinfu_KinFu>

fn as_raw_Kinfu_KinFu(&self) -> *const c_void

fn get_params(&self) -> Result<Kinfu_Params>

Get current parameters

fn render(&self, image: &mut impl ToOutputArray) -> Result<()>

Renders a volume into an image

fn render_1( &self, image: &mut impl ToOutputArray, camera_pose: Matx44f ) -> Result<()>

Renders a volume into an image

fn get_cloud( &self, points: &mut impl ToOutputArray, normals: &mut impl ToOutputArray ) -> Result<()>

Gets points and normals of current 3d mesh

fn get_points(&self, points: &mut impl ToOutputArray) -> Result<()>

Gets points of current 3d mesh

fn get_normals( &self, points: &impl ToInputArray, normals: &mut impl ToOutputArray ) -> Result<()>

Calculates normals for given points

fn get_pose(&self) -> Result<Affine3f>

Get current pose in voxel space

impl Kinfu_ParamsTrait for Ptr<Kinfu_Params>

fn as_raw_mut_Kinfu_Params(&mut self) -> *mut c_void

fn set_frame_size(&mut self, val: Size)

frame size in pixels

fn set_volume_type(&mut self, val: Kinfu_VolumeType)

rgb frame size in pixels

fn set_intr(&mut self, val: Matx33f)

camera intrinsics

fn set_rgb_intr(&mut self, val: Matx33f)

rgb camera intrinsics

fn set_depth_factor(&mut self, val: f32)

pre-scale per 1 meter for input values

fn set_bilateral_sigma_depth(&mut self, val: f32)

Depth sigma in meters for bilateral smooth

fn set_bilateral_sigma_spatial(&mut self, val: f32)

Spatial sigma in pixels for bilateral smooth

fn set_bilateral_kernel_size(&mut self, val: i32)

Kernel size in pixels for bilateral smooth

fn set_pyramid_levels(&mut self, val: i32)

Number of pyramid levels for ICP

fn set_volume_dims(&mut self, val: Vec3i)

Resolution of voxel space

fn set_voxel_size(&mut self, val: f32)

Size of voxel in meters

fn set_tsdf_min_camera_movement(&mut self, val: f32)

Minimal camera movement in meters

fn set_volume_pose(&mut self, val: Affine3f)

initial volume pose in meters

fn set_tsdf_trunc_dist(&mut self, val: f32)

distance to truncate in meters

fn set_tsdf_max_weight(&mut self, val: i32)

max number of frames per voxel

fn set_raycast_step_factor(&mut self, val: f32)

A length of one raycast step

fn set_light_pose(&mut self, val: Vec3f)

light pose for rendering in meters

fn set_icp_dist_thresh(&mut self, val: f32)

distance theshold for ICP in meters

fn set_icp_angle_thresh(&mut self, val: f32)

angle threshold for ICP in radians

fn set_icp_iterations(&mut self, val: Vector<i32>)

number of ICP iterations for each pyramid level

fn set_truncate_threshold(&mut self, val: f32)

Threshold for depth truncation in meters

fn set_initial_volume_pose(&mut self, r: Matx33f, t: Vec3f) -> Result<()>

Set Initial Volume Pose Sets the initial pose of the TSDF volume.

fn set_initial_volume_pose_1(&mut self, homogen_tf: Matx44f) -> Result<()>

Set Initial Volume Pose Sets the initial pose of the TSDF volume.

impl Kinfu_ParamsTraitConst for Ptr<Kinfu_Params>

fn as_raw_Kinfu_Params(&self) -> *const c_void

fn frame_size(&self) -> Size

frame size in pixels

fn volume_type(&self) -> Kinfu_VolumeType

rgb frame size in pixels

fn intr(&self) -> Matx33f

camera intrinsics

fn rgb_intr(&self) -> Matx33f

rgb camera intrinsics

fn depth_factor(&self) -> f32

pre-scale per 1 meter for input values

fn bilateral_sigma_depth(&self) -> f32

Depth sigma in meters for bilateral smooth

fn bilateral_sigma_spatial(&self) -> f32

Spatial sigma in pixels for bilateral smooth

fn bilateral_kernel_size(&self) -> i32

Kernel size in pixels for bilateral smooth

fn pyramid_levels(&self) -> i32

Number of pyramid levels for ICP

fn volume_dims(&self) -> Vec3i

Resolution of voxel space

fn voxel_size(&self) -> f32

Size of voxel in meters

fn tsdf_min_camera_movement(&self) -> f32

Minimal camera movement in meters

fn volume_pose(&self) -> Affine3f

initial volume pose in meters

fn tsdf_trunc_dist(&self) -> f32

distance to truncate in meters

fn tsdf_max_weight(&self) -> i32

max number of frames per voxel

fn raycast_step_factor(&self) -> f32

A length of one raycast step

fn light_pose(&self) -> Vec3f

light pose for rendering in meters

fn icp_dist_thresh(&self) -> f32

distance theshold for ICP in meters

fn icp_angle_thresh(&self) -> f32

angle threshold for ICP in radians

fn icp_iterations(&self) -> Vector<i32>

number of ICP iterations for each pyramid level

fn truncate_threshold(&self) -> f32

Threshold for depth truncation in meters

impl Kinfu_VolumeParamsTrait for Ptr<Kinfu_VolumeParams>

fn as_raw_mut_Kinfu_VolumeParams(&mut self) -> *mut c_void

fn set_type(&mut self, val: Kinfu_VolumeType)

Type of Volume Values can be TSDF (single volume) or HASHTSDF (hashtable of volume units)

fn set_resolution(&mut self, val: Vec3i)

Resolution of voxel space Number of voxels in each dimension. Applicable only for TSDF Volume. HashTSDF volume only supports equal resolution in all three dimensions

fn set_unit_resolution(&mut self, val: i32)

Resolution of volumeUnit in voxel space Number of voxels in each dimension for volumeUnit Applicable only for hashTSDF.

fn set_pose(&mut self, val: Affine3f)

Initial pose of the volume in meters

fn set_voxel_size(&mut self, val: f32)

Length of voxels in meters

fn set_tsdf_trunc_dist(&mut self, val: f32)

TSDF truncation distance Distances greater than value from surface will be truncated to 1.0

fn set_max_weight(&mut self, val: i32)

Max number of frames to integrate per voxel Represents the max number of frames over which a running average of the TSDF is calculated for a voxel

fn set_depth_trunc_threshold(&mut self, val: f32)

Threshold for depth truncation in meters Truncates the depth greater than threshold to 0

fn set_raycast_step_factor(&mut self, val: f32)

Length of single raycast step Describes the percentage of voxel length that is skipped per march

impl Kinfu_VolumeParamsTraitConst for Ptr<Kinfu_VolumeParams>

fn as_raw_Kinfu_VolumeParams(&self) -> *const c_void

fn typ(&self) -> Kinfu_VolumeType

Type of Volume Values can be TSDF (single volume) or HASHTSDF (hashtable of volume units)

fn resolution(&self) -> Vec3i

Resolution of voxel space Number of voxels in each dimension. Applicable only for TSDF Volume. HashTSDF volume only supports equal resolution in all three dimensions

fn unit_resolution(&self) -> i32

Resolution of volumeUnit in voxel space Number of voxels in each dimension for volumeUnit Applicable only for hashTSDF.

fn pose(&self) -> Affine3f

Initial pose of the volume in meters

fn voxel_size(&self) -> f32

Length of voxels in meters

fn tsdf_trunc_dist(&self) -> f32

TSDF truncation distance Distances greater than value from surface will be truncated to 1.0

fn max_weight(&self) -> i32

Max number of frames to integrate per voxel Represents the max number of frames over which a running average of the TSDF is calculated for a voxel

fn depth_trunc_threshold(&self) -> f32

Threshold for depth truncation in meters Truncates the depth greater than threshold to 0

fn raycast_step_factor(&self) -> f32

Length of single raycast step Describes the percentage of voxel length that is skipped per march

impl Kinfu_VolumeTrait for Ptr<Kinfu_Volume>

fn as_raw_mut_Kinfu_Volume(&mut self) -> *mut c_void

fn integrate( &mut self, _depth: &impl ToInputArray, depth_factor: f32, camera_pose: Matx44f, intrinsics: Kinfu_Intr, frame_id: i32 ) -> Result<()>

C++ default parameters

fn integrate_def( &mut self, _depth: &impl ToInputArray, depth_factor: f32, camera_pose: Matx44f, intrinsics: Kinfu_Intr ) -> Result<()>

Note

fn integrate_1( &mut self, _depth: &impl ToInputArray, _rgb: &impl ToInputArray, depth_factor: f32, camera_pose: Matx44f, intrinsics: Kinfu_Intr, rgb_intrinsics: Kinfu_Intr, frame_id: i32 ) -> Result<()>

C++ default parameters

fn integrate_def_1( &mut self, _depth: &impl ToInputArray, _rgb: &impl ToInputArray, depth_factor: f32, camera_pose: Matx44f, intrinsics: Kinfu_Intr, rgb_intrinsics: Kinfu_Intr ) -> Result<()>

Note

fn reset(&mut self) -> Result<()>

impl Kinfu_VolumeTraitConst for Ptr<Kinfu_Volume>

fn as_raw_Kinfu_Volume(&self) -> *const c_void

fn voxel_size(&self) -> f32

fn voxel_size_inv(&self) -> f32

fn pose(&self) -> Affine3f

fn raycast_step_factor(&self) -> f32

fn raycast( &self, camera_pose: Matx44f, intrinsics: Kinfu_Intr, frame_size: Size, points: &mut impl ToOutputArray, normals: &mut impl ToOutputArray ) -> Result<()>

fn raycast_1( &self, camera_pose: Matx44f, intrinsics: Kinfu_Intr, frame_size: Size, points: &mut impl ToOutputArray, normals: &mut impl ToOutputArray, colors: &mut impl ToOutputArray ) -> Result<()>

fn fetch_normals( &self, points: &impl ToInputArray, _normals: &mut impl ToOutputArray ) -> Result<()>

fn fetch_points_normals( &self, points: &mut impl ToOutputArray, normals: &mut impl ToOutputArray ) -> Result<()>

fn fetch_points_normals_colors( &self, unnamed: &mut impl ToOutputArray, unnamed_1: &mut impl ToOutputArray, unnamed_2: &mut impl ToOutputArray ) -> Result<()>

impl LATCHTrait for Ptr<LATCH>

fn as_raw_mut_LATCH(&mut self) -> *mut c_void

fn set_bytes(&mut self, bytes: i32) -> Result<()>

fn set_rotation_invariance(&mut self, rotation_invariance: bool) -> Result<()>

fn set_half_ss_dsize(&mut self, half_ssd_size: i32) -> Result<()>

fn set_sigma(&mut self, sigma: f64) -> Result<()>

impl LATCHTraitConst for Ptr<LATCH>

fn as_raw_LATCH(&self) -> *const c_void

fn get_bytes(&self) -> Result<i32>

fn get_rotation_invariance(&self) -> Result<bool>

fn get_half_ss_dsize(&self) -> Result<i32>

fn get_sigma(&self) -> Result<f64>

fn get_default_name(&self) -> Result<String>

impl LBPHFaceRecognizerTrait for Ptr<LBPHFaceRecognizer>

fn as_raw_mut_LBPHFaceRecognizer(&mut self) -> *mut c_void

fn set_grid_x(&mut self, val: i32) -> Result<()>

See also

fn set_grid_y(&mut self, val: i32) -> Result<()>

See also

fn set_radius(&mut self, val: i32) -> Result<()>

See also

fn set_neighbors(&mut self, val: i32) -> Result<()>

See also

fn set_threshold(&mut self, val: f64) -> Result<()>

See also

impl LBPHFaceRecognizerTraitConst for Ptr<LBPHFaceRecognizer>

fn as_raw_LBPHFaceRecognizer(&self) -> *const c_void

fn get_grid_x(&self) -> Result<i32>

See also

fn get_grid_y(&self) -> Result<i32>

See also

fn get_radius(&self) -> Result<i32>

See also

fn get_neighbors(&self) -> Result<i32>

See also

fn get_threshold(&self) -> Result<f64>

See also

fn get_histograms(&self) -> Result<Vector<Mat>>

fn get_labels(&self) -> Result<Mat>

impl LMSolverTrait for Ptr<LMSolver>

fn as_raw_mut_LMSolver(&mut self) -> *mut c_void

fn set_max_iters(&mut self, max_iters: i32) -> Result<()>

Sets the maximum number of iterations

impl LMSolverTraitConst for Ptr<LMSolver>

fn as_raw_LMSolver(&self) -> *const c_void

fn run(&self, param: &mut impl ToInputOutputArray) -> Result<i32>

Runs Levenberg-Marquardt algorithm using the passed vector of parameters as the start point. The final vector of parameters (whether the algorithm converged or not) is stored at the same vector. The method returns the number of iterations used. If it’s equal to the previously specified maxIters, there is a big chance the algorithm did not converge.

fn get_max_iters(&self) -> Result<i32>

Retrieves the current maximum number of iterations

impl LMSolver_CallbackTrait for Ptr<LMSolver_Callback>

fn as_raw_mut_LMSolver_Callback(&mut self) -> *mut c_void

impl LMSolver_CallbackTraitConst for Ptr<LMSolver_Callback>

fn as_raw_LMSolver_Callback(&self) -> *const c_void

fn compute( &self, param: &impl ToInputArray, err: &mut impl ToOutputArray, j: &mut impl ToOutputArray ) -> Result<bool>

computes error and Jacobian for the specified vector of parameters

impl LRNLayerTrait for Ptr<LRNLayer>

fn as_raw_mut_LRNLayer(&mut self) -> *mut c_void

fn set_type(&mut self, val: i32)

fn set_size(&mut self, val: i32)

fn set_alpha(&mut self, val: f32)

fn set_beta(&mut self, val: f32)

fn set_bias(&mut self, val: f32)

fn set_norm_by_size(&mut self, val: bool)

impl LRNLayerTraitConst for Ptr<LRNLayer>

fn as_raw_LRNLayer(&self) -> *const c_void

fn typ(&self) -> i32

fn size(&self) -> i32

fn alpha(&self) -> f32

fn beta(&self) -> f32

fn bias(&self) -> f32

fn norm_by_size(&self) -> bool

impl LSDDetectorTrait for Ptr<LSDDetector>

fn as_raw_mut_LSDDetector(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl MatTraitConst, keypoints: &mut Vector<KeyLine>, scale: i32, num_octaves: i32, mask: &impl MatTraitConst ) -> Result<()>

Detect lines inside an image.

fn detect_def( &mut self, image: &impl MatTraitConst, keypoints: &mut Vector<KeyLine>, scale: i32, num_octaves: i32 ) -> Result<()>

Detect lines inside an image.

impl LSDDetectorTraitConst for Ptr<LSDDetector>

fn as_raw_LSDDetector(&self) -> *const c_void

fn detect_multiple( &self, images: &Vector<Mat>, keylines: &mut Vector<Vector<KeyLine>>, scale: i32, num_octaves: i32, masks: &Vector<Mat> ) -> Result<()>

Detect lines inside an image.

fn detect_multiple_def( &self, images: &Vector<Mat>, keylines: &mut Vector<Vector<KeyLine>>, scale: i32, num_octaves: i32 ) -> Result<()>

@overload

impl LSTMLayerTrait for Ptr<LSTMLayer>

fn as_raw_mut_LSTMLayer(&mut self) -> *mut c_void

fn set_weights( &mut self, wh: &impl MatTraitConst, wx: &impl MatTraitConst, b: &impl MatTraitConst ) -> Result<()>

👎Deprecated: Use LayerParams::blobs instead.

Deprecated: Use LayerParams::blobs instead. Set trained weights for LSTM layer.

fn set_out_shape(&mut self, out_tail_shape: &MatShape) -> Result<()>

Specifies shape of output blob which will be [[T], N] + @p outTailShape. @details If this parameter is empty or unset then @p outTailShape = [Wh.size(0)] will be used, where Wh is parameter from setWeights().

fn set_out_shape_def(&mut self) -> Result<()>

Specifies shape of output blob which will be [[T], N] + @p outTailShape. @details If this parameter is empty or unset then @p outTailShape = [Wh.size(0)] will be used, where Wh is parameter from setWeights().

fn set_use_timstamps_dim(&mut self, use_: bool) -> Result<()>

👎Deprecated: Use flag produce_cell_output in LayerParams.

Deprecated: Use flag produce_cell_output in LayerParams. Specifies either interpret first dimension of input blob as timestamp dimension either as sample.

fn set_use_timstamps_dim_def(&mut self) -> Result<()>

👎Deprecated: Use flag produce_cell_output in LayerParams.

Deprecated: Use flag produce_cell_output in LayerParams. Specifies either interpret first dimension of input blob as timestamp dimension either as sample.

fn set_produce_cell_output(&mut self, produce: bool) -> Result<()>

👎Deprecated: Use flag use_timestamp_dim in LayerParams.

Deprecated: Use flag use_timestamp_dim in LayerParams. If this flag is set to true then layer will produce @f$ c_t @f$ as second output. @details Shape of the second output is the same as first output.

fn set_produce_cell_output_def(&mut self) -> Result<()>

👎Deprecated: Use flag use_timestamp_dim in LayerParams.

Deprecated: Use flag use_timestamp_dim in LayerParams. If this flag is set to true then layer will produce @f$ c_t @f$ as second output. @details Shape of the second output is the same as first output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

impl LSTMLayerTraitConst for Ptr<LSTMLayer>

fn as_raw_LSTMLayer(&self) -> *const c_void

impl LUCIDTrait for Ptr<LUCID>

fn as_raw_mut_LUCID(&mut self) -> *mut c_void

fn set_lucid_kernel(&mut self, lucid_kernel: i32) -> Result<()>

fn set_blur_kernel(&mut self, blur_kernel: i32) -> Result<()>

impl LUCIDTraitConst for Ptr<LUCID>

fn as_raw_LUCID(&self) -> *const c_void

fn get_lucid_kernel(&self) -> Result<i32>

fn get_blur_kernel(&self) -> Result<i32>

fn get_default_name(&self) -> Result<String>

impl LargeKinfuTrait for Ptr<LargeKinfu>

fn as_raw_mut_LargeKinfu(&mut self) -> *mut c_void

fn reset(&mut self) -> Result<()>

fn update(&mut self, depth: &impl ToInputArray) -> Result<bool>

impl LargeKinfuTraitConst for Ptr<LargeKinfu>

fn as_raw_LargeKinfu(&self) -> *const c_void

fn get_params(&self) -> Result<Params>

fn render(&self, image: &mut impl ToOutputArray) -> Result<()>

fn render_1( &self, image: &mut impl ToOutputArray, camera_pose: Matx44f ) -> Result<()>

fn get_cloud( &self, points: &mut impl ToOutputArray, normals: &mut impl ToOutputArray ) -> Result<()>

fn get_points(&self, points: &mut impl ToOutputArray) -> Result<()>

fn get_normals( &self, points: &impl ToInputArray, normals: &mut impl ToOutputArray ) -> Result<()>

fn get_pose(&self) -> Result<Affine3f>

impl LayerNormLayerTrait for Ptr<LayerNormLayer>

fn as_raw_mut_LayerNormLayer(&mut self) -> *mut c_void

fn set_has_bias(&mut self, val: bool)

fn set_axis(&mut self, val: i32)

fn set_epsilon(&mut self, val: f32)

impl LayerNormLayerTraitConst for Ptr<LayerNormLayer>

fn as_raw_LayerNormLayer(&self) -> *const c_void

fn has_bias(&self) -> bool

fn axis(&self) -> i32

fn epsilon(&self) -> f32

impl LayerTrait for Ptr<AbsLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<AccumLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<AcosLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<AcoshLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ActivationLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ActivationLayerInt8>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ArgLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<AsinLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<AsinhLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<AtanLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<AtanhLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<AttentionLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<BNLLLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<BaseConvolutionLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<BatchNormLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<BatchNormLayerInt8>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<BlankLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<CeilLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<CeluLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ChannelsPReLULayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<CompareLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ConcatLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ConstLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ConvolutionLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ConvolutionLayerInt8>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<CorrelationLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<CosLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<CoshLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<CropAndResizeLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<CropLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<CumSumLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<DataAugmentationLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<DeconvolutionLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<DequantizeLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<DetectionOutputLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ELULayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<EinsumLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<EltwiseLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<EltwiseLayerInt8>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ErfLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ExpLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ExpandLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<FlattenLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<FloorLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<FlowWarpLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<GRULayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<GatherElementsLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<GatherLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<GeluApproximationLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<GeluLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<GemmLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<HardSigmoidLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<HardSwishLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<InnerProductLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<InnerProductLayerInt8>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<InstanceNormLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<InterpLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<LRNLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<LSTMLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<Layer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<LayerNormLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<LogLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<MVNLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<MatMulLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<MaxUnpoolLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<MishLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<NaryEltwiseLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<NormalizeBBoxLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<NotLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<PaddingLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<PermuteLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<PoolingLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<PoolingLayerInt8>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<PowerLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<PriorBoxLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ProposalLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<QuantizeLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<RNNLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ReLU6Layer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ReLULayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ReciprocalLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ReduceLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<RegionLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ReorgLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<RequantizeLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ReshapeLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ResizeLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<RoundLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ScaleLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ScaleLayerInt8>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ScatterLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ScatterNDLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<SeluLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ShiftLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ShiftLayerInt8>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ShrinkLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ShuffleChannelLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<SigmoidLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<SignLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<SinLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<SinhLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<SliceLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<SoftmaxLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<SoftmaxLayerInt8>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<SoftplusLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<SoftsignLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<SplitLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<SqrtLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<SwishLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<TanHLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<TanLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<ThresholdedReluLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTrait for Ptr<TileLayer>

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated: Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat> ) -> Result<()>

👎Deprecated: This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTraitConst for Ptr<AbsLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<AccumLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<AcosLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<AcoshLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ActivationLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ActivationLayerInt8>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ArgLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<AsinLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<AsinhLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<AtanLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<AtanhLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<AttentionLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<BNLLLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<BaseConvolutionLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<BatchNormLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<BatchNormLayerInt8>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<BlankLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<CeilLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<CeluLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ChannelsPReLULayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<CompareLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ConcatLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ConstLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ConvolutionLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ConvolutionLayerInt8>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<CorrelationLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<CosLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<CoshLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<CropAndResizeLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<CropLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<CumSumLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<DataAugmentationLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<DeconvolutionLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<DequantizeLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<DetectionOutputLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ELULayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<EinsumLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<EltwiseLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<EltwiseLayerInt8>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ErfLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ExpLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ExpandLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<FlattenLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<FloorLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<FlowWarpLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<GRULayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<GatherElementsLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<GatherLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<GeluApproximationLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<GeluLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<GemmLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<HardSigmoidLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<HardSwishLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<InnerProductLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<InnerProductLayerInt8>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<InstanceNormLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<InterpLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<LRNLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<LSTMLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<Layer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<LayerNormLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<LogLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<MVNLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<MatMulLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<MaxUnpoolLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<MishLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<NaryEltwiseLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<NormalizeBBoxLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<NotLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<PaddingLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<PermuteLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<PoolingLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<PoolingLayerInt8>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<PowerLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<PriorBoxLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ProposalLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<QuantizeLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<RNNLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ReLU6Layer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ReLULayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ReciprocalLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ReduceLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<RegionLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ReorgLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<RequantizeLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ReshapeLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ResizeLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<RoundLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ScaleLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ScaleLayerInt8>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ScatterLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ScatterNDLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<SeluLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ShiftLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ShiftLayerInt8>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ShrinkLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ShuffleChannelLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<SigmoidLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<SignLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<SinLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<SinhLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<SliceLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<SoftmaxLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<SoftmaxLayerInt8>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<SoftplusLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<SoftsignLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<SplitLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<SqrtLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<SwishLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<TanHLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<TanLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<ThresholdedReluLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LayerTraitConst for Ptr<TileLayer>

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape> ) -> Result<bool>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl LearningBasedWBTrait for Ptr<LearningBasedWB>

fn as_raw_mut_LearningBasedWB(&mut self) -> *mut c_void

fn extract_simple_features( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Implements the feature extraction part of the algorithm.

fn set_range_max_val(&mut self, val: i32) -> Result<()>

Maximum possible value of the input image (e.g. 255 for 8 bit images, 4095 for 12 bit images)

fn set_saturation_threshold(&mut self, val: f32) -> Result<()>

Threshold that is used to determine saturated pixels, i.e. pixels where at least one of the channels exceeds inline formula are ignored.

fn set_hist_bin_num(&mut self, val: i32) -> Result<()>

Defines the size of one dimension of a three-dimensional RGB histogram that is used internally by the algorithm. It often makes sense to increase the number of bins for images with higher bit depth (e.g. 256 bins for a 12 bit image).

impl LearningBasedWBTraitConst for Ptr<LearningBasedWB>

fn as_raw_LearningBasedWB(&self) -> *const c_void

fn get_range_max_val(&self) -> Result<i32>

Maximum possible value of the input image (e.g. 255 for 8 bit images, 4095 for 12 bit images)

fn get_saturation_threshold(&self) -> Result<f32>

Threshold that is used to determine saturated pixels, i.e. pixels where at least one of the channels exceeds inline formula are ignored.

fn get_hist_bin_num(&self) -> Result<i32>

Defines the size of one dimension of a three-dimensional RGB histogram that is used internally by the algorithm. It often makes sense to increase the number of bins for images with higher bit depth (e.g. 256 bins for a 12 bit image).

impl LineMod_ColorGradientTrait for Ptr<LineMod_ColorGradient>

fn as_raw_mut_LineMod_ColorGradient(&mut self) -> *mut c_void

fn set_weak_threshold(&mut self, val: f32)

fn set_num_features(&mut self, val: size_t)

fn set_strong_threshold(&mut self, val: f32)

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

impl LineMod_ColorGradientTraitConst for Ptr<LineMod_ColorGradient>

fn as_raw_LineMod_ColorGradient(&self) -> *const c_void

fn weak_threshold(&self) -> f32

fn num_features(&self) -> size_t

fn strong_threshold(&self) -> f32

fn name(&self) -> Result<String>

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

impl LineMod_DepthNormalTrait for Ptr<LineMod_DepthNormal>

fn as_raw_mut_LineMod_DepthNormal(&mut self) -> *mut c_void

fn set_distance_threshold(&mut self, val: i32)

fn set_difference_threshold(&mut self, val: i32)

fn set_num_features(&mut self, val: size_t)

fn set_extract_threshold(&mut self, val: i32)

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

impl LineMod_DepthNormalTraitConst for Ptr<LineMod_DepthNormal>

fn as_raw_LineMod_DepthNormal(&self) -> *const c_void

fn distance_threshold(&self) -> i32

fn difference_threshold(&self) -> i32

fn num_features(&self) -> size_t

fn extract_threshold(&self) -> i32

fn name(&self) -> Result<String>

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

impl LineMod_DetectorTrait for Ptr<LineMod_Detector>

fn as_raw_mut_LineMod_Detector(&mut self) -> *mut c_void

fn add_template( &mut self, sources: &Vector<Mat>, class_id: &str, object_mask: &impl MatTraitConst, bounding_box: &mut Rect ) -> Result<i32>

\brief Add new object template.

fn add_template_def( &mut self, sources: &Vector<Mat>, class_id: &str, object_mask: &impl MatTraitConst ) -> Result<i32>

\brief Add new object template.

fn add_synthetic_template( &mut self, templates: &Vector<LineMod_Template>, class_id: &str ) -> Result<i32>

\brief Add a new object template computed by external means.

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

fn read_class( &mut self, fn_: &impl FileNodeTraitConst, class_id_override: &str ) -> Result<String>

C++ default parameters

fn read_class_def(&mut self, fn_: &impl FileNodeTraitConst) -> Result<String>

Note

fn read_classes( &mut self, class_ids: &Vector<String>, format: &str ) -> Result<()>

C++ default parameters

fn read_classes_def(&mut self, class_ids: &Vector<String>) -> Result<()>

Note

impl LineMod_DetectorTraitConst for Ptr<LineMod_Detector>

fn as_raw_LineMod_Detector(&self) -> *const c_void

fn match_( &self, sources: &Vector<Mat>, threshold: f32, matches: &mut Vector<LineMod_Match>, class_ids: &Vector<String>, quantized_images: &mut impl ToOutputArray, masks: &Vector<Mat> ) -> Result<()>

\brief Detect objects by template matching.

fn match__def( &self, sources: &Vector<Mat>, threshold: f32, matches: &mut Vector<LineMod_Match> ) -> Result<()>

\brief Detect objects by template matching.

fn get_modalities(&self) -> Result<Vector<Ptr<LineMod_Modality>>>

\brief Get the modalities used by this detector.

fn get_t(&self, pyramid_level: i32) -> Result<i32>

\brief Get sampling step T at pyramid_level.

fn pyramid_levels(&self) -> Result<i32>

\brief Get number of pyramid levels used by this detector.

fn get_templates( &self, class_id: &str, template_id: i32 ) -> Result<Vector<LineMod_Template>>

\brief Get the template pyramid identified by template_id.

fn num_templates(&self) -> Result<i32>

fn num_templates_1(&self, class_id: &str) -> Result<i32>

fn num_classes(&self) -> Result<i32>

fn class_ids(&self) -> Result<Vector<String>>

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

fn write_class( &self, class_id: &str, fs: &mut impl FileStorageTrait ) -> Result<()>

fn write_classes(&self, format: &str) -> Result<()>

C++ default parameters

fn write_classes_def(&self) -> Result<()>

Note

impl LineMod_ModalityTrait for Ptr<LineMod_ColorGradient>

fn as_raw_mut_LineMod_Modality(&mut self) -> *mut c_void

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

impl LineMod_ModalityTrait for Ptr<LineMod_DepthNormal>

fn as_raw_mut_LineMod_Modality(&mut self) -> *mut c_void

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

impl LineMod_ModalityTrait for Ptr<LineMod_Modality>

fn as_raw_mut_LineMod_Modality(&mut self) -> *mut c_void

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

impl LineMod_ModalityTraitConst for Ptr<LineMod_ColorGradient>

fn as_raw_LineMod_Modality(&self) -> *const c_void

fn process( &self, src: &impl MatTraitConst, mask: &impl MatTraitConst ) -> Result<Ptr<LineMod_QuantizedPyramid>>

\brief Form a quantized image pyramid from a source image.

fn process_def( &self, src: &impl MatTraitConst ) -> Result<Ptr<LineMod_QuantizedPyramid>>

\brief Form a quantized image pyramid from a source image.

fn name(&self) -> Result<String>

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

impl LineMod_ModalityTraitConst for Ptr<LineMod_DepthNormal>

fn as_raw_LineMod_Modality(&self) -> *const c_void

fn process( &self, src: &impl MatTraitConst, mask: &impl MatTraitConst ) -> Result<Ptr<LineMod_QuantizedPyramid>>

\brief Form a quantized image pyramid from a source image.

fn process_def( &self, src: &impl MatTraitConst ) -> Result<Ptr<LineMod_QuantizedPyramid>>

\brief Form a quantized image pyramid from a source image.

fn name(&self) -> Result<String>

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

impl LineMod_ModalityTraitConst for Ptr<LineMod_Modality>

fn as_raw_LineMod_Modality(&self) -> *const c_void

fn process( &self, src: &impl MatTraitConst, mask: &impl MatTraitConst ) -> Result<Ptr<LineMod_QuantizedPyramid>>

\brief Form a quantized image pyramid from a source image.

fn process_def( &self, src: &impl MatTraitConst ) -> Result<Ptr<LineMod_QuantizedPyramid>>

\brief Form a quantized image pyramid from a source image.

fn name(&self) -> Result<String>

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

impl LineMod_QuantizedPyramidTrait for Ptr<LineMod_QuantizedPyramid>

fn as_raw_mut_LineMod_QuantizedPyramid(&mut self) -> *mut c_void

fn pyr_down(&mut self) -> Result<()>

\brief Go to the next pyramid level.

impl LineMod_QuantizedPyramidTraitConst for Ptr<LineMod_QuantizedPyramid>

fn as_raw_LineMod_QuantizedPyramid(&self) -> *const c_void

fn quantize(&self, dst: &mut impl MatTrait) -> Result<()>

\brief Compute quantized image at current pyramid level for online detection.

fn extract_template( &self, templ: &mut impl LineMod_TemplateTrait ) -> Result<bool>

\brief Extract most discriminant features at current pyramid level to form a new template.

impl LineSegmentDetectorTrait for Ptr<LineSegmentDetector>

fn as_raw_mut_LineSegmentDetector(&mut self) -> *mut c_void

fn detect( &mut self, image: &impl ToInputArray, lines: &mut impl ToOutputArray, width: &mut impl ToOutputArray, prec: &mut impl ToOutputArray, nfa: &mut impl ToOutputArray ) -> Result<()>

Finds lines in the input image.

fn detect_def( &mut self, image: &impl ToInputArray, lines: &mut impl ToOutputArray ) -> Result<()>

Finds lines in the input image.

fn draw_segments( &mut self, image: &mut impl ToInputOutputArray, lines: &impl ToInputArray ) -> Result<()>

Draws the line segments on a given image.

fn compare_segments( &mut self, size: Size, lines1: &impl ToInputArray, lines2: &impl ToInputArray, image: &mut impl ToInputOutputArray ) -> Result<i32>

Draws two groups of lines in blue and red, counting the non overlapping (mismatching) pixels.

fn compare_segments_def( &mut self, size: Size, lines1: &impl ToInputArray, lines2: &impl ToInputArray ) -> Result<i32>

Draws two groups of lines in blue and red, counting the non overlapping (mismatching) pixels.

impl LineSegmentDetectorTraitConst for Ptr<LineSegmentDetector>

fn as_raw_LineSegmentDetector(&self) -> *const c_void

impl LinearIndexParamsTrait for Ptr<LinearIndexParams>

fn as_raw_mut_LinearIndexParams(&mut self) -> *mut c_void

impl LinearIndexParamsTraitConst for Ptr<LinearIndexParams>

fn as_raw_LinearIndexParams(&self) -> *const c_void

impl LogLayerTrait for Ptr<LogLayer>

fn as_raw_mut_LogLayer(&mut self) -> *mut c_void

impl LogLayerTraitConst for Ptr<LogLayer>

fn as_raw_LogLayer(&self) -> *const c_void

impl LogToStdoutTrait for Ptr<LogToStdout>

fn as_raw_mut_LogToStdout(&mut self) -> *mut c_void

fn print(&mut self, format: &str) -> Result<()>

impl LogToStdoutTraitConst for Ptr<LogToStdout>

fn as_raw_LogToStdout(&self) -> *const c_void

impl LogisticRegressionTrait for Ptr<LogisticRegression>

fn as_raw_mut_LogisticRegression(&mut self) -> *mut c_void

fn set_learning_rate(&mut self, val: f64) -> Result<()>

Learning rate.

fn set_iterations(&mut self, val: i32) -> Result<()>

Number of iterations.

fn set_regularization(&mut self, val: i32) -> Result<()>

Kind of regularization to be applied. See LogisticRegression::RegKinds.

fn set_train_method(&mut self, val: i32) -> Result<()>

Kind of training method used. See LogisticRegression::Methods.

fn set_mini_batch_size(&mut self, val: i32) -> Result<()>

Specifies the number of training samples taken in each step of Mini-Batch Gradient Descent. Will only be used if using LogisticRegression::MINI_BATCH training algorithm. It has to take values less than the total number of training samples.

fn set_term_criteria(&mut self, val: TermCriteria) -> Result<()>

Termination criteria of the algorithm.

impl LogisticRegressionTraitConst for Ptr<LogisticRegression>

fn as_raw_LogisticRegression(&self) -> *const c_void

fn get_learning_rate(&self) -> Result<f64>

Learning rate.

fn get_iterations(&self) -> Result<i32>

Number of iterations.

fn get_regularization(&self) -> Result<i32>

Kind of regularization to be applied. See LogisticRegression::RegKinds.

fn get_train_method(&self) -> Result<i32>

Kind of training method used. See LogisticRegression::Methods.

fn get_mini_batch_size(&self) -> Result<i32>

Specifies the number of training samples taken in each step of Mini-Batch Gradient Descent. Will only be used if using LogisticRegression::MINI_BATCH training algorithm. It has to take values less than the total number of training samples.

fn get_term_criteria(&self) -> Result<TermCriteria>

Termination criteria of the algorithm.

fn predict( &self, samples: &impl ToInputArray, results: &mut impl ToOutputArray, flags: i32 ) -> Result<f32>

Predicts responses for input samples and returns a float type.

fn predict_def(&self, samples: &impl ToInputArray) -> Result<f32>

Predicts responses for input samples and returns a float type.

fn get_learnt_thetas(&self) -> Result<Mat>

This function returns the trained parameters arranged across rows.

impl LookUpTableTrait for Ptr<LookUpTable>

fn as_raw_mut_LookUpTable(&mut self) -> *mut c_void

fn transform( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Transforms the source matrix into the destination matrix using the given look-up table: dst(I) = lut(src(I)) .

fn transform_def( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Transforms the source matrix into the destination matrix using the given look-up table: dst(I) = lut(src(I)) .

impl LookUpTableTraitConst for Ptr<LookUpTable>

fn as_raw_LookUpTable(&self) -> *const c_void

impl LpMotionStabilizerTrait for Ptr<LpMotionStabilizer>

fn as_raw_mut_LpMotionStabilizer(&mut self) -> *mut c_void

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn set_frame_size(&mut self, val: Size) -> Result<()>

fn set_trim_ratio(&mut self, val: f32) -> Result<()>

fn set_weight1(&mut self, val: f32) -> Result<()>

fn set_weight2(&mut self, val: f32) -> Result<()>

fn set_weight3(&mut self, val: f32) -> Result<()>

fn set_weight4(&mut self, val: f32) -> Result<()>

fn stabilize( &mut self, size: i32, motions: &Vector<Mat>, range: &impl RangeTraitConst, stabilization_motions: &mut impl MatTrait ) -> Result<()>

impl LpMotionStabilizerTraitConst for Ptr<LpMotionStabilizer>

fn as_raw_LpMotionStabilizer(&self) -> *const c_void

fn motion_model(&self) -> Result<MotionModel>

fn frame_size(&self) -> Result<Size>

fn trim_ratio(&self) -> Result<f32>

fn weight1(&self) -> Result<f32>

fn weight2(&self) -> Result<f32>

fn weight3(&self) -> Result<f32>

fn weight4(&self) -> Result<f32>

impl LshIndexParamsTrait for Ptr<LshIndexParams>

fn as_raw_mut_LshIndexParams(&mut self) -> *mut c_void

impl LshIndexParamsTraitConst for Ptr<LshIndexParams>

fn as_raw_LshIndexParams(&self) -> *const c_void

impl MACETrait for Ptr<MACE>

fn as_raw_mut_MACE(&mut self) -> *mut c_void

fn salt(&mut self, passphrase: &str) -> Result<()>

optionally encrypt images with random convolution

fn train(&mut self, images: &impl ToInputArray) -> Result<()>

train it on positive features compute the mace filter: h = D(-1) * X * (X(+) * D(-1) * X)(-1) * C also calculate a minimal threshold for this class, the smallest self-similarity from the train images

impl MACETraitConst for Ptr<MACE>

fn as_raw_MACE(&self) -> *const c_void

fn same(&self, query: &impl ToInputArray) -> Result<bool>

correlate query img and threshold to min class value

impl MCC_CCheckerDetectorTrait for Ptr<MCC_CCheckerDetector>

fn as_raw_mut_MCC_CCheckerDetector(&mut self) -> *mut c_void

fn set_net(&mut self, net: impl NetTrait) -> Result<bool>

\brief Set the net which will be used to find the approximate bounding boxes for the color charts.

fn process_with_roi( &mut self, image: &impl ToInputArray, chart_type: MCC_TYPECHART, regions_of_interest: &Vector<Rect>, nc: i32, use_net: bool, params: &Ptr<MCC_DetectorParameters> ) -> Result<bool>

\brief Find the ColorCharts in the given image.

fn process_with_roi_def( &mut self, image: &impl ToInputArray, chart_type: MCC_TYPECHART, regions_of_interest: &Vector<Rect> ) -> Result<bool>

\brief Find the ColorCharts in the given image.

fn process( &mut self, image: &impl ToInputArray, chart_type: MCC_TYPECHART, nc: i32, use_net: bool, params: &Ptr<MCC_DetectorParameters> ) -> Result<bool>

\brief Find the ColorCharts in the given image.

fn process_def( &mut self, image: &impl ToInputArray, chart_type: MCC_TYPECHART ) -> Result<bool>

\brief Find the ColorCharts in the given image.

fn get_best_color_checker(&mut self) -> Result<Ptr<MCC_CChecker>>

\brief Get the best color checker. By the best it means the one detected with the highest confidence. \return checker A single colorchecker, if atleast one colorchecker was detected, ‘nullptr’ otherwise.

fn get_list_color_checker(&mut self) -> Result<Vector<Ptr<MCC_CChecker>>>

\brief Get the list of all detected colorcheckers \return checkers vector of colorcheckers

impl MCC_CCheckerDetectorTraitConst for Ptr<MCC_CCheckerDetector>

fn as_raw_MCC_CCheckerDetector(&self) -> *const c_void

impl MCC_CCheckerDrawTrait for Ptr<MCC_CCheckerDraw>

fn as_raw_mut_MCC_CCheckerDraw(&mut self) -> *mut c_void

fn draw(&mut self, img: &mut impl ToInputOutputArray) -> Result<()>

\brief Draws the checker to the given image. \param img image in color space BGR \return void

impl MCC_CCheckerDrawTraitConst for Ptr<MCC_CCheckerDraw>

fn as_raw_MCC_CCheckerDraw(&self) -> *const c_void

impl MCC_CCheckerTrait for Ptr<MCC_CChecker>

fn as_raw_mut_MCC_CChecker(&mut self) -> *mut c_void

fn set_target(&mut self, _target: MCC_TYPECHART) -> Result<()>

fn set_box(&mut self, _box: Vector<Point2f>) -> Result<()>

fn set_charts_rgb(&mut self, _charts_rgb: impl MatTrait) -> Result<()>

fn set_charts_y_cb_cr(&mut self, _charts_y_cb_cr: impl MatTrait) -> Result<()>

fn set_cost(&mut self, _cost: f32) -> Result<()>

fn set_center(&mut self, _center: Point2f) -> Result<()>

fn get_target(&mut self) -> Result<MCC_TYPECHART>

fn get_box(&mut self) -> Result<Vector<Point2f>>

fn get_charts_rgb(&mut self) -> Result<Mat>

fn get_charts_y_cb_cr(&mut self) -> Result<Mat>

fn get_cost(&mut self) -> Result<f32>

fn get_center(&mut self) -> Result<Point2f>

impl MCC_CCheckerTraitConst for Ptr<MCC_CChecker>

fn as_raw_MCC_CChecker(&self) -> *const c_void

impl MCC_DetectorParametersTrait for Ptr<MCC_DetectorParameters>

fn as_raw_mut_MCC_DetectorParameters(&mut self) -> *mut c_void

fn set_adaptive_thresh_win_size_min(&mut self, val: i32)

fn set_adaptive_thresh_win_size_max(&mut self, val: i32)

fn set_adaptive_thresh_win_size_step(&mut self, val: i32)

fn set_adaptive_thresh_constant(&mut self, val: f64)

fn set_min_contours_area_rate(&mut self, val: f64)

fn set_min_contours_area(&mut self, val: f64)

fn set_confidence_threshold(&mut self, val: f64)

fn set_min_contour_solidity(&mut self, val: f64)

fn set_find_candidates_approx_poly_dp_eps_multiplier(&mut self, val: f64)

fn set_border_width(&mut self, val: i32)

fn set_b0factor(&mut self, val: f32)

fn set_max_error(&mut self, val: f32)

fn set_min_contour_points_allowed(&mut self, val: i32)

fn set_min_contour_length_allowed(&mut self, val: i32)

fn set_min_inter_contour_distance(&mut self, val: i32)

fn set_min_inter_checker_distance(&mut self, val: i32)

fn set_min_image_size(&mut self, val: i32)

fn set_min_group_size(&mut self, val: u32)

impl MCC_DetectorParametersTraitConst for Ptr<MCC_DetectorParameters>

fn as_raw_MCC_DetectorParameters(&self) -> *const c_void

fn adaptive_thresh_win_size_min(&self) -> i32

fn adaptive_thresh_win_size_max(&self) -> i32

fn adaptive_thresh_win_size_step(&self) -> i32

fn adaptive_thresh_constant(&self) -> f64

fn min_contours_area_rate(&self) -> f64

fn min_contours_area(&self) -> f64

fn confidence_threshold(&self) -> f64

fn min_contour_solidity(&self) -> f64

fn find_candidates_approx_poly_dp_eps_multiplier(&self) -> f64

fn border_width(&self) -> i32

fn b0factor(&self) -> f32

fn max_error(&self) -> f32

fn min_contour_points_allowed(&self) -> i32

fn min_contour_length_allowed(&self) -> i32

fn min_inter_contour_distance(&self) -> i32

fn min_inter_checker_distance(&self) -> i32

fn min_image_size(&self) -> i32

fn min_group_size(&self) -> u32

impl MSDDetectorTrait for Ptr<MSDDetector>

fn as_raw_mut_MSDDetector(&mut self) -> *mut c_void

fn set_patch_radius(&mut self, patch_radius: i32) -> Result<()>

fn set_search_area_radius(&mut self, use_orientation: i32) -> Result<()>

fn set_nms_radius(&mut self, nms_radius: i32) -> Result<()>

fn set_nms_scale_radius(&mut self, nms_scale_radius: i32) -> Result<()>

fn set_th_saliency(&mut self, th_saliency: f32) -> Result<()>

fn set_knn(&mut self, k_nn: i32) -> Result<()>

fn set_scale_factor(&mut self, scale_factor: f32) -> Result<()>

fn set_n_scales(&mut self, use_orientation: i32) -> Result<()>

fn set_compute_orientation(&mut self, compute_orientation: bool) -> Result<()>

impl MSDDetectorTraitConst for Ptr<MSDDetector>

fn as_raw_MSDDetector(&self) -> *const c_void

fn get_patch_radius(&self) -> Result<i32>

fn get_search_area_radius(&self) -> Result<i32>

fn get_nms_radius(&self) -> Result<i32>

fn get_nms_scale_radius(&self) -> Result<i32>

fn get_th_saliency(&self) -> Result<f32>

fn get_knn(&self) -> Result<i32>

fn get_scale_factor(&self) -> Result<f32>

fn get_n_scales(&self) -> Result<i32>

fn get_compute_orientation(&self) -> Result<bool>

fn get_default_name(&self) -> Result<String>

impl MSERTrait for Ptr<MSER>

fn as_raw_mut_MSER(&mut self) -> *mut c_void

fn detect_regions( &mut self, image: &impl ToInputArray, msers: &mut Vector<Vector<Point>>, bboxes: &mut Vector<Rect> ) -> Result<()>

Detect %MSER regions

fn set_delta(&mut self, delta: i32) -> Result<()>

fn set_min_area(&mut self, min_area: i32) -> Result<()>

fn set_max_area(&mut self, max_area: i32) -> Result<()>

fn set_max_variation(&mut self, max_variation: f64) -> Result<()>

fn set_min_diversity(&mut self, min_diversity: f64) -> Result<()>

fn set_max_evolution(&mut self, max_evolution: i32) -> Result<()>

fn set_area_threshold(&mut self, area_threshold: f64) -> Result<()>

fn set_min_margin(&mut self, min_margin: f64) -> Result<()>

fn set_edge_blur_size(&mut self, edge_blur_size: i32) -> Result<()>

fn set_pass2_only(&mut self, f: bool) -> Result<()>

impl MSERTraitConst for Ptr<MSER>

fn as_raw_MSER(&self) -> *const c_void

fn get_delta(&self) -> Result<i32>

fn get_min_area(&self) -> Result<i32>

fn get_max_area(&self) -> Result<i32>

fn get_max_variation(&self) -> Result<f64>

fn get_min_diversity(&self) -> Result<f64>

fn get_max_evolution(&self) -> Result<i32>

fn get_area_threshold(&self) -> Result<f64>

fn get_min_margin(&self) -> Result<f64>

fn get_edge_blur_size(&self) -> Result<i32>

fn get_pass2_only(&self) -> Result<bool>

fn get_default_name(&self) -> Result<String>

impl MVNLayerTrait for Ptr<MVNLayer>

fn as_raw_mut_MVNLayer(&mut self) -> *mut c_void

fn set_eps(&mut self, val: f32)

fn set_norm_variance(&mut self, val: bool)

fn set_across_channels(&mut self, val: bool)

impl MVNLayerTraitConst for Ptr<MVNLayer>

fn as_raw_MVNLayer(&self) -> *const c_void

fn eps(&self) -> f32

fn norm_variance(&self) -> bool

fn across_channels(&self) -> bool

impl MarrHildrethHashTrait for Ptr<MarrHildrethHash>

fn as_raw_mut_MarrHildrethHash(&mut self) -> *mut c_void

fn set_kernel_param(&mut self, alpha: f32, scale: f32) -> Result<()>

Set Mh kernel parameters

impl MarrHildrethHashTraitConst for Ptr<MarrHildrethHash>

fn as_raw_MarrHildrethHash(&self) -> *const c_void

fn get_alpha(&self) -> Result<f32>

self explain

fn get_scale(&self) -> Result<f32>

self explain

impl MaskFrameSourceTrait for Ptr<MaskFrameSource>

fn as_raw_mut_MaskFrameSource(&mut self) -> *mut c_void

fn reset(&mut self) -> Result<()>

fn next_frame(&mut self) -> Result<Mat>

impl MaskFrameSourceTraitConst for Ptr<MaskFrameSource>

fn as_raw_MaskFrameSource(&self) -> *const c_void

impl MatMulLayerTrait for Ptr<MatMulLayer>

fn as_raw_mut_MatMulLayer(&mut self) -> *mut c_void

impl MatMulLayerTraitConst for Ptr<MatMulLayer>

fn as_raw_MatMulLayer(&self) -> *const c_void

impl MaxUnpoolLayerTrait for Ptr<MaxUnpoolLayer>

fn as_raw_mut_MaxUnpoolLayer(&mut self) -> *mut c_void

fn set_pool_kernel(&mut self, val: Size)

fn set_pool_pad(&mut self, val: Size)

fn set_pool_stride(&mut self, val: Size)

impl MaxUnpoolLayerTraitConst for Ptr<MaxUnpoolLayer>

fn as_raw_MaxUnpoolLayer(&self) -> *const c_void

fn pool_kernel(&self) -> Size

fn pool_pad(&self) -> Size

fn pool_stride(&self) -> Size

impl MercatorWarperTrait for Ptr<MercatorWarper>

fn as_raw_mut_MercatorWarper(&mut self) -> *mut c_void

impl MercatorWarperTraitConst for Ptr<MercatorWarper>

fn as_raw_MercatorWarper(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl MergeDebevecTrait for Ptr<MergeDebevec>

fn as_raw_mut_MergeDebevec(&mut self) -> *mut c_void

fn process_with_response( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, times: &impl ToInputArray, response: &impl ToInputArray ) -> Result<()>

fn process( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, times: &impl ToInputArray ) -> Result<()>

impl MergeDebevecTraitConst for Ptr<MergeDebevec>

fn as_raw_MergeDebevec(&self) -> *const c_void

impl MergeExposuresTrait for Ptr<MergeDebevec>

fn as_raw_mut_MergeExposures(&mut self) -> *mut c_void

fn process( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, times: &impl ToInputArray, response: &impl ToInputArray ) -> Result<()>

Merges images.

impl MergeExposuresTrait for Ptr<MergeExposures>

fn as_raw_mut_MergeExposures(&mut self) -> *mut c_void

fn process( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, times: &impl ToInputArray, response: &impl ToInputArray ) -> Result<()>

Merges images.

impl MergeExposuresTrait for Ptr<MergeMertens>

fn as_raw_mut_MergeExposures(&mut self) -> *mut c_void

fn process( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, times: &impl ToInputArray, response: &impl ToInputArray ) -> Result<()>

Merges images.

impl MergeExposuresTrait for Ptr<MergeRobertson>

fn as_raw_mut_MergeExposures(&mut self) -> *mut c_void

fn process( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, times: &impl ToInputArray, response: &impl ToInputArray ) -> Result<()>

Merges images.

impl MergeExposuresTraitConst for Ptr<MergeDebevec>

fn as_raw_MergeExposures(&self) -> *const c_void

impl MergeExposuresTraitConst for Ptr<MergeExposures>

fn as_raw_MergeExposures(&self) -> *const c_void

impl MergeExposuresTraitConst for Ptr<MergeMertens>

fn as_raw_MergeExposures(&self) -> *const c_void

impl MergeExposuresTraitConst for Ptr<MergeRobertson>

fn as_raw_MergeExposures(&self) -> *const c_void

impl MergeMertensTrait for Ptr<MergeMertens>

fn as_raw_mut_MergeMertens(&mut self) -> *mut c_void

fn process_with_response( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, times: &impl ToInputArray, response: &impl ToInputArray ) -> Result<()>

fn process( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Short version of process, that doesn’t take extra arguments.

fn set_contrast_weight(&mut self, contrast_weiht: f32) -> Result<()>

fn set_saturation_weight(&mut self, saturation_weight: f32) -> Result<()>

fn set_exposure_weight(&mut self, exposure_weight: f32) -> Result<()>

impl MergeMertensTraitConst for Ptr<MergeMertens>

fn as_raw_MergeMertens(&self) -> *const c_void

fn get_contrast_weight(&self) -> Result<f32>

fn get_saturation_weight(&self) -> Result<f32>

fn get_exposure_weight(&self) -> Result<f32>

impl MergeRobertsonTrait for Ptr<MergeRobertson>

fn as_raw_mut_MergeRobertson(&mut self) -> *mut c_void

fn process_with_response( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, times: &impl ToInputArray, response: &impl ToInputArray ) -> Result<()>

fn process( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, times: &impl ToInputArray ) -> Result<()>

impl MergeRobertsonTraitConst for Ptr<MergeRobertson>

fn as_raw_MergeRobertson(&self) -> *const c_void

impl MinProblemSolverTrait for Ptr<ConjGradSolver>

fn as_raw_mut_MinProblemSolver(&mut self) -> *mut c_void

fn set_function(&mut self, f: &Ptr<MinProblemSolver_Function>) -> Result<()>

Setter for the optimized function.

fn set_term_criteria(&mut self, termcrit: TermCriteria) -> Result<()>

Set terminal criteria for solver.

fn minimize(&mut self, x: &mut impl ToInputOutputArray) -> Result<f64>

actually runs the algorithm and performs the minimization.

impl MinProblemSolverTrait for Ptr<DownhillSolver>

fn as_raw_mut_MinProblemSolver(&mut self) -> *mut c_void

fn set_function(&mut self, f: &Ptr<MinProblemSolver_Function>) -> Result<()>

Setter for the optimized function.

fn set_term_criteria(&mut self, termcrit: TermCriteria) -> Result<()>

Set terminal criteria for solver.

fn minimize(&mut self, x: &mut impl ToInputOutputArray) -> Result<f64>

actually runs the algorithm and performs the minimization.

impl MinProblemSolverTrait for Ptr<MinProblemSolver>

fn as_raw_mut_MinProblemSolver(&mut self) -> *mut c_void

fn set_function(&mut self, f: &Ptr<MinProblemSolver_Function>) -> Result<()>

Setter for the optimized function.

fn set_term_criteria(&mut self, termcrit: TermCriteria) -> Result<()>

Set terminal criteria for solver.

fn minimize(&mut self, x: &mut impl ToInputOutputArray) -> Result<f64>

actually runs the algorithm and performs the minimization.

impl MinProblemSolverTraitConst for Ptr<ConjGradSolver>

fn as_raw_MinProblemSolver(&self) -> *const c_void

fn get_function(&self) -> Result<Ptr<MinProblemSolver_Function>>

Getter for the optimized function.

fn get_term_criteria(&self) -> Result<TermCriteria>

Getter for the previously set terminal criteria for this algorithm.

impl MinProblemSolverTraitConst for Ptr<DownhillSolver>

fn as_raw_MinProblemSolver(&self) -> *const c_void

fn get_function(&self) -> Result<Ptr<MinProblemSolver_Function>>

Getter for the optimized function.

fn get_term_criteria(&self) -> Result<TermCriteria>

Getter for the previously set terminal criteria for this algorithm.

impl MinProblemSolverTraitConst for Ptr<MinProblemSolver>

fn as_raw_MinProblemSolver(&self) -> *const c_void

fn get_function(&self) -> Result<Ptr<MinProblemSolver_Function>>

Getter for the optimized function.

fn get_term_criteria(&self) -> Result<TermCriteria>

Getter for the previously set terminal criteria for this algorithm.

impl MinProblemSolver_FunctionTrait for Ptr<MinProblemSolver_Function>

fn as_raw_mut_MinProblemSolver_Function(&mut self) -> *mut c_void

fn get_gradient(&mut self, x: &f64, grad: &mut f64) -> Result<()>

impl MinProblemSolver_FunctionTraitConst for Ptr<MinProblemSolver_Function>

fn as_raw_MinProblemSolver_Function(&self) -> *const c_void

fn get_dims(&self) -> Result<i32>

fn get_gradient_eps(&self) -> Result<f64>

fn calc(&self, x: &f64) -> Result<f64>

impl MishLayerTrait for Ptr<MishLayer>

fn as_raw_mut_MishLayer(&mut self) -> *mut c_void

impl MishLayerTraitConst for Ptr<MishLayer>

fn as_raw_MishLayer(&self) -> *const c_void

impl MoreAccurateMotionWobbleSuppressorBaseTrait for Ptr<MoreAccurateMotionWobbleSuppressor>

fn as_raw_mut_MoreAccurateMotionWobbleSuppressorBase(&mut self) -> *mut c_void

fn set_period(&mut self, val: i32) -> Result<()>

impl MoreAccurateMotionWobbleSuppressorBaseTrait for Ptr<MoreAccurateMotionWobbleSuppressorBase>

fn as_raw_mut_MoreAccurateMotionWobbleSuppressorBase(&mut self) -> *mut c_void

fn set_period(&mut self, val: i32) -> Result<()>

impl MoreAccurateMotionWobbleSuppressorBaseTrait for Ptr<MoreAccurateMotionWobbleSuppressorGpu>

fn as_raw_mut_MoreAccurateMotionWobbleSuppressorBase(&mut self) -> *mut c_void

fn set_period(&mut self, val: i32) -> Result<()>

impl MoreAccurateMotionWobbleSuppressorBaseTraitConst for Ptr<MoreAccurateMotionWobbleSuppressor>

fn as_raw_MoreAccurateMotionWobbleSuppressorBase(&self) -> *const c_void

fn period(&self) -> Result<i32>

impl MoreAccurateMotionWobbleSuppressorBaseTraitConst for Ptr<MoreAccurateMotionWobbleSuppressorBase>

fn as_raw_MoreAccurateMotionWobbleSuppressorBase(&self) -> *const c_void

fn period(&self) -> Result<i32>

impl MoreAccurateMotionWobbleSuppressorBaseTraitConst for Ptr<MoreAccurateMotionWobbleSuppressorGpu>

fn as_raw_MoreAccurateMotionWobbleSuppressorBase(&self) -> *const c_void

fn period(&self) -> Result<i32>

impl MoreAccurateMotionWobbleSuppressorGpuTrait for Ptr<MoreAccurateMotionWobbleSuppressorGpu>

fn as_raw_mut_MoreAccurateMotionWobbleSuppressorGpu(&mut self) -> *mut c_void

fn suppress( &mut self, idx: i32, frame: &impl GpuMatTraitConst, result: &mut impl GpuMatTrait ) -> Result<()>

fn suppress_1( &mut self, idx: i32, frame: &impl MatTraitConst, result: &mut impl MatTrait ) -> Result<()>

impl MoreAccurateMotionWobbleSuppressorGpuTraitConst for Ptr<MoreAccurateMotionWobbleSuppressorGpu>

fn as_raw_MoreAccurateMotionWobbleSuppressorGpu(&self) -> *const c_void

impl MoreAccurateMotionWobbleSuppressorTrait for Ptr<MoreAccurateMotionWobbleSuppressor>

fn as_raw_mut_MoreAccurateMotionWobbleSuppressor(&mut self) -> *mut c_void

fn suppress( &mut self, idx: i32, frame: &impl MatTraitConst, result: &mut impl MatTrait ) -> Result<()>

impl MoreAccurateMotionWobbleSuppressorTraitConst for Ptr<MoreAccurateMotionWobbleSuppressor>

fn as_raw_MoreAccurateMotionWobbleSuppressor(&self) -> *const c_void

impl MotionEstimatorBaseTrait for Ptr<MotionEstimatorBase>

fn as_raw_mut_MotionEstimatorBase(&mut self) -> *mut c_void

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

Sets motion model.

fn estimate( &mut self, points0: &impl ToInputArray, points1: &impl ToInputArray, ok: &mut bool ) -> Result<Mat>

Estimates global motion between two 2D point clouds.

fn estimate_def( &mut self, points0: &impl ToInputArray, points1: &impl ToInputArray ) -> Result<Mat>

Estimates global motion between two 2D point clouds.

impl MotionEstimatorBaseTrait for Ptr<MotionEstimatorL1>

fn as_raw_mut_MotionEstimatorBase(&mut self) -> *mut c_void

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

Sets motion model.

fn estimate( &mut self, points0: &impl ToInputArray, points1: &impl ToInputArray, ok: &mut bool ) -> Result<Mat>

Estimates global motion between two 2D point clouds.

fn estimate_def( &mut self, points0: &impl ToInputArray, points1: &impl ToInputArray ) -> Result<Mat>

Estimates global motion between two 2D point clouds.

impl MotionEstimatorBaseTrait for Ptr<MotionEstimatorRansacL2>

fn as_raw_mut_MotionEstimatorBase(&mut self) -> *mut c_void

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

Sets motion model.

fn estimate( &mut self, points0: &impl ToInputArray, points1: &impl ToInputArray, ok: &mut bool ) -> Result<Mat>

Estimates global motion between two 2D point clouds.

fn estimate_def( &mut self, points0: &impl ToInputArray, points1: &impl ToInputArray ) -> Result<Mat>

Estimates global motion between two 2D point clouds.

impl MotionEstimatorBaseTraitConst for Ptr<MotionEstimatorBase>

fn as_raw_MotionEstimatorBase(&self) -> *const c_void

fn motion_model(&self) -> Result<MotionModel>

Returns

impl MotionEstimatorBaseTraitConst for Ptr<MotionEstimatorL1>

fn as_raw_MotionEstimatorBase(&self) -> *const c_void

fn motion_model(&self) -> Result<MotionModel>

Returns

impl MotionEstimatorBaseTraitConst for Ptr<MotionEstimatorRansacL2>

fn as_raw_MotionEstimatorBase(&self) -> *const c_void

fn motion_model(&self) -> Result<MotionModel>

Returns

impl MotionEstimatorL1Trait for Ptr<MotionEstimatorL1>

fn as_raw_mut_MotionEstimatorL1(&mut self) -> *mut c_void

fn estimate( &mut self, points0: &impl ToInputArray, points1: &impl ToInputArray, ok: &mut bool ) -> Result<Mat>

C++ default parameters

fn estimate_def( &mut self, points0: &impl ToInputArray, points1: &impl ToInputArray ) -> Result<Mat>

Note

impl MotionEstimatorL1TraitConst for Ptr<MotionEstimatorL1>

fn as_raw_MotionEstimatorL1(&self) -> *const c_void

impl MotionEstimatorRansacL2Trait for Ptr<MotionEstimatorRansacL2>

fn as_raw_mut_MotionEstimatorRansacL2(&mut self) -> *mut c_void

fn set_ransac_params(&mut self, val: &impl RansacParamsTraitConst) -> Result<()>

fn set_min_inlier_ratio(&mut self, val: f32) -> Result<()>

fn estimate( &mut self, points0: &impl ToInputArray, points1: &impl ToInputArray, ok: &mut bool ) -> Result<Mat>

C++ default parameters

fn estimate_def( &mut self, points0: &impl ToInputArray, points1: &impl ToInputArray ) -> Result<Mat>

Note

impl MotionEstimatorRansacL2TraitConst for Ptr<MotionEstimatorRansacL2>

fn as_raw_MotionEstimatorRansacL2(&self) -> *const c_void

fn ransac_params(&self) -> Result<RansacParams>

fn min_inlier_ratio(&self) -> Result<f32>

impl MotionFilterBaseTrait for Ptr<GaussianMotionFilter>

fn as_raw_mut_MotionFilterBase(&mut self) -> *mut c_void

fn stabilize( &mut self, idx: i32, motions: &Vector<Mat>, range: &impl RangeTraitConst ) -> Result<Mat>

fn stabilize_1( &mut self, size: i32, motions: &Vector<Mat>, range: &impl RangeTraitConst, stabilization_motions: &mut impl MatTrait ) -> Result<()>

impl MotionFilterBaseTrait for Ptr<MotionFilterBase>

fn as_raw_mut_MotionFilterBase(&mut self) -> *mut c_void

fn stabilize( &mut self, idx: i32, motions: &Vector<Mat>, range: &impl RangeTraitConst ) -> Result<Mat>

fn stabilize_1( &mut self, size: i32, motions: &Vector<Mat>, range: &impl RangeTraitConst, stabilization_motions: &mut impl MatTrait ) -> Result<()>

impl MotionFilterBaseTraitConst for Ptr<GaussianMotionFilter>

fn as_raw_MotionFilterBase(&self) -> *const c_void

impl MotionFilterBaseTraitConst for Ptr<MotionFilterBase>

fn as_raw_MotionFilterBase(&self) -> *const c_void

impl MotionInpainterTrait for Ptr<MotionInpainter>

fn as_raw_mut_MotionInpainter(&mut self) -> *mut c_void

fn set_opt_flow_estimator( &mut self, val: Ptr<IDenseOptFlowEstimator> ) -> Result<()>

fn set_flow_error_threshold(&mut self, val: f32) -> Result<()>

fn set_dist_threshold(&mut self, val: f32) -> Result<()>

fn set_border_mode(&mut self, val: i32) -> Result<()>

fn inpaint( &mut self, idx: i32, frame: &mut impl MatTrait, mask: &mut impl MatTrait ) -> Result<()>

impl MotionInpainterTraitConst for Ptr<MotionInpainter>

fn as_raw_MotionInpainter(&self) -> *const c_void

fn opt_flow_estimator(&self) -> Result<Ptr<IDenseOptFlowEstimator>>

fn flow_error_threshold(&self) -> Result<f32>

fn dist_thresh(&self) -> Result<f32>

fn border_mode(&self) -> Result<i32>

impl MotionSaliencyBinWangApr2014Trait for Ptr<MotionSaliencyBinWangApr2014>

fn as_raw_mut_MotionSaliencyBinWangApr2014(&mut self) -> *mut c_void

fn compute_saliency( &mut self, image: &impl ToInputArray, saliency_map: &mut impl ToOutputArray ) -> Result<bool>

fn set_imagesize(&mut self, w: i32, h: i32) -> Result<()>

This is a utility function that allows to set the correct size (taken from the input image) in the corresponding variables that will be used to size the data structures of the algorithm.

fn init(&mut self) -> Result<bool>

This function allows the correct initialization of all data structures that will be used by the algorithm.

fn set_image_width(&mut self, val: i32) -> Result<()>

fn set_image_height(&mut self, val: i32) -> Result<()>

impl MotionSaliencyBinWangApr2014TraitConst for Ptr<MotionSaliencyBinWangApr2014>

fn as_raw_MotionSaliencyBinWangApr2014(&self) -> *const c_void

fn get_image_width(&self) -> Result<i32>

fn get_image_height(&self) -> Result<i32>

impl MotionSaliencyTrait for Ptr<MotionSaliency>

fn as_raw_mut_MotionSaliency(&mut self) -> *mut c_void

impl MotionSaliencyTrait for Ptr<MotionSaliencyBinWangApr2014>

fn as_raw_mut_MotionSaliency(&mut self) -> *mut c_void

impl MotionSaliencyTraitConst for Ptr<MotionSaliency>

fn as_raw_MotionSaliency(&self) -> *const c_void

impl MotionSaliencyTraitConst for Ptr<MotionSaliencyBinWangApr2014>

fn as_raw_MotionSaliency(&self) -> *const c_void

impl MotionStabilizationPipelineTrait for Ptr<MotionStabilizationPipeline>

fn as_raw_mut_MotionStabilizationPipeline(&mut self) -> *mut c_void

fn push_back(&mut self, stabilizer: Ptr<IMotionStabilizer>) -> Result<()>

fn stabilize( &mut self, size: i32, motions: &Vector<Mat>, range: &impl RangeTraitConst, stabilization_motions: &mut impl MatTrait ) -> Result<()>

impl MotionStabilizationPipelineTraitConst for Ptr<MotionStabilizationPipeline>

fn as_raw_MotionStabilizationPipeline(&self) -> *const c_void

fn empty(&self) -> Result<bool>

impl NaryEltwiseLayerTrait for Ptr<NaryEltwiseLayer>

fn as_raw_mut_NaryEltwiseLayer(&mut self) -> *mut c_void

impl NaryEltwiseLayerTraitConst for Ptr<NaryEltwiseLayer>

fn as_raw_NaryEltwiseLayer(&self) -> *const c_void

impl NormHistogramCostExtractorTrait for Ptr<NormHistogramCostExtractor>

fn as_raw_mut_NormHistogramCostExtractor(&mut self) -> *mut c_void

fn set_norm_flag(&mut self, flag: i32) -> Result<()>

impl NormHistogramCostExtractorTraitConst for Ptr<NormHistogramCostExtractor>

fn as_raw_NormHistogramCostExtractor(&self) -> *const c_void

fn get_norm_flag(&self) -> Result<i32>

impl NormalBayesClassifierTrait for Ptr<NormalBayesClassifier>

fn as_raw_mut_NormalBayesClassifier(&mut self) -> *mut c_void

impl NormalBayesClassifierTraitConst for Ptr<NormalBayesClassifier>

fn as_raw_NormalBayesClassifier(&self) -> *const c_void

fn predict_prob( &self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, output_probs: &mut impl ToOutputArray, flags: i32 ) -> Result<f32>

Predicts the response for sample(s).

fn predict_prob_def( &self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, output_probs: &mut impl ToOutputArray ) -> Result<f32>

Predicts the response for sample(s).

impl NormalizeBBoxLayerTrait for Ptr<NormalizeBBoxLayer>

fn as_raw_mut_NormalizeBBoxLayer(&mut self) -> *mut c_void

fn set_pnorm(&mut self, val: f32)

fn set_epsilon(&mut self, val: f32)

fn set_across_spatial(&mut self, val: bool)

impl NormalizeBBoxLayerTraitConst for Ptr<NormalizeBBoxLayer>

fn as_raw_NormalizeBBoxLayer(&self) -> *const c_void

fn pnorm(&self) -> f32

fn epsilon(&self) -> f32

fn across_spatial(&self) -> bool

impl NotLayerTrait for Ptr<NotLayer>

fn as_raw_mut_NotLayer(&mut self) -> *mut c_void

impl NotLayerTraitConst for Ptr<NotLayer>

fn as_raw_NotLayer(&self) -> *const c_void

impl NullDeblurerTrait for Ptr<NullDeblurer>

fn as_raw_mut_NullDeblurer(&mut self) -> *mut c_void

fn deblur( &mut self, unnamed: i32, unnamed_1: &mut impl MatTrait, unnamed_2: &impl RangeTraitConst ) -> Result<()>

impl NullDeblurerTraitConst for Ptr<NullDeblurer>

fn as_raw_NullDeblurer(&self) -> *const c_void

impl NullFrameSourceTrait for Ptr<NullFrameSource>

fn as_raw_mut_NullFrameSource(&mut self) -> *mut c_void

fn reset(&mut self) -> Result<()>

fn next_frame(&mut self) -> Result<Mat>

impl NullFrameSourceTraitConst for Ptr<NullFrameSource>

fn as_raw_NullFrameSource(&self) -> *const c_void

impl NullInpainterTrait for Ptr<NullInpainter>

fn as_raw_mut_NullInpainter(&mut self) -> *mut c_void

fn inpaint( &mut self, unnamed: i32, unnamed_1: &mut impl MatTrait, unnamed_2: &mut impl MatTrait ) -> Result<()>

impl NullInpainterTraitConst for Ptr<NullInpainter>

fn as_raw_NullInpainter(&self) -> *const c_void

impl NullLogTrait for Ptr<NullLog>

fn as_raw_mut_NullLog(&mut self) -> *mut c_void

fn print(&mut self, unnamed: &str) -> Result<()>

impl NullLogTraitConst for Ptr<NullLog>

fn as_raw_NullLog(&self) -> *const c_void

impl NullOutlierRejectorTrait for Ptr<NullOutlierRejector>

fn as_raw_mut_NullOutlierRejector(&mut self) -> *mut c_void

fn process( &mut self, frame_size: Size, points0: &impl ToInputArray, points1: &impl ToInputArray, mask: &mut impl ToOutputArray ) -> Result<()>

impl NullOutlierRejectorTraitConst for Ptr<NullOutlierRejector>

fn as_raw_NullOutlierRejector(&self) -> *const c_void

impl NullWobbleSuppressorTrait for Ptr<NullWobbleSuppressor>

fn as_raw_mut_NullWobbleSuppressor(&mut self) -> *mut c_void

fn suppress( &mut self, idx: i32, frame: &impl MatTraitConst, result: &mut impl MatTrait ) -> Result<()>

impl NullWobbleSuppressorTraitConst for Ptr<NullWobbleSuppressor>

fn as_raw_NullWobbleSuppressor(&self) -> *const c_void

impl OCRBeamSearchDecoderTrait for Ptr<OCRBeamSearchDecoder>

fn as_raw_mut_OCRBeamSearchDecoder(&mut self) -> *mut c_void

fn run_multiple( &mut self, image: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

Recognize text using Beam Search.

fn run_multiple_def( &mut self, image: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Recognize text using Beam Search.

fn run_multiple_mask( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

C++ default parameters

fn run_multiple_mask_def( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Note

fn run( &mut self, image: &impl ToInputArray, min_confidence: i32, component_level: i32 ) -> Result<String>

C++ default parameters

fn run_def( &mut self, image: &impl ToInputArray, min_confidence: i32 ) -> Result<String>

Note

fn run_mask( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, min_confidence: i32, component_level: i32 ) -> Result<String>

C++ default parameters

fn run_mask_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, min_confidence: i32 ) -> Result<String>

Note

impl OCRBeamSearchDecoderTraitConst for Ptr<OCRBeamSearchDecoder>

fn as_raw_OCRBeamSearchDecoder(&self) -> *const c_void

impl OCRBeamSearchDecoder_ClassifierCallbackTrait for Ptr<OCRBeamSearchDecoder_ClassifierCallback>

fn as_raw_mut_OCRBeamSearchDecoder_ClassifierCallback(&mut self) -> *mut c_void

fn eval( &mut self, image: &impl ToInputArray, recognition_probabilities: &mut Vector<Vector<f64>>, oversegmentation: &mut Vector<i32> ) -> Result<()>

The character classifier must return a (ranked list of) class(es) id(’s)

fn get_window_size(&mut self) -> Result<i32>

fn get_step_size(&mut self) -> Result<i32>

impl OCRBeamSearchDecoder_ClassifierCallbackTraitConst for Ptr<OCRBeamSearchDecoder_ClassifierCallback>

fn as_raw_OCRBeamSearchDecoder_ClassifierCallback(&self) -> *const c_void

impl OCRHMMDecoderTrait for Ptr<OCRHMMDecoder>

fn as_raw_mut_OCRHMMDecoder(&mut self) -> *mut c_void

fn run_multiple( &mut self, image: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

Recognize text using HMM.

fn run_multiple_def( &mut self, image: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Recognize text using HMM.

fn run_multiple_mask( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

Recognize text using HMM.

fn run_multiple_mask_def( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Recognize text using HMM.

fn run( &mut self, image: &impl ToInputArray, min_confidence: i32, component_level: i32 ) -> Result<String>

C++ default parameters

fn run_def( &mut self, image: &impl ToInputArray, min_confidence: i32 ) -> Result<String>

Note

fn run_mask( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, min_confidence: i32, component_level: i32 ) -> Result<String>

C++ default parameters

fn run_mask_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, min_confidence: i32 ) -> Result<String>

Note

impl OCRHMMDecoderTraitConst for Ptr<OCRHMMDecoder>

fn as_raw_OCRHMMDecoder(&self) -> *const c_void

impl OCRHMMDecoder_ClassifierCallbackTrait for Ptr<OCRHMMDecoder_ClassifierCallback>

fn as_raw_mut_OCRHMMDecoder_ClassifierCallback(&mut self) -> *mut c_void

fn eval( &mut self, image: &impl ToInputArray, out_class: &mut Vector<i32>, out_confidence: &mut Vector<f64> ) -> Result<()>

The character classifier must return a (ranked list of) class(es) id(’s)

impl OCRHMMDecoder_ClassifierCallbackTraitConst for Ptr<OCRHMMDecoder_ClassifierCallback>

fn as_raw_OCRHMMDecoder_ClassifierCallback(&self) -> *const c_void

impl OCRHolisticWordRecognizerTrait for Ptr<OCRHolisticWordRecognizer>

fn as_raw_mut_OCRHolisticWordRecognizer(&mut self) -> *mut c_void

fn run( &mut self, image: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

C++ default parameters

fn run_def( &mut self, image: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Note

fn run_mask( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

Recognize text using a segmentation based word-spotting/classifier cnn.

fn run_mask_def( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Recognize text using a segmentation based word-spotting/classifier cnn.

impl OCRHolisticWordRecognizerTraitConst for Ptr<OCRHolisticWordRecognizer>

fn as_raw_OCRHolisticWordRecognizer(&self) -> *const c_void

impl OCRTesseractTrait for Ptr<OCRTesseract>

fn as_raw_mut_OCRTesseract(&mut self) -> *mut c_void

fn run_multiple( &mut self, image: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

Recognize text using the tesseract-ocr API.

fn run_multiple_def( &mut self, image: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Recognize text using the tesseract-ocr API.

fn run_multiple_mask( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String, component_rects: &mut Vector<Rect>, component_texts: &mut Vector<String>, component_confidences: &mut Vector<f32>, component_level: i32 ) -> Result<()>

C++ default parameters

fn run_multiple_mask_def( &mut self, image: &mut impl MatTrait, mask: &mut impl MatTrait, output_text: &mut String ) -> Result<()>

Note

fn run( &mut self, image: &impl ToInputArray, min_confidence: i32, component_level: i32 ) -> Result<String>

C++ default parameters

fn run_def( &mut self, image: &impl ToInputArray, min_confidence: i32 ) -> Result<String>

Note

fn run_mask( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, min_confidence: i32, component_level: i32 ) -> Result<String>

C++ default parameters

fn run_mask_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, min_confidence: i32 ) -> Result<String>

Note

fn set_white_list(&mut self, char_whitelist: &str) -> Result<()>

impl OCRTesseractTraitConst for Ptr<OCRTesseract>

fn as_raw_OCRTesseract(&self) -> *const c_void

impl ORBTrait for Ptr<ORB>

fn as_raw_mut_ORB(&mut self) -> *mut c_void

fn set_max_features(&mut self, max_features: i32) -> Result<()>

fn set_scale_factor(&mut self, scale_factor: f64) -> Result<()>

fn set_n_levels(&mut self, nlevels: i32) -> Result<()>

fn set_edge_threshold(&mut self, edge_threshold: i32) -> Result<()>

fn set_first_level(&mut self, first_level: i32) -> Result<()>

fn set_wta_k(&mut self, wta_k: i32) -> Result<()>

fn set_score_type(&mut self, score_type: ORB_ScoreType) -> Result<()>

fn set_patch_size(&mut self, patch_size: i32) -> Result<()>

fn set_fast_threshold(&mut self, fast_threshold: i32) -> Result<()>

impl ORBTraitConst for Ptr<ORB>

fn as_raw_ORB(&self) -> *const c_void

fn get_max_features(&self) -> Result<i32>

fn get_scale_factor(&self) -> Result<f64>

fn get_n_levels(&self) -> Result<i32>

fn get_edge_threshold(&self) -> Result<i32>

fn get_first_level(&self) -> Result<i32>

fn get_wta_k(&self) -> Result<i32>

fn get_score_type(&self) -> Result<ORB_ScoreType>

fn get_patch_size(&self) -> Result<i32>

fn get_fast_threshold(&self) -> Result<i32>

fn get_default_name(&self) -> Result<String>

impl ObjectnessBINGTrait for Ptr<ObjectnessBING>

fn as_raw_mut_ObjectnessBING(&mut self) -> *mut c_void

fn compute_saliency( &mut self, image: &impl ToInputArray, saliency_map: &mut impl ToOutputArray ) -> Result<bool>

fn read(&mut self) -> Result<()>

fn getobjectness_values(&mut self) -> Result<Vector<f32>>

Return the list of the rectangles’ objectness value,

fn set_training_path(&mut self, training_path: &str) -> Result<()>

This is a utility function that allows to set the correct path from which the algorithm will load the trained model.

fn set_bb_res_dir(&mut self, results_dir: &str) -> Result<()>

This is a utility function that allows to set an arbitrary path in which the algorithm will save the optional results

fn set_base(&mut self, val: f64) -> Result<()>

fn set_nss(&mut self, val: i32) -> Result<()>

fn set_w(&mut self, val: i32) -> Result<()>

impl ObjectnessBINGTraitConst for Ptr<ObjectnessBING>

fn as_raw_ObjectnessBING(&self) -> *const c_void

fn write(&self) -> Result<()>

fn get_base(&self) -> Result<f64>

fn get_nss(&self) -> Result<i32>

fn get_w(&self) -> Result<i32>

impl ObjectnessTrait for Ptr<Objectness>

fn as_raw_mut_Objectness(&mut self) -> *mut c_void

impl ObjectnessTrait for Ptr<ObjectnessBING>

fn as_raw_mut_Objectness(&mut self) -> *mut c_void

impl ObjectnessTraitConst for Ptr<Objectness>

fn as_raw_Objectness(&self) -> *const c_void

impl ObjectnessTraitConst for Ptr<ObjectnessBING>

fn as_raw_Objectness(&self) -> *const c_void

impl OdometryFrameTrait for Ptr<OdometryFrame>

fn as_raw_mut_OdometryFrame(&mut self) -> *mut c_void

fn set_pyramid_image(&mut self, val: Vector<Mat>)

fn set_pyramid_depth(&mut self, val: Vector<Mat>)

fn set_pyramid_mask(&mut self, val: Vector<Mat>)

fn set_pyramid_cloud(&mut self, val: Vector<Mat>)

fn set_pyramid_d_i_dx(&mut self, val: Vector<Mat>)

fn set_pyramid_d_i_dy(&mut self, val: Vector<Mat>)

fn set_pyramid_textured_mask(&mut self, val: Vector<Mat>)

fn set_pyramid_normals(&mut self, val: Vector<Mat>)

fn set_pyramid_normals_mask(&mut self, val: Vector<Mat>)

fn release(&mut self) -> Result<()>

fn release_pyramids(&mut self) -> Result<()>

impl OdometryFrameTraitConst for Ptr<OdometryFrame>

fn as_raw_OdometryFrame(&self) -> *const c_void

fn pyramid_image(&self) -> Vector<Mat>

fn pyramid_depth(&self) -> Vector<Mat>

fn pyramid_mask(&self) -> Vector<Mat>

fn pyramid_cloud(&self) -> Vector<Mat>

fn pyramid_d_i_dx(&self) -> Vector<Mat>

fn pyramid_d_i_dy(&self) -> Vector<Mat>

fn pyramid_textured_mask(&self) -> Vector<Mat>

fn pyramid_normals(&self) -> Vector<Mat>

fn pyramid_normals_mask(&self) -> Vector<Mat>

impl OdometryTrait for Ptr<FastICPOdometry>

fn as_raw_mut_Odometry(&mut self) -> *mut c_void

fn set_camera_matrix(&mut self, val: &impl MatTraitConst) -> Result<()>

See also

fn set_transform_type(&mut self, val: i32) -> Result<()>

See also

impl OdometryTrait for Ptr<ICPOdometry>

fn as_raw_mut_Odometry(&mut self) -> *mut c_void

fn set_camera_matrix(&mut self, val: &impl MatTraitConst) -> Result<()>

See also

fn set_transform_type(&mut self, val: i32) -> Result<()>

See also

impl OdometryTrait for Ptr<Odometry>

fn as_raw_mut_Odometry(&mut self) -> *mut c_void

fn set_camera_matrix(&mut self, val: &impl MatTraitConst) -> Result<()>

See also

fn set_transform_type(&mut self, val: i32) -> Result<()>

See also

impl OdometryTrait for Ptr<RgbdICPOdometry>

fn as_raw_mut_Odometry(&mut self) -> *mut c_void

fn set_camera_matrix(&mut self, val: &impl MatTraitConst) -> Result<()>

See also

fn set_transform_type(&mut self, val: i32) -> Result<()>

See also

impl OdometryTrait for Ptr<RgbdOdometry>

fn as_raw_mut_Odometry(&mut self) -> *mut c_void

fn set_camera_matrix(&mut self, val: &impl MatTraitConst) -> Result<()>

See also

fn set_transform_type(&mut self, val: i32) -> Result<()>

See also

impl OdometryTraitConst for Ptr<FastICPOdometry>

fn as_raw_Odometry(&self) -> *const c_void

fn compute( &self, src_image: &impl MatTraitConst, src_depth: &impl MatTraitConst, src_mask: &impl MatTraitConst, dst_image: &impl MatTraitConst, dst_depth: &impl MatTraitConst, dst_mask: &impl MatTraitConst, rt: &mut impl ToOutputArray, init_rt: &impl MatTraitConst ) -> Result<bool>

Method to compute a transformation from the source frame to the destination one. Some odometry algorithms do not used some data of frames (eg. ICP does not use images). In such case corresponding arguments can be set as empty Mat. The method returns true if all internal computations were possible (e.g. there were enough correspondences, system of equations has a solution, etc) and resulting transformation satisfies some test if it’s provided by the Odometry inheritor implementation (e.g. thresholds for maximum translation and rotation).

fn compute_def( &self, src_image: &impl MatTraitConst, src_depth: &impl MatTraitConst, src_mask: &impl MatTraitConst, dst_image: &impl MatTraitConst, dst_depth: &impl MatTraitConst, dst_mask: &impl MatTraitConst, rt: &mut impl ToOutputArray ) -> Result<bool>

Method to compute a transformation from the source frame to the destination one. Some odometry algorithms do not used some data of frames (eg. ICP does not use images). In such case corresponding arguments can be set as empty Mat. The method returns true if all internal computations were possible (e.g. there were enough correspondences, system of equations has a solution, etc) and resulting transformation satisfies some test if it’s provided by the Odometry inheritor implementation (e.g. thresholds for maximum translation and rotation).

fn compute2( &self, src_frame: &mut Ptr<OdometryFrame>, dst_frame: &mut Ptr<OdometryFrame>, rt: &mut impl ToOutputArray, init_rt: &impl MatTraitConst ) -> Result<bool>

One more method to compute a transformation from the source frame to the destination one. It is designed to save on computing the frame data (image pyramids, normals, etc.).

fn compute2_def( &self, src_frame: &mut Ptr<OdometryFrame>, dst_frame: &mut Ptr<OdometryFrame>, rt: &mut impl ToOutputArray ) -> Result<bool>

One more method to compute a transformation from the source frame to the destination one. It is designed to save on computing the frame data (image pyramids, normals, etc.).

fn prepare_frame_cache( &self, frame: &mut Ptr<OdometryFrame>, cache_type: i32 ) -> Result<Size>

Prepare a cache for the frame. The function checks the precomputed/passed data (throws the error if this data does not satisfy) and computes all remaining cache data needed for the frame. Returned size is a resolution of the prepared frame.

fn get_camera_matrix(&self) -> Result<Mat>

See also

fn get_transform_type(&self) -> Result<i32>

See also

impl OdometryTraitConst for Ptr<ICPOdometry>

fn as_raw_Odometry(&self) -> *const c_void

fn compute( &self, src_image: &impl MatTraitConst, src_depth: &impl MatTraitConst, src_mask: &impl MatTraitConst, dst_image: &impl MatTraitConst, dst_depth: &impl MatTraitConst, dst_mask: &impl MatTraitConst, rt: &mut impl ToOutputArray, init_rt: &impl MatTraitConst ) -> Result<bool>

Method to compute a transformation from the source frame to the destination one. Some odometry algorithms do not used some data of frames (eg. ICP does not use images). In such case corresponding arguments can be set as empty Mat. The method returns true if all internal computations were possible (e.g. there were enough correspondences, system of equations has a solution, etc) and resulting transformation satisfies some test if it’s provided by the Odometry inheritor implementation (e.g. thresholds for maximum translation and rotation).

fn compute_def( &self, src_image: &impl MatTraitConst, src_depth: &impl MatTraitConst, src_mask: &impl MatTraitConst, dst_image: &impl MatTraitConst, dst_depth: &impl MatTraitConst, dst_mask: &impl MatTraitConst, rt: &mut impl ToOutputArray ) -> Result<bool>

Method to compute a transformation from the source frame to the destination one. Some odometry algorithms do not used some data of frames (eg. ICP does not use images). In such case corresponding arguments can be set as empty Mat. The method returns true if all internal computations were possible (e.g. there were enough correspondences, system of equations has a solution, etc) and resulting transformation satisfies some test if it’s provided by the Odometry inheritor implementation (e.g. thresholds for maximum translation and rotation).

fn compute2( &self, src_frame: &mut Ptr<OdometryFrame>, dst_frame: &mut Ptr<OdometryFrame>, rt: &mut impl ToOutputArray, init_rt: &impl MatTraitConst ) -> Result<bool>

One more method to compute a transformation from the source frame to the destination one. It is designed to save on computing the frame data (image pyramids, normals, etc.).

fn compute2_def( &self, src_frame: &mut Ptr<OdometryFrame>, dst_frame: &mut Ptr<OdometryFrame>, rt: &mut impl ToOutputArray ) -> Result<bool>

One more method to compute a transformation from the source frame to the destination one. It is designed to save on computing the frame data (image pyramids, normals, etc.).

fn prepare_frame_cache( &self, frame: &mut Ptr<OdometryFrame>, cache_type: i32 ) -> Result<Size>

Prepare a cache for the frame. The function checks the precomputed/passed data (throws the error if this data does not satisfy) and computes all remaining cache data needed for the frame. Returned size is a resolution of the prepared frame.

fn get_camera_matrix(&self) -> Result<Mat>

See also

fn get_transform_type(&self) -> Result<i32>

See also

impl OdometryTraitConst for Ptr<Odometry>

fn as_raw_Odometry(&self) -> *const c_void

fn compute( &self, src_image: &impl MatTraitConst, src_depth: &impl MatTraitConst, src_mask: &impl MatTraitConst, dst_image: &impl MatTraitConst, dst_depth: &impl MatTraitConst, dst_mask: &impl MatTraitConst, rt: &mut impl ToOutputArray, init_rt: &impl MatTraitConst ) -> Result<bool>

Method to compute a transformation from the source frame to the destination one. Some odometry algorithms do not used some data of frames (eg. ICP does not use images). In such case corresponding arguments can be set as empty Mat. The method returns true if all internal computations were possible (e.g. there were enough correspondences, system of equations has a solution, etc) and resulting transformation satisfies some test if it’s provided by the Odometry inheritor implementation (e.g. thresholds for maximum translation and rotation).

fn compute_def( &self, src_image: &impl MatTraitConst, src_depth: &impl MatTraitConst, src_mask: &impl MatTraitConst, dst_image: &impl MatTraitConst, dst_depth: &impl MatTraitConst, dst_mask: &impl MatTraitConst, rt: &mut impl ToOutputArray ) -> Result<bool>

Method to compute a transformation from the source frame to the destination one. Some odometry algorithms do not used some data of frames (eg. ICP does not use images). In such case corresponding arguments can be set as empty Mat. The method returns true if all internal computations were possible (e.g. there were enough correspondences, system of equations has a solution, etc) and resulting transformation satisfies some test if it’s provided by the Odometry inheritor implementation (e.g. thresholds for maximum translation and rotation).

fn compute2( &self, src_frame: &mut Ptr<OdometryFrame>, dst_frame: &mut Ptr<OdometryFrame>, rt: &mut impl ToOutputArray, init_rt: &impl MatTraitConst ) -> Result<bool>

One more method to compute a transformation from the source frame to the destination one. It is designed to save on computing the frame data (image pyramids, normals, etc.).

fn compute2_def( &self, src_frame: &mut Ptr<OdometryFrame>, dst_frame: &mut Ptr<OdometryFrame>, rt: &mut impl ToOutputArray ) -> Result<bool>

One more method to compute a transformation from the source frame to the destination one. It is designed to save on computing the frame data (image pyramids, normals, etc.).

fn prepare_frame_cache( &self, frame: &mut Ptr<OdometryFrame>, cache_type: i32 ) -> Result<Size>

Prepare a cache for the frame. The function checks the precomputed/passed data (throws the error if this data does not satisfy) and computes all remaining cache data needed for the frame. Returned size is a resolution of the prepared frame.

fn get_camera_matrix(&self) -> Result<Mat>

See also

fn get_transform_type(&self) -> Result<i32>

See also

impl OdometryTraitConst for Ptr<RgbdICPOdometry>

fn as_raw_Odometry(&self) -> *const c_void

fn compute( &self, src_image: &impl MatTraitConst, src_depth: &impl MatTraitConst, src_mask: &impl MatTraitConst, dst_image: &impl MatTraitConst, dst_depth: &impl MatTraitConst, dst_mask: &impl MatTraitConst, rt: &mut impl ToOutputArray, init_rt: &impl MatTraitConst ) -> Result<bool>

Method to compute a transformation from the source frame to the destination one. Some odometry algorithms do not used some data of frames (eg. ICP does not use images). In such case corresponding arguments can be set as empty Mat. The method returns true if all internal computations were possible (e.g. there were enough correspondences, system of equations has a solution, etc) and resulting transformation satisfies some test if it’s provided by the Odometry inheritor implementation (e.g. thresholds for maximum translation and rotation).

fn compute_def( &self, src_image: &impl MatTraitConst, src_depth: &impl MatTraitConst, src_mask: &impl MatTraitConst, dst_image: &impl MatTraitConst, dst_depth: &impl MatTraitConst, dst_mask: &impl MatTraitConst, rt: &mut impl ToOutputArray ) -> Result<bool>

Method to compute a transformation from the source frame to the destination one. Some odometry algorithms do not used some data of frames (eg. ICP does not use images). In such case corresponding arguments can be set as empty Mat. The method returns true if all internal computations were possible (e.g. there were enough correspondences, system of equations has a solution, etc) and resulting transformation satisfies some test if it’s provided by the Odometry inheritor implementation (e.g. thresholds for maximum translation and rotation).

fn compute2( &self, src_frame: &mut Ptr<OdometryFrame>, dst_frame: &mut Ptr<OdometryFrame>, rt: &mut impl ToOutputArray, init_rt: &impl MatTraitConst ) -> Result<bool>

One more method to compute a transformation from the source frame to the destination one. It is designed to save on computing the frame data (image pyramids, normals, etc.).

fn compute2_def( &self, src_frame: &mut Ptr<OdometryFrame>, dst_frame: &mut Ptr<OdometryFrame>, rt: &mut impl ToOutputArray ) -> Result<bool>

One more method to compute a transformation from the source frame to the destination one. It is designed to save on computing the frame data (image pyramids, normals, etc.).

fn prepare_frame_cache( &self, frame: &mut Ptr<OdometryFrame>, cache_type: i32 ) -> Result<Size>

Prepare a cache for the frame. The function checks the precomputed/passed data (throws the error if this data does not satisfy) and computes all remaining cache data needed for the frame. Returned size is a resolution of the prepared frame.

fn get_camera_matrix(&self) -> Result<Mat>

See also

fn get_transform_type(&self) -> Result<i32>

See also

impl OdometryTraitConst for Ptr<RgbdOdometry>

fn as_raw_Odometry(&self) -> *const c_void

fn compute( &self, src_image: &impl MatTraitConst, src_depth: &impl MatTraitConst, src_mask: &impl MatTraitConst, dst_image: &impl MatTraitConst, dst_depth: &impl MatTraitConst, dst_mask: &impl MatTraitConst, rt: &mut impl ToOutputArray, init_rt: &impl MatTraitConst ) -> Result<bool>

Method to compute a transformation from the source frame to the destination one. Some odometry algorithms do not used some data of frames (eg. ICP does not use images). In such case corresponding arguments can be set as empty Mat. The method returns true if all internal computations were possible (e.g. there were enough correspondences, system of equations has a solution, etc) and resulting transformation satisfies some test if it’s provided by the Odometry inheritor implementation (e.g. thresholds for maximum translation and rotation).

fn compute_def( &self, src_image: &impl MatTraitConst, src_depth: &impl MatTraitConst, src_mask: &impl MatTraitConst, dst_image: &impl MatTraitConst, dst_depth: &impl MatTraitConst, dst_mask: &impl MatTraitConst, rt: &mut impl ToOutputArray ) -> Result<bool>

Method to compute a transformation from the source frame to the destination one. Some odometry algorithms do not used some data of frames (eg. ICP does not use images). In such case corresponding arguments can be set as empty Mat. The method returns true if all internal computations were possible (e.g. there were enough correspondences, system of equations has a solution, etc) and resulting transformation satisfies some test if it’s provided by the Odometry inheritor implementation (e.g. thresholds for maximum translation and rotation).

fn compute2( &self, src_frame: &mut Ptr<OdometryFrame>, dst_frame: &mut Ptr<OdometryFrame>, rt: &mut impl ToOutputArray, init_rt: &impl MatTraitConst ) -> Result<bool>

One more method to compute a transformation from the source frame to the destination one. It is designed to save on computing the frame data (image pyramids, normals, etc.).

fn compute2_def( &self, src_frame: &mut Ptr<OdometryFrame>, dst_frame: &mut Ptr<OdometryFrame>, rt: &mut impl ToOutputArray ) -> Result<bool>

One more method to compute a transformation from the source frame to the destination one. It is designed to save on computing the frame data (image pyramids, normals, etc.).

fn prepare_frame_cache( &self, frame: &mut Ptr<OdometryFrame>, cache_type: i32 ) -> Result<Size>

Prepare a cache for the frame. The function checks the precomputed/passed data (throws the error if this data does not satisfy) and computes all remaining cache data needed for the frame. Returned size is a resolution of the prepared frame.

fn get_camera_matrix(&self) -> Result<Mat>

See also

fn get_transform_type(&self) -> Result<i32>

See also

impl OnePassStabilizerTrait for Ptr<OnePassStabilizer>

fn as_raw_mut_OnePassStabilizer(&mut self) -> *mut c_void

fn set_motion_filter(&mut self, val: Ptr<MotionFilterBase>) -> Result<()>

fn reset(&mut self) -> Result<()>

fn next_frame(&mut self) -> Result<Mat>

impl OnePassStabilizerTraitConst for Ptr<OnePassStabilizer>

fn as_raw_OnePassStabilizer(&self) -> *const c_void

fn motion_filter(&self) -> Result<Ptr<MotionFilterBase>>

impl OpticalFlowPCAFlowTrait for Ptr<OpticalFlowPCAFlow>

fn as_raw_mut_OpticalFlowPCAFlow(&mut self) -> *mut c_void

fn calc( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

fn collect_garbage(&mut self) -> Result<()>

impl OpticalFlowPCAFlowTraitConst for Ptr<OpticalFlowPCAFlow>

fn as_raw_OpticalFlowPCAFlow(&self) -> *const c_void

impl OriginalClassNameTrait for Ptr<OriginalClassName>

fn as_raw_mut_OriginalClassName(&mut self) -> *mut c_void

impl OriginalClassNameTraitConst for Ptr<OriginalClassName>

fn as_raw_OriginalClassName(&self) -> *const c_void

fn get_int_param(&self) -> Result<i32>

fn get_float_param(&self) -> Result<f32>

impl PCAPriorTrait for Ptr<PCAPrior>

fn as_raw_mut_PCAPrior(&mut self) -> *mut c_void

impl PCAPriorTraitConst for Ptr<PCAPrior>

fn as_raw_PCAPrior(&self) -> *const c_void

fn get_padding(&self) -> Result<i32>

fn get_basis_size(&self) -> Result<i32>

fn fill_constraints( &self, a1: &mut f32, a2: &mut f32, b1: &mut f32, b2: &mut f32 ) -> Result<()>

impl PCTSignaturesSQFDTrait for Ptr<PCTSignaturesSQFD>

fn as_raw_mut_PCTSignaturesSQFD(&mut self) -> *mut c_void

impl PCTSignaturesSQFDTraitConst for Ptr<PCTSignaturesSQFD>

fn as_raw_PCTSignaturesSQFD(&self) -> *const c_void

fn compute_quadratic_form_distance( &self, _signature0: &impl ToInputArray, _signature1: &impl ToInputArray ) -> Result<f32>

Computes Signature Quadratic Form Distance of two signatures.

fn compute_quadratic_form_distances( &self, source_signature: &impl MatTraitConst, image_signatures: &Vector<Mat>, distances: &mut Vector<f32> ) -> Result<()>

Computes Signature Quadratic Form Distance between the reference signature and each of the other image signatures.

impl PCTSignaturesTrait for Ptr<PCTSignatures>

fn as_raw_mut_PCTSignatures(&mut self) -> *mut c_void

fn set_grayscale_bits(&mut self, grayscale_bits: i32) -> Result<()>

Color resolution of the greyscale bitmap represented in allocated bits (i.e., value 4 means that 16 shades of grey are used). The greyscale bitmap is used for computing contrast and entropy values.

fn set_window_radius(&mut self, radius: i32) -> Result<()>

Size of the texture sampling window used to compute contrast and entropy (center of the window is always in the pixel selected by x,y coordinates of the corresponding feature sample).

fn set_weight_x(&mut self, weight: f32) -> Result<()>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space (x,y = position; L,a,b = color in CIE Lab space; c = contrast. e = entropy)

fn set_weight_y(&mut self, weight: f32) -> Result<()>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space (x,y = position; L,a,b = color in CIE Lab space; c = contrast. e = entropy)

fn set_weight_l(&mut self, weight: f32) -> Result<()>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space (x,y = position; L,a,b = color in CIE Lab space; c = contrast. e = entropy)

fn set_weight_a(&mut self, weight: f32) -> Result<()>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space (x,y = position; L,a,b = color in CIE Lab space; c = contrast. e = entropy)

fn set_weight_b(&mut self, weight: f32) -> Result<()>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space (x,y = position; L,a,b = color in CIE Lab space; c = contrast. e = entropy)

fn set_weight_contrast(&mut self, weight: f32) -> Result<()>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space (x,y = position; L,a,b = color in CIE Lab space; c = contrast. e = entropy)

fn set_weight_entropy(&mut self, weight: f32) -> Result<()>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space (x,y = position; L,a,b = color in CIE Lab space; c = contrast. e = entropy)

fn set_weight(&mut self, idx: i32, value: f32) -> Result<()>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space.

fn set_weights(&mut self, weights: &Vector<f32>) -> Result<()>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space.

fn set_translation(&mut self, idx: i32, value: f32) -> Result<()>

Translations of the individual axes of the feature space.

fn set_translations(&mut self, translations: &Vector<f32>) -> Result<()>

Translations of the individual axes of the feature space.

fn set_sampling_points( &mut self, sampling_points: Vector<Point2f> ) -> Result<()>

Sets sampling points used to sample the input image.

fn set_init_seed_indexes( &mut self, init_seed_indexes: Vector<i32> ) -> Result<()>

Initial seed indexes for the k-means algorithm.

fn set_iteration_count(&mut self, iteration_count: i32) -> Result<()>

Number of iterations of the k-means clustering. We use fixed number of iterations, since the modified clustering is pruning clusters (not iteratively refining k clusters).

fn set_max_clusters_count(&mut self, max_clusters_count: i32) -> Result<()>

Maximal number of generated clusters. If the number is exceeded, the clusters are sorted by their weights and the smallest clusters are cropped.

fn set_cluster_min_size(&mut self, cluster_min_size: i32) -> Result<()>

This parameter multiplied by the index of iteration gives lower limit for cluster size. Clusters containing fewer points than specified by the limit have their centroid dismissed and points are reassigned.

fn set_joining_distance(&mut self, joining_distance: f32) -> Result<()>

Threshold euclidean distance between two centroids. If two cluster centers are closer than this distance, one of the centroid is dismissed and points are reassigned.

fn set_drop_threshold(&mut self, drop_threshold: f32) -> Result<()>

Remove centroids in k-means whose weight is lesser or equal to given threshold.

fn set_distance_function(&mut self, distance_function: i32) -> Result<()>

Distance function selector used for measuring distance between two points in k-means. Available: L0_25, L0_5, L1, L2, L2SQUARED, L5, L_INFINITY.

impl PCTSignaturesTraitConst for Ptr<PCTSignatures>

fn as_raw_PCTSignatures(&self) -> *const c_void

fn compute_signature( &self, image: &impl ToInputArray, signature: &mut impl ToOutputArray ) -> Result<()>

Computes signature of given image.

fn compute_signatures( &self, images: &Vector<Mat>, signatures: &mut Vector<Mat> ) -> Result<()>

Computes signatures for multiple images in parallel.

fn get_sample_count(&self) -> Result<i32>

Number of initial samples taken from the image.

fn get_grayscale_bits(&self) -> Result<i32>

Color resolution of the greyscale bitmap represented in allocated bits (i.e., value 4 means that 16 shades of grey are used). The greyscale bitmap is used for computing contrast and entropy values.

fn get_window_radius(&self) -> Result<i32>

Size of the texture sampling window used to compute contrast and entropy (center of the window is always in the pixel selected by x,y coordinates of the corresponding feature sample).

fn get_weight_x(&self) -> Result<f32>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space (x,y = position; L,a,b = color in CIE Lab space; c = contrast. e = entropy)

fn get_weight_y(&self) -> Result<f32>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space (x,y = position; L,a,b = color in CIE Lab space; c = contrast. e = entropy)

fn get_weight_l(&self) -> Result<f32>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space (x,y = position; L,a,b = color in CIE Lab space; c = contrast. e = entropy)

fn get_weight_a(&self) -> Result<f32>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space (x,y = position; L,a,b = color in CIE Lab space; c = contrast. e = entropy)

fn get_weight_b(&self) -> Result<f32>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space (x,y = position; L,a,b = color in CIE Lab space; c = contrast. e = entropy)

fn get_weight_contrast(&self) -> Result<f32>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space (x,y = position; L,a,b = color in CIE Lab space; c = contrast. e = entropy)

fn get_weight_entropy(&self) -> Result<f32>

Weights (multiplicative constants) that linearly stretch individual axes of the feature space (x,y = position; L,a,b = color in CIE Lab space; c = contrast. e = entropy)

fn get_sampling_points(&self) -> Result<Vector<Point2f>>

Initial samples taken from the image. These sampled features become the input for clustering.

fn get_init_seed_indexes(&self) -> Result<Vector<i32>>

** clusterizer ***

fn get_init_seed_count(&self) -> Result<i32>

Number of initial seeds (initial number of clusters) for the k-means algorithm.

fn get_iteration_count(&self) -> Result<i32>

Number of iterations of the k-means clustering. We use fixed number of iterations, since the modified clustering is pruning clusters (not iteratively refining k clusters).

fn get_max_clusters_count(&self) -> Result<i32>

Maximal number of generated clusters. If the number is exceeded, the clusters are sorted by their weights and the smallest clusters are cropped.

fn get_cluster_min_size(&self) -> Result<i32>

This parameter multiplied by the index of iteration gives lower limit for cluster size. Clusters containing fewer points than specified by the limit have their centroid dismissed and points are reassigned.

fn get_joining_distance(&self) -> Result<f32>

Threshold euclidean distance between two centroids. If two cluster centers are closer than this distance, one of the centroid is dismissed and points are reassigned.

fn get_drop_threshold(&self) -> Result<f32>

Remove centroids in k-means whose weight is lesser or equal to given threshold.

fn get_distance_function(&self) -> Result<i32>

Distance function selector used for measuring distance between two points in k-means.

impl PHashTrait for Ptr<PHash>

fn as_raw_mut_PHash(&mut self) -> *mut c_void

impl PHashTraitConst for Ptr<PHash>

fn as_raw_PHash(&self) -> *const c_void

impl PaddingLayerTrait for Ptr<PaddingLayer>

fn as_raw_mut_PaddingLayer(&mut self) -> *mut c_void

impl PaddingLayerTraitConst for Ptr<PaddingLayer>

fn as_raw_PaddingLayer(&self) -> *const c_void

impl PaniniPortraitWarperTrait for Ptr<PaniniPortraitWarper>

fn as_raw_mut_PaniniPortraitWarper(&mut self) -> *mut c_void

impl PaniniPortraitWarperTraitConst for Ptr<PaniniPortraitWarper>

fn as_raw_PaniniPortraitWarper(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl PaniniWarperTrait for Ptr<PaniniWarper>

fn as_raw_mut_PaniniWarper(&mut self) -> *mut c_void

impl PaniniWarperTraitConst for Ptr<PaniniWarper>

fn as_raw_PaniniWarper(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl ParamGridTrait for Ptr<ParamGrid>

fn as_raw_mut_ParamGrid(&mut self) -> *mut c_void

fn set_min_val(&mut self, val: f64)

Minimum value of the statmodel parameter. Default value is 0.

fn set_max_val(&mut self, val: f64)

Maximum value of the statmodel parameter. Default value is 0.

fn set_log_step(&mut self, val: f64)

Logarithmic step for iterating the statmodel parameter.

impl ParamGridTraitConst for Ptr<ParamGrid>

fn as_raw_ParamGrid(&self) -> *const c_void

fn min_val(&self) -> f64

Minimum value of the statmodel parameter. Default value is 0.

fn max_val(&self) -> f64

Maximum value of the statmodel parameter. Default value is 0.

fn log_step(&self) -> f64

Logarithmic step for iterating the statmodel parameter.

impl ParamsTrait for Ptr<Params>

fn as_raw_mut_Params(&mut self) -> *mut c_void

fn set_frame_size(&mut self, val: Size)

frame size in pixels

fn set_intr(&mut self, val: Matx33f)

camera intrinsics

fn set_rgb_intr(&mut self, val: Matx33f)

rgb camera intrinsics

fn set_depth_factor(&mut self, val: f32)

pre-scale per 1 meter for input values Typical values are: * 5000 per 1 meter for the 16-bit PNG files of TUM database * 1000 per 1 meter for Kinect 2 device * 1 per 1 meter for the 32-bit float images in the ROS bag files

fn set_bilateral_sigma_depth(&mut self, val: f32)

Depth sigma in meters for bilateral smooth

fn set_bilateral_sigma_spatial(&mut self, val: f32)

Spatial sigma in pixels for bilateral smooth

fn set_bilateral_kernel_size(&mut self, val: i32)

Kernel size in pixels for bilateral smooth

fn set_pyramid_levels(&mut self, val: i32)

Number of pyramid levels for ICP

fn set_tsdf_min_camera_movement(&mut self, val: f32)

Minimal camera movement in meters Integrate new depth frame only if camera movement exceeds this value.

fn set_light_pose(&mut self, val: Vec3f)

light pose for rendering in meters

fn set_icp_dist_thresh(&mut self, val: f32)

distance theshold for ICP in meters

fn set_icp_angle_thresh(&mut self, val: f32)

angle threshold for ICP in radians

fn set_icp_iterations(&mut self, val: Vector<i32>)

number of ICP iterations for each pyramid level

fn set_truncate_threshold(&mut self, val: f32)

Threshold for depth truncation in meters All depth values beyond this threshold will be set to zero

fn set_volume_params(&mut self, val: Kinfu_VolumeParams)

Volume parameters

impl ParamsTraitConst for Ptr<Params>

fn as_raw_Params(&self) -> *const c_void

fn frame_size(&self) -> Size

frame size in pixels

fn intr(&self) -> Matx33f

camera intrinsics

fn rgb_intr(&self) -> Matx33f

rgb camera intrinsics

fn depth_factor(&self) -> f32

pre-scale per 1 meter for input values Typical values are: * 5000 per 1 meter for the 16-bit PNG files of TUM database * 1000 per 1 meter for Kinect 2 device * 1 per 1 meter for the 32-bit float images in the ROS bag files

fn bilateral_sigma_depth(&self) -> f32

Depth sigma in meters for bilateral smooth

fn bilateral_sigma_spatial(&self) -> f32

Spatial sigma in pixels for bilateral smooth

fn bilateral_kernel_size(&self) -> i32

Kernel size in pixels for bilateral smooth

fn pyramid_levels(&self) -> i32

Number of pyramid levels for ICP

fn tsdf_min_camera_movement(&self) -> f32

Minimal camera movement in meters Integrate new depth frame only if camera movement exceeds this value.

fn light_pose(&self) -> Vec3f

light pose for rendering in meters

fn icp_dist_thresh(&self) -> f32

distance theshold for ICP in meters

fn icp_angle_thresh(&self) -> f32

angle threshold for ICP in radians

fn icp_iterations(&self) -> Vector<i32>

number of ICP iterations for each pyramid level

fn truncate_threshold(&self) -> f32

Threshold for depth truncation in meters All depth values beyond this threshold will be set to zero

fn volume_params(&self) -> Kinfu_VolumeParams

Volume parameters

impl PermuteLayerTrait for Ptr<PermuteLayer>

fn as_raw_mut_PermuteLayer(&mut self) -> *mut c_void

impl PermuteLayerTraitConst for Ptr<PermuteLayer>

fn as_raw_PermuteLayer(&self) -> *const c_void

impl PhaseUnwrappingTrait for Ptr<HistogramPhaseUnwrapping>

fn as_raw_mut_PhaseUnwrapping(&mut self) -> *mut c_void

fn unwrap_phase_map( &mut self, wrapped_phase_map: &impl ToInputArray, unwrapped_phase_map: &mut impl ToOutputArray, shadow_mask: &impl ToInputArray ) -> Result<()>

Unwraps a 2D phase map.

fn unwrap_phase_map_def( &mut self, wrapped_phase_map: &impl ToInputArray, unwrapped_phase_map: &mut impl ToOutputArray ) -> Result<()>

Unwraps a 2D phase map.

impl PhaseUnwrappingTrait for Ptr<PhaseUnwrapping>

fn as_raw_mut_PhaseUnwrapping(&mut self) -> *mut c_void

fn unwrap_phase_map( &mut self, wrapped_phase_map: &impl ToInputArray, unwrapped_phase_map: &mut impl ToOutputArray, shadow_mask: &impl ToInputArray ) -> Result<()>

Unwraps a 2D phase map.

fn unwrap_phase_map_def( &mut self, wrapped_phase_map: &impl ToInputArray, unwrapped_phase_map: &mut impl ToOutputArray ) -> Result<()>

Unwraps a 2D phase map.

impl PhaseUnwrappingTraitConst for Ptr<HistogramPhaseUnwrapping>

fn as_raw_PhaseUnwrapping(&self) -> *const c_void

impl PhaseUnwrappingTraitConst for Ptr<PhaseUnwrapping>

fn as_raw_PhaseUnwrapping(&self) -> *const c_void

impl PlaneWarperGpuTrait for Ptr<PlaneWarperGpu>

fn as_raw_mut_PlaneWarperGpu(&mut self) -> *mut c_void

impl PlaneWarperGpuTraitConst for Ptr<PlaneWarperGpu>

fn as_raw_PlaneWarperGpu(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl PlaneWarperTrait for Ptr<PlaneWarper>

fn as_raw_mut_PlaneWarper(&mut self) -> *mut c_void

impl PlaneWarperTraitConst for Ptr<PlaneWarper>

fn as_raw_PlaneWarper(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl Plot2dTrait for Ptr<Plot2d>

fn as_raw_mut_Plot2d(&mut self) -> *mut c_void

fn set_min_x(&mut self, _plot_min_x: f64) -> Result<()>

fn set_min_y(&mut self, _plot_min_y: f64) -> Result<()>

fn set_max_x(&mut self, _plot_max_x: f64) -> Result<()>

fn set_max_y(&mut self, _plot_max_y: f64) -> Result<()>

fn set_plot_line_width(&mut self, _plot_line_width: i32) -> Result<()>

fn set_need_plot_line(&mut self, _need_plot_line: bool) -> Result<()>

Switches data visualization mode

fn set_plot_line_color(&mut self, _plot_line_color: Scalar) -> Result<()>

fn set_plot_background_color( &mut self, _plot_background_color: Scalar ) -> Result<()>

fn set_plot_axis_color(&mut self, _plot_axis_color: Scalar) -> Result<()>

fn set_plot_grid_color(&mut self, _plot_grid_color: Scalar) -> Result<()>

fn set_plot_text_color(&mut self, _plot_text_color: Scalar) -> Result<()>

fn set_plot_size( &mut self, _plot_size_width: i32, _plot_size_height: i32 ) -> Result<()>

fn set_show_grid(&mut self, need_show_grid: bool) -> Result<()>

fn set_show_text(&mut self, need_show_text: bool) -> Result<()>

fn set_grid_lines_number(&mut self, grid_lines_number: i32) -> Result<()>

fn set_invert_orientation(&mut self, _invert_orientation: bool) -> Result<()>

fn set_point_idx_to_print(&mut self, point_idx: i32) -> Result<()>

Sets the index of a point which coordinates will be printed on the top left corner of the plot (if ShowText flag is true).

fn render(&mut self, _plot_result: &mut impl ToOutputArray) -> Result<()>

impl Plot2dTraitConst for Ptr<Plot2d>

fn as_raw_Plot2d(&self) -> *const c_void

impl PoolingLayerInt8Trait for Ptr<PoolingLayerInt8>

fn as_raw_mut_PoolingLayerInt8(&mut self) -> *mut c_void

fn set_input_zp(&mut self, val: i32)

fn set_output_zp(&mut self, val: i32)

fn set_input_sc(&mut self, val: f32)

fn set_output_sc(&mut self, val: f32)

impl PoolingLayerInt8TraitConst for Ptr<PoolingLayerInt8>

fn as_raw_PoolingLayerInt8(&self) -> *const c_void

fn input_zp(&self) -> i32

fn output_zp(&self) -> i32

fn input_sc(&self) -> f32

fn output_sc(&self) -> f32

impl PoolingLayerTrait for Ptr<PoolingLayer>

fn as_raw_mut_PoolingLayer(&mut self) -> *mut c_void

fn set_type(&mut self, val: i32)

fn set_kernel_size(&mut self, val: Vector<size_t>)

fn set_strides(&mut self, val: Vector<size_t>)

fn set_pads_begin(&mut self, val: Vector<size_t>)

fn set_pads_end(&mut self, val: Vector<size_t>)

fn set_global_pooling(&mut self, val: bool)

Flag is true if at least one of the axes is global pooled.

fn set_is_global_pooling(&mut self, val: Vector<bool>)

fn set_compute_max_idx(&mut self, val: bool)

fn set_pad_mode(&mut self, val: &str)

fn set_ceil_mode(&mut self, val: bool)

fn set_ave_pool_padded_area(&mut self, val: bool)

fn set_pooled_size(&mut self, val: Size)

fn set_spatial_scale(&mut self, val: f32)

fn set_ps_roi_out_channels(&mut self, val: i32)

impl PoolingLayerTrait for Ptr<PoolingLayerInt8>

fn as_raw_mut_PoolingLayer(&mut self) -> *mut c_void

fn set_type(&mut self, val: i32)

fn set_kernel_size(&mut self, val: Vector<size_t>)

fn set_strides(&mut self, val: Vector<size_t>)

fn set_pads_begin(&mut self, val: Vector<size_t>)

fn set_pads_end(&mut self, val: Vector<size_t>)

fn set_global_pooling(&mut self, val: bool)

Flag is true if at least one of the axes is global pooled.

fn set_is_global_pooling(&mut self, val: Vector<bool>)

fn set_compute_max_idx(&mut self, val: bool)

fn set_pad_mode(&mut self, val: &str)

fn set_ceil_mode(&mut self, val: bool)

fn set_ave_pool_padded_area(&mut self, val: bool)

fn set_pooled_size(&mut self, val: Size)

fn set_spatial_scale(&mut self, val: f32)

fn set_ps_roi_out_channels(&mut self, val: i32)

impl PoolingLayerTraitConst for Ptr<PoolingLayer>

fn as_raw_PoolingLayer(&self) -> *const c_void

fn typ(&self) -> i32

fn kernel_size(&self) -> Vector<size_t>

fn strides(&self) -> Vector<size_t>

fn pads_begin(&self) -> Vector<size_t>

fn pads_end(&self) -> Vector<size_t>

fn global_pooling(&self) -> bool

Flag is true if at least one of the axes is global pooled.

fn is_global_pooling(&self) -> Vector<bool>

fn compute_max_idx(&self) -> bool

fn pad_mode(&self) -> String

fn ceil_mode(&self) -> bool

fn ave_pool_padded_area(&self) -> bool

fn pooled_size(&self) -> Size

fn spatial_scale(&self) -> f32

fn ps_roi_out_channels(&self) -> i32

impl PoolingLayerTraitConst for Ptr<PoolingLayerInt8>

fn as_raw_PoolingLayer(&self) -> *const c_void

fn typ(&self) -> i32

fn kernel_size(&self) -> Vector<size_t>

fn strides(&self) -> Vector<size_t>

fn pads_begin(&self) -> Vector<size_t>

fn pads_end(&self) -> Vector<size_t>

fn global_pooling(&self) -> bool

Flag is true if at least one of the axes is global pooled.

fn is_global_pooling(&self) -> Vector<bool>

fn compute_max_idx(&self) -> bool

fn pad_mode(&self) -> String

fn ceil_mode(&self) -> bool

fn ave_pool_padded_area(&self) -> bool

fn pooled_size(&self) -> Size

fn spatial_scale(&self) -> f32

fn ps_roi_out_channels(&self) -> i32

impl Pose3DTrait for Ptr<Pose3D>

fn as_raw_mut_Pose3D(&mut self) -> *mut c_void

fn set_alpha(&mut self, val: f64)

fn set_residual(&mut self, val: f64)

fn set_model_index(&mut self, val: size_t)

fn set_num_votes(&mut self, val: size_t)

fn set_pose(&mut self, val: Matx44d)

fn set_angle(&mut self, val: f64)

fn set_t(&mut self, val: Vec3d)

fn set_q(&mut self, val: Vec4d)

fn update_pose(&mut self, new_pose: &mut Matx44d) -> Result<()>

\brief Updates the pose with the new one \param [in] NewPose New pose to overwrite

fn update_pose_1( &mut self, new_r: &mut Matx33d, new_t: &mut Vec3d ) -> Result<()>

\brief Updates the pose with the new one

fn update_pose_quat(&mut self, q: &mut Vec4d, new_t: &mut Vec3d) -> Result<()>

\brief Updates the pose with the new one, but this time using quaternions to represent rotation

fn append_pose(&mut self, incremental_pose: &mut Matx44d) -> Result<()>

\brief Left multiplies the existing pose in order to update the transformation \param [in] IncrementalPose New pose to apply

fn print_pose(&mut self) -> Result<()>

fn clone(&mut self) -> Result<Pose3DPtr>

fn write_pose(&mut self, file_name: &str) -> Result<i32>

fn read_pose(&mut self, file_name: &str) -> Result<i32>

impl Pose3DTraitConst for Ptr<Pose3D>

fn as_raw_Pose3D(&self) -> *const c_void

fn alpha(&self) -> f64

fn residual(&self) -> f64

fn model_index(&self) -> size_t

fn num_votes(&self) -> size_t

fn pose(&self) -> Matx44d

fn angle(&self) -> f64

fn t(&self) -> Vec3d

fn q(&self) -> Vec4d

impl PoseCluster3DTrait for Ptr<PoseCluster3D>

fn as_raw_mut_PoseCluster3D(&mut self) -> *mut c_void

fn set_pose_list(&mut self, val: Vector<Pose3DPtr>)

fn set_num_votes(&mut self, val: size_t)

fn set_id(&mut self, val: i32)

fn add_pose(&mut self, new_pose: Pose3DPtr) -> Result<()>

\brief Adds a new pose to the cluster. The pose should be “close” to the mean poses in order to preserve the consistency \param [in] newPose Pose to add to the cluster

fn write_pose_cluster(&mut self, file_name: &str) -> Result<i32>

fn read_pose_cluster(&mut self, file_name: &str) -> Result<i32>

impl PoseCluster3DTraitConst for Ptr<PoseCluster3D>

fn as_raw_PoseCluster3D(&self) -> *const c_void

fn pose_list(&self) -> Vector<Pose3DPtr>

fn num_votes(&self) -> size_t

fn id(&self) -> i32

impl PowerLayerTrait for Ptr<PowerLayer>

fn as_raw_mut_PowerLayer(&mut self) -> *mut c_void

fn set_power(&mut self, val: f32)

fn set_scale(&mut self, val: f32)

fn set_shift(&mut self, val: f32)

impl PowerLayerTraitConst for Ptr<PowerLayer>

fn as_raw_PowerLayer(&self) -> *const c_void

fn power(&self) -> f32

fn scale(&self) -> f32

fn shift(&self) -> f32

impl PredictCollectorTrait for Ptr<PredictCollector>

fn as_raw_mut_PredictCollector(&mut self) -> *mut c_void

fn init(&mut self, size: size_t) -> Result<()>

Interface method called by face recognizer before results processing

fn collect(&mut self, label: i32, dist: f64) -> Result<bool>

Interface method called by face recognizer for each result

impl PredictCollectorTrait for Ptr<StandardCollector>

fn as_raw_mut_PredictCollector(&mut self) -> *mut c_void

fn init(&mut self, size: size_t) -> Result<()>

Interface method called by face recognizer before results processing

fn collect(&mut self, label: i32, dist: f64) -> Result<bool>

Interface method called by face recognizer for each result

impl PredictCollectorTraitConst for Ptr<PredictCollector>

fn as_raw_PredictCollector(&self) -> *const c_void

impl PredictCollectorTraitConst for Ptr<StandardCollector>

fn as_raw_PredictCollector(&self) -> *const c_void

impl PriorBoxLayerTrait for Ptr<PriorBoxLayer>

fn as_raw_mut_PriorBoxLayer(&mut self) -> *mut c_void

impl PriorBoxLayerTraitConst for Ptr<PriorBoxLayer>

fn as_raw_PriorBoxLayer(&self) -> *const c_void

impl ProposalLayerTrait for Ptr<ProposalLayer>

fn as_raw_mut_ProposalLayer(&mut self) -> *mut c_void

impl ProposalLayerTraitConst for Ptr<ProposalLayer>

fn as_raw_ProposalLayer(&self) -> *const c_void

impl PyrLkOptFlowEstimatorBaseTrait for Ptr<DensePyrLkOptFlowEstimatorGpu>

fn as_raw_mut_PyrLkOptFlowEstimatorBase(&mut self) -> *mut c_void

fn set_win_size(&mut self, val: Size) -> Result<()>

fn set_max_level(&mut self, val: i32) -> Result<()>

impl PyrLkOptFlowEstimatorBaseTrait for Ptr<PyrLkOptFlowEstimatorBase>

fn as_raw_mut_PyrLkOptFlowEstimatorBase(&mut self) -> *mut c_void

fn set_win_size(&mut self, val: Size) -> Result<()>

fn set_max_level(&mut self, val: i32) -> Result<()>

impl PyrLkOptFlowEstimatorBaseTrait for Ptr<SparsePyrLkOptFlowEstimator>

fn as_raw_mut_PyrLkOptFlowEstimatorBase(&mut self) -> *mut c_void

fn set_win_size(&mut self, val: Size) -> Result<()>

fn set_max_level(&mut self, val: i32) -> Result<()>

impl PyrLkOptFlowEstimatorBaseTrait for Ptr<SparsePyrLkOptFlowEstimatorGpu>

fn as_raw_mut_PyrLkOptFlowEstimatorBase(&mut self) -> *mut c_void

fn set_win_size(&mut self, val: Size) -> Result<()>

fn set_max_level(&mut self, val: i32) -> Result<()>

impl PyrLkOptFlowEstimatorBaseTraitConst for Ptr<DensePyrLkOptFlowEstimatorGpu>

fn as_raw_PyrLkOptFlowEstimatorBase(&self) -> *const c_void

fn win_size(&self) -> Result<Size>

fn max_level(&self) -> Result<i32>

impl PyrLkOptFlowEstimatorBaseTraitConst for Ptr<PyrLkOptFlowEstimatorBase>

fn as_raw_PyrLkOptFlowEstimatorBase(&self) -> *const c_void

fn win_size(&self) -> Result<Size>

fn max_level(&self) -> Result<i32>

impl PyrLkOptFlowEstimatorBaseTraitConst for Ptr<SparsePyrLkOptFlowEstimator>

fn as_raw_PyrLkOptFlowEstimatorBase(&self) -> *const c_void

fn win_size(&self) -> Result<Size>

fn max_level(&self) -> Result<i32>

impl PyrLkOptFlowEstimatorBaseTraitConst for Ptr<SparsePyrLkOptFlowEstimatorGpu>

fn as_raw_PyrLkOptFlowEstimatorBase(&self) -> *const c_void

fn win_size(&self) -> Result<Size>

fn max_level(&self) -> Result<i32>

impl QRCodeEncoderTrait for Ptr<QRCodeEncoder>

fn as_raw_mut_QRCodeEncoder(&mut self) -> *mut c_void

fn encode( &mut self, encoded_info: &str, qrcode: &mut impl ToOutputArray ) -> Result<()>

Generates QR code from input string.

fn encode_structured_append( &mut self, encoded_info: &str, qrcodes: &mut impl ToOutputArray ) -> Result<()>

Generates QR code from input string in Structured Append mode. The encoded message is splitting over a number of QR codes.

impl QRCodeEncoderTraitConst for Ptr<QRCodeEncoder>

fn as_raw_QRCodeEncoder(&self) -> *const c_void

impl QualityBRISQUETrait for Ptr<QualityBRISQUE>

fn as_raw_mut_QualityBRISQUE(&mut self) -> *mut c_void

fn compute(&mut self, img: &impl ToInputArray) -> Result<Scalar>

Computes BRISQUE quality score for input image

impl QualityBRISQUETraitConst for Ptr<QualityBRISQUE>

fn as_raw_QualityBRISQUE(&self) -> *const c_void

impl QualityBaseTrait for Ptr<QualityBRISQUE>

fn as_raw_mut_QualityBase(&mut self) -> *mut c_void

fn compute(&mut self, img: &impl ToInputArray) -> Result<Scalar>

Compute quality score per channel with the per-channel score in each element of the resulting cv::Scalar. See specific algorithm for interpreting result scores

fn clear(&mut self) -> Result<()>

Implements Algorithm::clear()

impl QualityBaseTrait for Ptr<QualityBase>

fn as_raw_mut_QualityBase(&mut self) -> *mut c_void

fn compute(&mut self, img: &impl ToInputArray) -> Result<Scalar>

Compute quality score per channel with the per-channel score in each element of the resulting cv::Scalar. See specific algorithm for interpreting result scores

fn clear(&mut self) -> Result<()>

Implements Algorithm::clear()

impl QualityBaseTrait for Ptr<QualityGMSD>

fn as_raw_mut_QualityBase(&mut self) -> *mut c_void

fn compute(&mut self, img: &impl ToInputArray) -> Result<Scalar>

Compute quality score per channel with the per-channel score in each element of the resulting cv::Scalar. See specific algorithm for interpreting result scores

fn clear(&mut self) -> Result<()>

Implements Algorithm::clear()

impl QualityBaseTrait for Ptr<QualityMSE>

fn as_raw_mut_QualityBase(&mut self) -> *mut c_void

fn compute(&mut self, img: &impl ToInputArray) -> Result<Scalar>

Compute quality score per channel with the per-channel score in each element of the resulting cv::Scalar. See specific algorithm for interpreting result scores

fn clear(&mut self) -> Result<()>

Implements Algorithm::clear()

impl QualityBaseTrait for Ptr<QualityPSNR>

fn as_raw_mut_QualityBase(&mut self) -> *mut c_void

fn compute(&mut self, img: &impl ToInputArray) -> Result<Scalar>

Compute quality score per channel with the per-channel score in each element of the resulting cv::Scalar. See specific algorithm for interpreting result scores

fn clear(&mut self) -> Result<()>

Implements Algorithm::clear()

impl QualityBaseTrait for Ptr<QualitySSIM>

fn as_raw_mut_QualityBase(&mut self) -> *mut c_void

fn compute(&mut self, img: &impl ToInputArray) -> Result<Scalar>

Compute quality score per channel with the per-channel score in each element of the resulting cv::Scalar. See specific algorithm for interpreting result scores

fn clear(&mut self) -> Result<()>

Implements Algorithm::clear()

impl QualityBaseTraitConst for Ptr<QualityBRISQUE>

fn as_raw_QualityBase(&self) -> *const c_void

fn get_quality_map(&self, dst: &mut impl ToOutputArray) -> Result<()>

Returns output quality map that was generated during computation, if supported by the algorithm

fn empty(&self) -> Result<bool>

Implements Algorithm::empty()

impl QualityBaseTraitConst for Ptr<QualityBase>

fn as_raw_QualityBase(&self) -> *const c_void

fn get_quality_map(&self, dst: &mut impl ToOutputArray) -> Result<()>

Returns output quality map that was generated during computation, if supported by the algorithm

fn empty(&self) -> Result<bool>

Implements Algorithm::empty()

impl QualityBaseTraitConst for Ptr<QualityGMSD>

fn as_raw_QualityBase(&self) -> *const c_void

fn get_quality_map(&self, dst: &mut impl ToOutputArray) -> Result<()>

Returns output quality map that was generated during computation, if supported by the algorithm

fn empty(&self) -> Result<bool>

Implements Algorithm::empty()

impl QualityBaseTraitConst for Ptr<QualityMSE>

fn as_raw_QualityBase(&self) -> *const c_void

fn get_quality_map(&self, dst: &mut impl ToOutputArray) -> Result<()>

Returns output quality map that was generated during computation, if supported by the algorithm

fn empty(&self) -> Result<bool>

Implements Algorithm::empty()

impl QualityBaseTraitConst for Ptr<QualityPSNR>

fn as_raw_QualityBase(&self) -> *const c_void

fn get_quality_map(&self, dst: &mut impl ToOutputArray) -> Result<()>

Returns output quality map that was generated during computation, if supported by the algorithm

fn empty(&self) -> Result<bool>

Implements Algorithm::empty()

impl QualityBaseTraitConst for Ptr<QualitySSIM>

fn as_raw_QualityBase(&self) -> *const c_void

fn get_quality_map(&self, dst: &mut impl ToOutputArray) -> Result<()>

Returns output quality map that was generated during computation, if supported by the algorithm

fn empty(&self) -> Result<bool>

Implements Algorithm::empty()

impl QualityGMSDTrait for Ptr<QualityGMSD>

fn as_raw_mut_QualityGMSD(&mut self) -> *mut c_void

fn compute(&mut self, cmp: &impl ToInputArray) -> Result<Scalar>

Compute GMSD

fn clear(&mut self) -> Result<()>

Implements Algorithm::clear()

impl QualityGMSDTraitConst for Ptr<QualityGMSD>

fn as_raw_QualityGMSD(&self) -> *const c_void

fn empty(&self) -> Result<bool>

Implements Algorithm::empty()

impl QualityMSETrait for Ptr<QualityMSE>

fn as_raw_mut_QualityMSE(&mut self) -> *mut c_void

fn compute(&mut self, cmp_imgs: &impl ToInputArray) -> Result<Scalar>

Computes MSE for reference images supplied in class constructor and provided comparison images

fn clear(&mut self) -> Result<()>

Implements Algorithm::clear()

impl QualityMSETraitConst for Ptr<QualityMSE>

fn as_raw_QualityMSE(&self) -> *const c_void

fn empty(&self) -> Result<bool>

Implements Algorithm::empty()

impl QualityPSNRTrait for Ptr<QualityPSNR>

fn as_raw_mut_QualityPSNR(&mut self) -> *mut c_void

fn compute(&mut self, cmp: &impl ToInputArray) -> Result<Scalar>

Compute the PSNR

fn clear(&mut self) -> Result<()>

Implements Algorithm::clear()

fn set_max_pixel_value(&mut self, val: f64) -> Result<()>

sets the maximum pixel value used for PSNR computation

impl QualityPSNRTraitConst for Ptr<QualityPSNR>

fn as_raw_QualityPSNR(&self) -> *const c_void

fn empty(&self) -> Result<bool>

Implements Algorithm::empty()

fn get_max_pixel_value(&self) -> Result<f64>

return the maximum pixel value used for PSNR computation

impl QualitySSIMTrait for Ptr<QualitySSIM>

fn as_raw_mut_QualitySSIM(&mut self) -> *mut c_void

fn compute(&mut self, cmp: &impl ToInputArray) -> Result<Scalar>

Computes SSIM

fn clear(&mut self) -> Result<()>

Implements Algorithm::clear()

impl QualitySSIMTraitConst for Ptr<QualitySSIM>

fn as_raw_QualitySSIM(&self) -> *const c_void

fn empty(&self) -> Result<bool>

Implements Algorithm::empty()

impl QuantizeLayerTrait for Ptr<QuantizeLayer>

fn as_raw_mut_QuantizeLayer(&mut self) -> *mut c_void

fn set_scales(&mut self, val: Vector<f32>)

fn set_zeropoints(&mut self, val: Vector<i32>)

impl QuantizeLayerTraitConst for Ptr<QuantizeLayer>

fn as_raw_QuantizeLayer(&self) -> *const c_void

fn scales(&self) -> Vector<f32>

fn zeropoints(&self) -> Vector<i32>

impl QuasiDenseStereoTrait for Ptr<QuasiDenseStereo>

fn as_raw_mut_QuasiDenseStereo(&mut self) -> *mut c_void

fn set_param(&mut self, val: PropagationParameters)

fn load_parameters(&mut self, filepath: &str) -> Result<i32>

Load a file containing the configuration parameters of the class.

fn save_parameters(&mut self, filepath: &str) -> Result<i32>

Save a file containing all the configuration parameters the class is currently set to.

fn get_sparse_matches( &mut self, s_matches: &mut Vector<MatchQuasiDense> ) -> Result<()>

Get The sparse corresponding points.

fn get_dense_matches( &mut self, dense_matches: &mut Vector<MatchQuasiDense> ) -> Result<()>

Get The dense corresponding points.

fn process( &mut self, img_left: &impl MatTraitConst, img_right: &impl MatTraitConst ) -> Result<()>

Main process of the algorithm. This method computes the sparse seeds and then densifies them.

fn get_match(&mut self, x: i32, y: i32) -> Result<Point2f>

Specify pixel coordinates in the left image and get its corresponding location in the right image.

fn get_disparity(&mut self) -> Result<Mat>

Compute and return the disparity map based on the correspondences found in the “process” method.

impl QuasiDenseStereoTraitConst for Ptr<QuasiDenseStereo>

fn as_raw_QuasiDenseStereo(&self) -> *const c_void

fn param(&self) -> PropagationParameters

impl RFFeatureGetterTrait for Ptr<RFFeatureGetter>

fn as_raw_mut_RFFeatureGetter(&mut self) -> *mut c_void

impl RFFeatureGetterTraitConst for Ptr<RFFeatureGetter>

fn as_raw_RFFeatureGetter(&self) -> *const c_void

fn get_features( &self, src: &impl MatTraitConst, features: &mut impl MatTrait, gnrm_rad: i32, gsmth_rad: i32, shrink: i32, out_num: i32, grad_num: i32 ) -> Result<()>

!

impl RICInterpolatorTrait for Ptr<RICInterpolator>

fn as_raw_mut_RICInterpolator(&mut self) -> *mut c_void

fn set_k(&mut self, k: i32) -> Result<()>

K is a number of nearest-neighbor matches considered, when fitting a locally affine model for a superpixel segment. However, lower values would make the interpolation noticeably faster. The original implementation of Hu2017 uses 32.

fn set_k_def(&mut self) -> Result<()>

K is a number of nearest-neighbor matches considered, when fitting a locally affine model for a superpixel segment. However, lower values would make the interpolation noticeably faster. The original implementation of Hu2017 uses 32.

fn set_cost_map(&mut self, cost_map: &impl MatTraitConst) -> Result<()>

Interface to provide a more elaborated cost map, i.e. edge map, for the edge-aware term. This implementation is based on a rather simple gradient-based edge map estimation. To used more complex edge map estimator (e.g. StructuredEdgeDetection that has been used in the original publication) that may lead to improved accuracies, the internal edge map estimation can be bypassed here.

fn set_superpixel_size(&mut self, sp_size: i32) -> Result<()>

Get the internal cost, i.e. edge map, used for estimating the edge-aware term.

fn set_superpixel_size_def(&mut self) -> Result<()>

Get the internal cost, i.e. edge map, used for estimating the edge-aware term.

fn set_superpixel_nn_cnt(&mut self, sp_nn: i32) -> Result<()>

Parameter defines the number of nearest-neighbor matches for each superpixel considered, when fitting a locally affine model.

fn set_superpixel_nn_cnt_def(&mut self) -> Result<()>

Parameter defines the number of nearest-neighbor matches for each superpixel considered, when fitting a locally affine model.

fn set_superpixel_ruler(&mut self, ruler: f32) -> Result<()>

Parameter to tune enforcement of superpixel smoothness factor used for oversegmentation.

fn set_superpixel_ruler_def(&mut self) -> Result<()>

Parameter to tune enforcement of superpixel smoothness factor used for oversegmentation.

fn set_superpixel_mode(&mut self, mode: i32) -> Result<()>

Parameter to choose superpixel algorithm variant to use:

fn set_superpixel_mode_def(&mut self) -> Result<()>

Parameter to choose superpixel algorithm variant to use:

fn set_alpha(&mut self, alpha: f32) -> Result<()>

Alpha is a parameter defining a global weight for transforming geodesic distance into weight.

fn set_alpha_def(&mut self) -> Result<()>

Alpha is a parameter defining a global weight for transforming geodesic distance into weight.

fn set_model_iter(&mut self, model_iter: i32) -> Result<()>

Parameter defining the number of iterations for piece-wise affine model estimation.

fn set_model_iter_def(&mut self) -> Result<()>

Parameter defining the number of iterations for piece-wise affine model estimation.

fn set_refine_models(&mut self, refine_modles: bool) -> Result<()>

Parameter to choose wether additional refinement of the piece-wise affine models is employed.

fn set_refine_models_def(&mut self) -> Result<()>

Parameter to choose wether additional refinement of the piece-wise affine models is employed.

fn set_max_flow(&mut self, max_flow: f32) -> Result<()>

MaxFlow is a threshold to validate the predictions using a certain piece-wise affine model. If the prediction exceeds the treshold the translational model will be applied instead.

fn set_max_flow_def(&mut self) -> Result<()>

MaxFlow is a threshold to validate the predictions using a certain piece-wise affine model. If the prediction exceeds the treshold the translational model will be applied instead.

fn set_use_variational_refinement( &mut self, use_variational_refinement: bool ) -> Result<()>

Parameter to choose wether the VariationalRefinement post-processing is employed.

fn set_use_variational_refinement_def(&mut self) -> Result<()>

Parameter to choose wether the VariationalRefinement post-processing is employed.

fn set_use_global_smoother_filter(&mut self, use_fgs: bool) -> Result<()>

Sets whether the fastGlobalSmootherFilter() post-processing is employed.

fn set_use_global_smoother_filter_def(&mut self) -> Result<()>

Sets whether the fastGlobalSmootherFilter() post-processing is employed.

fn set_fgs_lambda(&mut self, lambda: f32) -> Result<()>

Sets the respective fastGlobalSmootherFilter() parameter.

fn set_fgs_lambda_def(&mut self) -> Result<()>

Sets the respective fastGlobalSmootherFilter() parameter.

fn set_fgs_sigma(&mut self, sigma: f32) -> Result<()>

Sets the respective fastGlobalSmootherFilter() parameter.

fn set_fgs_sigma_def(&mut self) -> Result<()>

Sets the respective fastGlobalSmootherFilter() parameter.

impl RICInterpolatorTraitConst for Ptr<RICInterpolator>

fn as_raw_RICInterpolator(&self) -> *const c_void

fn get_k(&self) -> Result<i32>

K is a number of nearest-neighbor matches considered, when fitting a locally affine model for a superpixel segment. However, lower values would make the interpolation noticeably faster. The original implementation of Hu2017 uses 32.

fn get_superpixel_size(&self) -> Result<i32>

Get the internal cost, i.e. edge map, used for estimating the edge-aware term.

fn get_superpixel_nn_cnt(&self) -> Result<i32>

Parameter defines the number of nearest-neighbor matches for each superpixel considered, when fitting a locally affine model.

fn get_superpixel_ruler(&self) -> Result<f32>

Parameter to tune enforcement of superpixel smoothness factor used for oversegmentation.

fn get_superpixel_mode(&self) -> Result<i32>

Parameter to choose superpixel algorithm variant to use:

fn get_alpha(&self) -> Result<f32>

Alpha is a parameter defining a global weight for transforming geodesic distance into weight.

fn get_model_iter(&self) -> Result<i32>

Parameter defining the number of iterations for piece-wise affine model estimation.

fn get_refine_models(&self) -> Result<bool>

Parameter to choose wether additional refinement of the piece-wise affine models is employed.

fn get_max_flow(&self) -> Result<f32>

MaxFlow is a threshold to validate the predictions using a certain piece-wise affine model. If the prediction exceeds the treshold the translational model will be applied instead.

fn get_use_variational_refinement(&self) -> Result<bool>

Parameter to choose wether the VariationalRefinement post-processing is employed.

fn get_use_global_smoother_filter(&self) -> Result<bool>

Sets whether the fastGlobalSmootherFilter() post-processing is employed.

fn get_fgs_lambda(&self) -> Result<f32>

Sets the respective fastGlobalSmootherFilter() parameter.

fn get_fgs_sigma(&self) -> Result<f32>

Sets the respective fastGlobalSmootherFilter() parameter.

impl RLOFOpticalFlowParameterTrait for Ptr<RLOFOpticalFlowParameter>

fn as_raw_mut_RLOFOpticalFlowParameter(&mut self) -> *mut c_void

fn set_solver_type(&mut self, val: SolverType)

fn set_support_region_type(&mut self, val: SupportRegionType)

fn set_norm_sigma0(&mut self, val: f32)

fn set_norm_sigma1(&mut self, val: f32)

fn set_small_win_size(&mut self, val: i32)

fn set_large_win_size(&mut self, val: i32)

fn set_cross_segmentation_threshold(&mut self, val: i32)

fn set_max_level(&mut self, val: i32)

fn set_use_initial_flow(&mut self, val: bool)

fn set_use_illumination_model(&mut self, val: bool)

fn set_use_global_motion_prior(&mut self, val: bool)

fn set_max_iteration(&mut self, val: i32)

fn set_min_eigen_value(&mut self, val: f32)

fn set_global_motion_ransac_threshold(&mut self, val: f32)

fn set_use_m_estimator(&mut self, val: bool) -> Result<()>

Enable M-estimator or disable and use least-square estimator. Enables M-estimator by setting sigma parameters to (3.2, 7.0). Disabling M-estimator can reduce * runtime, while enabling can improve the accuracy.

fn set_solver_type_1(&mut self, val: SolverType) -> Result<()>

fn set_support_region_type_1(&mut self, val: SupportRegionType) -> Result<()>

fn set_norm_sigma0_1(&mut self, val: f32) -> Result<()>

fn set_norm_sigma1_1(&mut self, val: f32) -> Result<()>

fn set_small_win_size_1(&mut self, val: i32) -> Result<()>

fn set_large_win_size_1(&mut self, val: i32) -> Result<()>

fn set_cross_segmentation_threshold_1(&mut self, val: i32) -> Result<()>

fn set_max_level_1(&mut self, val: i32) -> Result<()>

fn set_use_initial_flow_1(&mut self, val: bool) -> Result<()>

fn set_use_illumination_model_1(&mut self, val: bool) -> Result<()>

fn set_use_global_motion_prior_1(&mut self, val: bool) -> Result<()>

fn set_max_iteration_1(&mut self, val: i32) -> Result<()>

fn set_min_eigen_value_1(&mut self, val: f32) -> Result<()>

fn set_global_motion_ransac_threshold_1(&mut self, val: f32) -> Result<()>

impl RLOFOpticalFlowParameterTraitConst for Ptr<RLOFOpticalFlowParameter>

fn as_raw_RLOFOpticalFlowParameter(&self) -> *const c_void

fn solver_type(&self) -> SolverType

fn support_region_type(&self) -> SupportRegionType

fn norm_sigma0(&self) -> f32

fn norm_sigma1(&self) -> f32

fn small_win_size(&self) -> i32

fn large_win_size(&self) -> i32

fn cross_segmentation_threshold(&self) -> i32

fn max_level(&self) -> i32

fn use_initial_flow(&self) -> bool

fn use_illumination_model(&self) -> bool

fn use_global_motion_prior(&self) -> bool

fn max_iteration(&self) -> i32

fn min_eigen_value(&self) -> f32

fn global_motion_ransac_threshold(&self) -> f32

fn get_solver_type(&self) -> Result<SolverType>

fn get_support_region_type(&self) -> Result<SupportRegionType>

fn get_norm_sigma0(&self) -> Result<f32>

fn get_norm_sigma1(&self) -> Result<f32>

fn get_small_win_size(&self) -> Result<i32>

fn get_large_win_size(&self) -> Result<i32>

fn get_cross_segmentation_threshold(&self) -> Result<i32>

fn get_max_level(&self) -> Result<i32>

fn get_use_initial_flow(&self) -> Result<bool>

fn get_use_illumination_model(&self) -> Result<bool>

fn get_use_global_motion_prior(&self) -> Result<bool>

fn get_max_iteration(&self) -> Result<i32>

fn get_min_eigen_value(&self) -> Result<f32>

fn get_global_motion_ransac_threshold(&self) -> Result<f32>

impl RNNLayerTrait for Ptr<RNNLayer>

fn as_raw_mut_RNNLayer(&mut self) -> *mut c_void

fn set_weights( &mut self, wxh: &impl MatTraitConst, bh: &impl MatTraitConst, whh: &impl MatTraitConst, who: &impl MatTraitConst, bo: &impl MatTraitConst ) -> Result<()>

Setups learned weights.

fn set_produce_hidden_output(&mut self, produce: bool) -> Result<()>

If this flag is set to true then layer will produce @f$ h_t @f$ as second output. @details Shape of the second output is the same as first output.

fn set_produce_hidden_output_def(&mut self) -> Result<()>

If this flag is set to true then layer will produce @f$ h_t @f$ as second output. @details Shape of the second output is the same as first output.

impl RNNLayerTraitConst for Ptr<RNNLayer>

fn as_raw_RNNLayer(&self) -> *const c_void

impl RTreesTrait for Ptr<RTrees>

fn as_raw_mut_RTrees(&mut self) -> *mut c_void

fn set_calculate_var_importance(&mut self, val: bool) -> Result<()>

If true then variable importance will be calculated and then it can be retrieved by RTrees::getVarImportance. Default value is false.

fn set_active_var_count(&mut self, val: i32) -> Result<()>

The size of the randomly selected subset of features at each tree node and that are used to find the best split(s). If you set it to 0 then the size will be set to the square root of the total number of features. Default value is 0.

fn set_term_criteria(&mut self, val: TermCriteria) -> Result<()>

The termination criteria that specifies when the training algorithm stops. Either when the specified number of trees is trained and added to the ensemble or when sufficient accuracy (measured as OOB error) is achieved. Typically the more trees you have the better the accuracy. However, the improvement in accuracy generally diminishes and asymptotes pass a certain number of trees. Also to keep in mind, the number of tree increases the prediction time linearly. Default value is TermCriteria(TermCriteria::MAX_ITERS + TermCriteria::EPS, 50, 0.1)

impl RTreesTraitConst for Ptr<RTrees>

fn as_raw_RTrees(&self) -> *const c_void

fn get_calculate_var_importance(&self) -> Result<bool>

If true then variable importance will be calculated and then it can be retrieved by RTrees::getVarImportance. Default value is false.

fn get_active_var_count(&self) -> Result<i32>

The size of the randomly selected subset of features at each tree node and that are used to find the best split(s). If you set it to 0 then the size will be set to the square root of the total number of features. Default value is 0.

fn get_term_criteria(&self) -> Result<TermCriteria>

The termination criteria that specifies when the training algorithm stops. Either when the specified number of trees is trained and added to the ensemble or when sufficient accuracy (measured as OOB error) is achieved. Typically the more trees you have the better the accuracy. However, the improvement in accuracy generally diminishes and asymptotes pass a certain number of trees. Also to keep in mind, the number of tree increases the prediction time linearly. Default value is TermCriteria(TermCriteria::MAX_ITERS + TermCriteria::EPS, 50, 0.1)

fn get_var_importance(&self) -> Result<Mat>

Returns the variable importance array. The method returns the variable importance vector, computed at the training stage when CalculateVarImportance is set to true. If this flag was set to false, the empty matrix is returned.

fn get_votes( &self, samples: &impl ToInputArray, results: &mut impl ToOutputArray, flags: i32 ) -> Result<()>

Returns the result of each individual tree in the forest. In case the model is a regression problem, the method will return each of the trees’ results for each of the sample cases. If the model is a classifier, it will return a Mat with samples + 1 rows, where the first row gives the class number and the following rows return the votes each class had for each sample.

fn get_oob_error(&self) -> Result<f64>

impl RadialVarianceHashTrait for Ptr<RadialVarianceHash>

fn as_raw_mut_RadialVarianceHash(&mut self) -> *mut c_void

fn set_num_of_angle_line(&mut self, value: i32) -> Result<()>

fn set_sigma(&mut self, value: f64) -> Result<()>

fn get_features(&mut self) -> Result<Vector<f64>>

fn get_hash(&mut self) -> Result<Mat>

fn get_pix_per_line(&mut self, input: &impl MatTraitConst) -> Result<Mat>

fn get_projection(&mut self) -> Result<Mat>

impl RadialVarianceHashTraitConst for Ptr<RadialVarianceHash>

fn as_raw_RadialVarianceHash(&self) -> *const c_void

fn get_num_of_angle_line(&self) -> Result<i32>

fn get_sigma(&self) -> Result<f64>

impl Rapid_GOSTrackerTrait for Ptr<Rapid_GOSTracker>

fn as_raw_mut_Rapid_GOSTracker(&mut self) -> *mut c_void

impl Rapid_GOSTrackerTraitConst for Ptr<Rapid_GOSTracker>

fn as_raw_Rapid_GOSTracker(&self) -> *const c_void

impl Rapid_OLSTrackerTrait for Ptr<Rapid_OLSTracker>

fn as_raw_mut_Rapid_OLSTracker(&mut self) -> *mut c_void

impl Rapid_OLSTrackerTraitConst for Ptr<Rapid_OLSTracker>

fn as_raw_Rapid_OLSTracker(&self) -> *const c_void

impl Rapid_RapidTrait for Ptr<Rapid_Rapid>

fn as_raw_mut_Rapid_Rapid(&mut self) -> *mut c_void

impl Rapid_RapidTraitConst for Ptr<Rapid_Rapid>

fn as_raw_Rapid_Rapid(&self) -> *const c_void

impl Rapid_TrackerTrait for Ptr<Rapid_GOSTracker>

fn as_raw_mut_Rapid_Tracker(&mut self) -> *mut c_void

fn compute( &mut self, img: &impl ToInputArray, num: i32, len: i32, k: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray, termcrit: TermCriteria ) -> Result<f32>

C++ default parameters

fn compute_def( &mut self, img: &impl ToInputArray, num: i32, len: i32, k: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray ) -> Result<f32>

Note

fn clear_state(&mut self) -> Result<()>

impl Rapid_TrackerTrait for Ptr<Rapid_OLSTracker>

fn as_raw_mut_Rapid_Tracker(&mut self) -> *mut c_void

fn compute( &mut self, img: &impl ToInputArray, num: i32, len: i32, k: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray, termcrit: TermCriteria ) -> Result<f32>

C++ default parameters

fn compute_def( &mut self, img: &impl ToInputArray, num: i32, len: i32, k: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray ) -> Result<f32>

Note

fn clear_state(&mut self) -> Result<()>

impl Rapid_TrackerTrait for Ptr<Rapid_Rapid>

fn as_raw_mut_Rapid_Tracker(&mut self) -> *mut c_void

fn compute( &mut self, img: &impl ToInputArray, num: i32, len: i32, k: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray, termcrit: TermCriteria ) -> Result<f32>

C++ default parameters

fn compute_def( &mut self, img: &impl ToInputArray, num: i32, len: i32, k: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray ) -> Result<f32>

Note

fn clear_state(&mut self) -> Result<()>

impl Rapid_TrackerTrait for Ptr<Rapid_Tracker>

fn as_raw_mut_Rapid_Tracker(&mut self) -> *mut c_void

fn compute( &mut self, img: &impl ToInputArray, num: i32, len: i32, k: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray, termcrit: TermCriteria ) -> Result<f32>

C++ default parameters

fn compute_def( &mut self, img: &impl ToInputArray, num: i32, len: i32, k: &impl ToInputArray, rvec: &mut impl ToInputOutputArray, tvec: &mut impl ToInputOutputArray ) -> Result<f32>

Note

fn clear_state(&mut self) -> Result<()>

impl Rapid_TrackerTraitConst for Ptr<Rapid_GOSTracker>

fn as_raw_Rapid_Tracker(&self) -> *const c_void

impl Rapid_TrackerTraitConst for Ptr<Rapid_OLSTracker>

fn as_raw_Rapid_Tracker(&self) -> *const c_void

impl Rapid_TrackerTraitConst for Ptr<Rapid_Rapid>

fn as_raw_Rapid_Tracker(&self) -> *const c_void

impl Rapid_TrackerTraitConst for Ptr<Rapid_Tracker>

fn as_raw_Rapid_Tracker(&self) -> *const c_void

impl ReLU6LayerTrait for Ptr<ReLU6Layer>

fn as_raw_mut_ReLU6Layer(&mut self) -> *mut c_void

fn set_min_value(&mut self, val: f32)

fn set_max_value(&mut self, val: f32)

impl ReLU6LayerTraitConst for Ptr<ReLU6Layer>

fn as_raw_ReLU6Layer(&self) -> *const c_void

fn min_value(&self) -> f32

fn max_value(&self) -> f32

impl ReLULayerTrait for Ptr<ReLULayer>

fn as_raw_mut_ReLULayer(&mut self) -> *mut c_void

fn set_negative_slope(&mut self, val: f32)

impl ReLULayerTraitConst for Ptr<ReLULayer>

fn as_raw_ReLULayer(&self) -> *const c_void

fn negative_slope(&self) -> f32

impl ReciprocalLayerTrait for Ptr<ReciprocalLayer>

fn as_raw_mut_ReciprocalLayer(&mut self) -> *mut c_void

impl ReciprocalLayerTraitConst for Ptr<ReciprocalLayer>

fn as_raw_ReciprocalLayer(&self) -> *const c_void

impl ReduceLayerTrait for Ptr<ReduceLayer>

fn as_raw_mut_ReduceLayer(&mut self) -> *mut c_void

impl ReduceLayerTraitConst for Ptr<ReduceLayer>

fn as_raw_ReduceLayer(&self) -> *const c_void

impl RegionLayerTrait for Ptr<RegionLayer>

fn as_raw_mut_RegionLayer(&mut self) -> *mut c_void

fn set_nms_threshold(&mut self, val: f32)

impl RegionLayerTraitConst for Ptr<RegionLayer>

fn as_raw_RegionLayer(&self) -> *const c_void

fn nms_threshold(&self) -> f32

impl ReorgLayerTrait for Ptr<ReorgLayer>

fn as_raw_mut_ReorgLayer(&mut self) -> *mut c_void

impl ReorgLayerTraitConst for Ptr<ReorgLayer>

fn as_raw_ReorgLayer(&self) -> *const c_void

impl RequantizeLayerTrait for Ptr<RequantizeLayer>

fn as_raw_mut_RequantizeLayer(&mut self) -> *mut c_void

fn set_scale(&mut self, val: f32)

fn set_shift(&mut self, val: f32)

impl RequantizeLayerTraitConst for Ptr<RequantizeLayer>

fn as_raw_RequantizeLayer(&self) -> *const c_void

fn scale(&self) -> f32

fn shift(&self) -> f32

impl ReshapeLayerTrait for Ptr<ReshapeLayer>

fn as_raw_mut_ReshapeLayer(&mut self) -> *mut c_void

fn set_new_shape_desc(&mut self, val: MatShape)

fn set_new_shape_range(&mut self, val: Range)

impl ReshapeLayerTraitConst for Ptr<ReshapeLayer>

fn as_raw_ReshapeLayer(&self) -> *const c_void

fn new_shape_desc(&self) -> MatShape

fn new_shape_range(&self) -> Range

impl ResizeLayerTrait for Ptr<ResizeLayer>

fn as_raw_mut_ResizeLayer(&mut self) -> *mut c_void

impl ResizeLayerTraitConst for Ptr<ResizeLayer>

fn as_raw_ResizeLayer(&self) -> *const c_void

impl RetinaFastToneMappingTrait for Ptr<RetinaFastToneMapping>

fn as_raw_mut_RetinaFastToneMapping(&mut self) -> *mut c_void

fn apply_fast_tone_mapping( &mut self, input_image: &impl ToInputArray, output_tone_mapped_image: &mut impl ToOutputArray ) -> Result<()>

applies a luminance correction (initially High Dynamic Range (HDR) tone mapping)

fn setup( &mut self, photoreceptors_neighborhood_radius: f32, ganglioncells_neighborhood_radius: f32, mean_luminance_modulator_k: f32 ) -> Result<()>

updates tone mapping behaviors by adjusing the local luminance computation area

fn setup_def(&mut self) -> Result<()>

updates tone mapping behaviors by adjusing the local luminance computation area

impl RetinaFastToneMappingTraitConst for Ptr<RetinaFastToneMapping>

fn as_raw_RetinaFastToneMapping(&self) -> *const c_void

impl RetinaTrait for Ptr<Retina>

fn as_raw_mut_Retina(&mut self) -> *mut c_void

fn get_input_size(&mut self) -> Result<Size>

Retreive retina input buffer size

fn get_output_size(&mut self) -> Result<Size>

Retreive retina output buffer size that can be different from the input if a spatial log transformation is applied

fn setup_from_file( &mut self, retina_parameter_file: &str, apply_default_setup_on_failure: bool ) -> Result<()>

Try to open an XML retina parameters file to adjust current retina instance setup

fn setup_from_file_def(&mut self) -> Result<()>

Try to open an XML retina parameters file to adjust current retina instance setup

fn setup_from_storage( &mut self, fs: &mut impl FileStorageTrait, apply_default_setup_on_failure: bool ) -> Result<()>

Try to open an XML retina parameters file to adjust current retina instance setup

fn setup_from_storage_def( &mut self, fs: &mut impl FileStorageTrait ) -> Result<()>

@overload

fn setup(&mut self, new_parameters: impl RetinaParametersTrait) -> Result<()>

Try to open an XML retina parameters file to adjust current retina instance setup

fn get_parameters(&mut self) -> Result<RetinaParameters>

Returns

fn print_setup(&mut self) -> Result<String>

Outputs a string showing the used parameters setup

fn setup_op_land_ipl_parvo_channel( &mut self, color_mode: bool, normalise_output: bool, photoreceptors_local_adaptation_sensitivity: f32, photoreceptors_temporal_constant: f32, photoreceptors_spatial_constant: f32, horizontal_cells_gain: f32, hcells_temporal_constant: f32, hcells_spatial_constant: f32, ganglion_cells_sensitivity: f32 ) -> Result<()>

Setup the OPL and IPL parvo channels (see biologocal model)

fn setup_op_land_ipl_parvo_channel_def(&mut self) -> Result<()>

Setup the OPL and IPL parvo channels (see biologocal model)

fn setup_ipl_magno_channel( &mut self, normalise_output: bool, parasol_cells_beta: f32, parasol_cells_tau: f32, parasol_cells_k: f32, amacrin_cells_temporal_cut_frequency: f32, v0_compression_parameter: f32, local_adaptintegration_tau: f32, local_adaptintegration_k: f32 ) -> Result<()>

Set parameters values for the Inner Plexiform Layer (IPL) magnocellular channel

fn setup_ipl_magno_channel_def(&mut self) -> Result<()>

Set parameters values for the Inner Plexiform Layer (IPL) magnocellular channel

fn run(&mut self, input_image: &impl ToInputArray) -> Result<()>

Method which allows retina to be applied on an input image,

fn apply_fast_tone_mapping( &mut self, input_image: &impl ToInputArray, output_tone_mapped_image: &mut impl ToOutputArray ) -> Result<()>

Method which processes an image in the aim to correct its luminance correct backlight problems, enhance details in shadows.

fn get_parvo( &mut self, retina_output_parvo: &mut impl ToOutputArray ) -> Result<()>

Accessor of the details channel of the retina (models foveal vision).

fn get_parvo_raw_to( &mut self, retina_output_parvo: &mut impl ToOutputArray ) -> Result<()>

Accessor of the details channel of the retina (models foveal vision).

fn get_magno( &mut self, retina_output_magno: &mut impl ToOutputArray ) -> Result<()>

Accessor of the motion channel of the retina (models peripheral vision).

fn get_magno_raw_to( &mut self, retina_output_magno: &mut impl ToOutputArray ) -> Result<()>

Accessor of the motion channel of the retina (models peripheral vision).

fn set_color_saturation( &mut self, saturate_colors: bool, color_saturation_value: f32 ) -> Result<()>

Activate color saturation as the final step of the color demultiplexing process -> this saturation is a sigmoide function applied to each channel of the demultiplexed image.

fn set_color_saturation_def(&mut self) -> Result<()>

Activate color saturation as the final step of the color demultiplexing process -> this saturation is a sigmoide function applied to each channel of the demultiplexed image.

fn clear_buffers(&mut self) -> Result<()>

Clears all retina buffers

fn activate_moving_contours_processing(&mut self, activate: bool) -> Result<()>

Activate/desactivate the Magnocellular pathway processing (motion information extraction), by default, it is activated

fn activate_contours_processing(&mut self, activate: bool) -> Result<()>

Activate/desactivate the Parvocellular pathway processing (contours information extraction), by default, it is activated

impl RetinaTraitConst for Ptr<Retina>

fn as_raw_Retina(&self) -> *const c_void

fn write(&self, fs: &str) -> Result<()>

Write xml/yml formated parameters information

fn write_to_storage(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Write xml/yml formated parameters information

fn get_magno_raw(&self) -> Result<Mat>

Accessor of the motion channel of the retina (models peripheral vision).

fn get_parvo_raw(&self) -> Result<Mat>

Accessor of the details channel of the retina (models foveal vision).

impl RgbdFrameTrait for Ptr<OdometryFrame>

fn as_raw_mut_RgbdFrame(&mut self) -> *mut c_void

fn set_id(&mut self, val: i32)

fn set_image(&mut self, val: Mat)

fn set_depth(&mut self, val: Mat)

fn set_mask(&mut self, val: Mat)

fn set_normals(&mut self, val: Mat)

fn release(&mut self) -> Result<()>

impl RgbdFrameTrait for Ptr<RgbdFrame>

fn as_raw_mut_RgbdFrame(&mut self) -> *mut c_void

fn set_id(&mut self, val: i32)

fn set_image(&mut self, val: Mat)

fn set_depth(&mut self, val: Mat)

fn set_mask(&mut self, val: Mat)

fn set_normals(&mut self, val: Mat)

fn release(&mut self) -> Result<()>

impl RgbdFrameTraitConst for Ptr<OdometryFrame>

fn as_raw_RgbdFrame(&self) -> *const c_void

fn id(&self) -> i32

fn image(&self) -> Mat

fn depth(&self) -> Mat

fn mask(&self) -> Mat

fn normals(&self) -> Mat

impl RgbdFrameTraitConst for Ptr<RgbdFrame>

fn as_raw_RgbdFrame(&self) -> *const c_void

fn id(&self) -> i32

fn image(&self) -> Mat

fn depth(&self) -> Mat

fn mask(&self) -> Mat

fn normals(&self) -> Mat

impl RgbdICPOdometryTrait for Ptr<RgbdICPOdometry>

fn as_raw_mut_RgbdICPOdometry(&mut self) -> *mut c_void

fn set_camera_matrix(&mut self, val: &impl MatTraitConst) -> Result<()>

fn set_min_depth(&mut self, val: f64) -> Result<()>

fn set_max_depth(&mut self, val: f64) -> Result<()>

fn set_max_depth_diff(&mut self, val: f64) -> Result<()>

fn set_max_points_part(&mut self, val: f64) -> Result<()>

fn set_iteration_counts(&mut self, val: &impl MatTraitConst) -> Result<()>

fn set_min_gradient_magnitudes( &mut self, val: &impl MatTraitConst ) -> Result<()>

fn set_transform_type(&mut self, val: i32) -> Result<()>

fn set_max_translation(&mut self, val: f64) -> Result<()>

fn set_max_rotation(&mut self, val: f64) -> Result<()>

impl RgbdICPOdometryTraitConst for Ptr<RgbdICPOdometry>

fn as_raw_RgbdICPOdometry(&self) -> *const c_void

fn prepare_frame_cache( &self, frame: &mut Ptr<OdometryFrame>, cache_type: i32 ) -> Result<Size>

fn get_camera_matrix(&self) -> Result<Mat>

fn get_min_depth(&self) -> Result<f64>

fn get_max_depth(&self) -> Result<f64>

fn get_max_depth_diff(&self) -> Result<f64>

fn get_max_points_part(&self) -> Result<f64>

fn get_iteration_counts(&self) -> Result<Mat>

fn get_min_gradient_magnitudes(&self) -> Result<Mat>

fn get_transform_type(&self) -> Result<i32>

fn get_max_translation(&self) -> Result<f64>

fn get_max_rotation(&self) -> Result<f64>

fn get_normals_computer(&self) -> Result<Ptr<RgbdNormals>>

impl RgbdNormalsTrait for Ptr<RgbdNormals>

fn as_raw_mut_RgbdNormals(&mut self) -> *mut c_void

fn set_rows(&mut self, val: i32) -> Result<()>

fn set_cols(&mut self, val: i32) -> Result<()>

fn set_window_size(&mut self, val: i32) -> Result<()>

fn set_depth(&mut self, val: i32) -> Result<()>

fn set_k(&mut self, val: &impl MatTraitConst) -> Result<()>

fn set_method(&mut self, val: i32) -> Result<()>

impl RgbdNormalsTraitConst for Ptr<RgbdNormals>

fn as_raw_RgbdNormals(&self) -> *const c_void

fn apply( &self, points: &impl ToInputArray, normals: &mut impl ToOutputArray ) -> Result<()>

Given a set of 3d points in a depth image, compute the normals at each point.

fn initialize(&self) -> Result<()>

Initializes some data that is cached for later computation If that function is not called, it will be called the first time normals are computed

fn get_rows(&self) -> Result<i32>

fn get_cols(&self) -> Result<i32>

fn get_window_size(&self) -> Result<i32>

fn get_depth(&self) -> Result<i32>

fn get_k(&self) -> Result<Mat>

fn get_method(&self) -> Result<i32>

impl RgbdOdometryTrait for Ptr<RgbdOdometry>

fn as_raw_mut_RgbdOdometry(&mut self) -> *mut c_void

fn set_camera_matrix(&mut self, val: &impl MatTraitConst) -> Result<()>

fn set_min_depth(&mut self, val: f64) -> Result<()>

fn set_max_depth(&mut self, val: f64) -> Result<()>

fn set_max_depth_diff(&mut self, val: f64) -> Result<()>

fn set_iteration_counts(&mut self, val: &impl MatTraitConst) -> Result<()>

fn set_min_gradient_magnitudes( &mut self, val: &impl MatTraitConst ) -> Result<()>

fn set_max_points_part(&mut self, val: f64) -> Result<()>

fn set_transform_type(&mut self, val: i32) -> Result<()>

fn set_max_translation(&mut self, val: f64) -> Result<()>

fn set_max_rotation(&mut self, val: f64) -> Result<()>

impl RgbdOdometryTraitConst for Ptr<RgbdOdometry>

fn as_raw_RgbdOdometry(&self) -> *const c_void

fn prepare_frame_cache( &self, frame: &mut Ptr<OdometryFrame>, cache_type: i32 ) -> Result<Size>

fn get_camera_matrix(&self) -> Result<Mat>

fn get_min_depth(&self) -> Result<f64>

fn get_max_depth(&self) -> Result<f64>

fn get_max_depth_diff(&self) -> Result<f64>

fn get_iteration_counts(&self) -> Result<Mat>

fn get_min_gradient_magnitudes(&self) -> Result<Mat>

fn get_max_points_part(&self) -> Result<f64>

fn get_transform_type(&self) -> Result<i32>

fn get_max_translation(&self) -> Result<f64>

fn get_max_rotation(&self) -> Result<f64>

impl RgbdPlaneTrait for Ptr<RgbdPlane>

fn as_raw_mut_RgbdPlane(&mut self) -> *mut c_void

fn apply( &mut self, points3d: &impl ToInputArray, normals: &impl ToInputArray, mask: &mut impl ToOutputArray, plane_coefficients: &mut impl ToOutputArray ) -> Result<()>

Find The planes in a depth image

fn apply_1( &mut self, points3d: &impl ToInputArray, mask: &mut impl ToOutputArray, plane_coefficients: &mut impl ToOutputArray ) -> Result<()>

Find The planes in a depth image but without doing a normal check, which is faster but less accurate

fn set_block_size(&mut self, val: i32) -> Result<()>

fn set_min_size(&mut self, val: i32) -> Result<()>

fn set_method(&mut self, val: i32) -> Result<()>

fn set_threshold(&mut self, val: f64) -> Result<()>

fn set_sensor_error_a(&mut self, val: f64) -> Result<()>

fn set_sensor_error_b(&mut self, val: f64) -> Result<()>

fn set_sensor_error_c(&mut self, val: f64) -> Result<()>

impl RgbdPlaneTraitConst for Ptr<RgbdPlane>

fn as_raw_RgbdPlane(&self) -> *const c_void

fn get_block_size(&self) -> Result<i32>

fn get_min_size(&self) -> Result<i32>

fn get_method(&self) -> Result<i32>

fn get_threshold(&self) -> Result<f64>

fn get_sensor_error_a(&self) -> Result<f64>

fn get_sensor_error_b(&self) -> Result<f64>

fn get_sensor_error_c(&self) -> Result<f64>

impl RidgeDetectionFilterTrait for Ptr<RidgeDetectionFilter>

fn as_raw_mut_RidgeDetectionFilter(&mut self) -> *mut c_void

fn get_ridge_filtered_image( &mut self, _img: &impl ToInputArray, out: &mut impl ToOutputArray ) -> Result<()>

Apply Ridge detection filter on input image.

impl RidgeDetectionFilterTraitConst for Ptr<RidgeDetectionFilter>

fn as_raw_RidgeDetectionFilter(&self) -> *const c_void

impl RoundLayerTrait for Ptr<RoundLayer>

fn as_raw_mut_RoundLayer(&mut self) -> *mut c_void

impl RoundLayerTraitConst for Ptr<RoundLayer>

fn as_raw_RoundLayer(&self) -> *const c_void

impl SFMLibmvEuclideanReconstructionTrait for Ptr<SFMLibmvEuclideanReconstruction>

fn as_raw_mut_SFMLibmvEuclideanReconstruction(&mut self) -> *mut c_void

fn run(&mut self, points2d: &impl ToInputArray) -> Result<()>

Calls the pipeline in order to perform Eclidean reconstruction.

fn run_1( &mut self, points2d: &impl ToInputArray, k: &mut impl ToInputOutputArray, rs: &mut impl ToOutputArray, ts: &mut impl ToOutputArray, points3d: &mut impl ToOutputArray ) -> Result<()>

Calls the pipeline in order to perform Eclidean reconstruction.

fn run_2(&mut self, images: &Vector<String>) -> Result<()>

Calls the pipeline in order to perform Eclidean reconstruction.

fn run_3( &mut self, images: &Vector<String>, k: &mut impl ToInputOutputArray, rs: &mut impl ToOutputArray, ts: &mut impl ToOutputArray, points3d: &mut impl ToOutputArray ) -> Result<()>

Calls the pipeline in order to perform Eclidean reconstruction.

fn get_points(&mut self, points3d: &mut impl ToOutputArray) -> Result<()>

Returns the estimated 3d points.

fn get_cameras( &mut self, rs: &mut impl ToOutputArray, ts: &mut impl ToOutputArray ) -> Result<()>

Returns the estimated camera extrinsic parameters.

fn set_reconstruction_options( &mut self, libmv_reconstruction_options: libmv_ReconstructionOptions ) -> Result<()>

Setter method for reconstruction options.

fn set_camera_intrinsic_options( &mut self, libmv_camera_intrinsics_options: libmv_CameraIntrinsicsOptions ) -> Result<()>

Setter method for camera intrinsic options.

impl SFMLibmvEuclideanReconstructionTraitConst for Ptr<SFMLibmvEuclideanReconstruction>

fn as_raw_SFMLibmvEuclideanReconstruction(&self) -> *const c_void

fn get_error(&self) -> Result<f64>

Returns the computed reprojection error.

fn get_intrinsics(&self) -> Result<Mat>

Returns the refined camera calibration matrix.

impl SIFTTrait for Ptr<SIFT>

fn as_raw_mut_SIFT(&mut self) -> *mut c_void

fn set_n_features(&mut self, max_features: i32) -> Result<()>

fn set_n_octave_layers(&mut self, n_octave_layers: i32) -> Result<()>

fn set_contrast_threshold(&mut self, contrast_threshold: f64) -> Result<()>

fn set_edge_threshold(&mut self, edge_threshold: f64) -> Result<()>

fn set_sigma(&mut self, sigma: f64) -> Result<()>

impl SIFTTraitConst for Ptr<SIFT>

fn as_raw_SIFT(&self) -> *const c_void

fn get_default_name(&self) -> Result<String>

fn get_n_features(&self) -> Result<i32>

fn get_n_octave_layers(&self) -> Result<i32>

fn get_contrast_threshold(&self) -> Result<f64>

fn get_edge_threshold(&self) -> Result<f64>

fn get_sigma(&self) -> Result<f64>

impl SURFTrait for Ptr<SURF>

fn as_raw_mut_SURF(&mut self) -> *mut c_void

fn set_hessian_threshold(&mut self, hessian_threshold: f64) -> Result<()>

fn set_n_octaves(&mut self, n_octaves: i32) -> Result<()>

fn set_n_octave_layers(&mut self, n_octave_layers: i32) -> Result<()>

fn set_extended(&mut self, extended: bool) -> Result<()>

fn set_upright(&mut self, upright: bool) -> Result<()>

impl SURFTraitConst for Ptr<SURF>

fn as_raw_SURF(&self) -> *const c_void

fn get_hessian_threshold(&self) -> Result<f64>

fn get_n_octaves(&self) -> Result<i32>

fn get_n_octave_layers(&self) -> Result<i32>

fn get_extended(&self) -> Result<bool>

fn get_upright(&self) -> Result<bool>

fn get_default_name(&self) -> Result<String>

impl SURF_CUDATrait for Ptr<SURF_CUDA>

fn as_raw_mut_SURF_CUDA(&mut self) -> *mut c_void

fn set_hessian_threshold(&mut self, val: f64)

fn set_n_octaves(&mut self, val: i32)

fn set_n_octave_layers(&mut self, val: i32)

fn set_extended(&mut self, val: bool)

fn set_upright(&mut self, val: bool)

fn set_keypoints_ratio(&mut self, val: f32)

max keypoints = min(keypointsRatio * img.size().area(), 65535)

fn set_sum(&mut self, val: GpuMat)

fn set_mask1(&mut self, val: GpuMat)

fn set_mask_sum(&mut self, val: GpuMat)

fn set_det(&mut self, val: GpuMat)

fn set_trace(&mut self, val: GpuMat)

fn set_max_pos_buffer(&mut self, val: GpuMat)

fn upload_keypoints( &mut self, keypoints: &Vector<KeyPoint>, keypoints_gpu: &mut impl GpuMatTrait ) -> Result<()>

upload host keypoints to device memory

fn download_keypoints( &mut self, keypoints_gpu: &impl GpuMatTraitConst, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

download keypoints from device to host memory

fn download_descriptors( &mut self, descriptors_gpu: &impl GpuMatTraitConst, descriptors: &mut Vector<f32> ) -> Result<()>

download descriptors from device to host memory

fn apply( &mut self, img: &impl GpuMatTraitConst, mask: &impl GpuMatTraitConst, keypoints: &mut impl GpuMatTrait ) -> Result<()>

finds the keypoints using fast hessian detector used in SURF supports CV_8UC1 images keypoints will have nFeature cols and 6 rows keypoints.ptr(X_ROW)[i] will contain x coordinate of i’th feature keypoints.ptr(Y_ROW)[i] will contain y coordinate of i’th feature keypoints.ptr(LAPLACIAN_ROW)[i] will contain laplacian sign of i’th feature keypoints.ptr(OCTAVE_ROW)[i] will contain octave of i’th feature keypoints.ptr(SIZE_ROW)[i] will contain size of i’th feature keypoints.ptr(ANGLE_ROW)[i] will contain orientation of i’th feature keypoints.ptr(HESSIAN_ROW)[i] will contain response of i’th feature

fn apply_1( &mut self, img: &impl GpuMatTraitConst, mask: &impl GpuMatTraitConst, keypoints: &mut impl GpuMatTrait, descriptors: &mut impl GpuMatTrait, use_provided_keypoints: bool ) -> Result<()>

finds the keypoints and computes their descriptors. Optionally it can compute descriptors for the user-provided keypoints and recompute keypoints direction

fn apply_def( &mut self, img: &impl GpuMatTraitConst, mask: &impl GpuMatTraitConst, keypoints: &mut impl GpuMatTrait, descriptors: &mut impl GpuMatTrait ) -> Result<()>

finds the keypoints and computes their descriptors. Optionally it can compute descriptors for the user-provided keypoints and recompute keypoints direction

fn detect( &mut self, img: &impl GpuMatTraitConst, mask: &impl GpuMatTraitConst, keypoints: &mut impl GpuMatTrait ) -> Result<()>

Finds the keypoints using fast hessian detector used in SURF

fn apply_2( &mut self, img: &impl GpuMatTraitConst, mask: &impl GpuMatTraitConst, keypoints: &mut Vector<KeyPoint> ) -> Result<()>

fn apply_3( &mut self, img: &impl GpuMatTraitConst, mask: &impl GpuMatTraitConst, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl GpuMatTrait, use_provided_keypoints: bool ) -> Result<()>

C++ default parameters

fn apply_def_1( &mut self, img: &impl GpuMatTraitConst, mask: &impl GpuMatTraitConst, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl GpuMatTrait ) -> Result<()>

Note

fn detect_with_descriptors( &mut self, img: &impl GpuMatTraitConst, mask: &impl GpuMatTraitConst, keypoints: &mut impl GpuMatTrait, descriptors: &mut impl GpuMatTrait, use_provided_keypoints: bool ) -> Result<()>

Finds the keypoints and computes their descriptors using fast hessian detector used in SURF

fn detect_with_descriptors_def( &mut self, img: &impl GpuMatTraitConst, mask: &impl GpuMatTraitConst, keypoints: &mut impl GpuMatTrait, descriptors: &mut impl GpuMatTrait ) -> Result<()>

Finds the keypoints and computes their descriptors using fast hessian detector used in SURF

fn apply_4( &mut self, img: &impl GpuMatTraitConst, mask: &impl GpuMatTraitConst, keypoints: &mut Vector<KeyPoint>, descriptors: &mut Vector<f32>, use_provided_keypoints: bool ) -> Result<()>

C++ default parameters

fn apply_def_2( &mut self, img: &impl GpuMatTraitConst, mask: &impl GpuMatTraitConst, keypoints: &mut Vector<KeyPoint>, descriptors: &mut Vector<f32> ) -> Result<()>

Note

fn release_memory(&mut self) -> Result<()>

impl SURF_CUDATraitConst for Ptr<SURF_CUDA>

fn as_raw_SURF_CUDA(&self) -> *const c_void

fn hessian_threshold(&self) -> f64

fn n_octaves(&self) -> i32

fn n_octave_layers(&self) -> i32

fn extended(&self) -> bool

fn upright(&self) -> bool

fn keypoints_ratio(&self) -> f32

max keypoints = min(keypointsRatio * img.size().area(), 65535)

fn sum(&self) -> GpuMat

fn mask1(&self) -> GpuMat

fn mask_sum(&self) -> GpuMat

fn det(&self) -> GpuMat

fn trace(&self) -> GpuMat

fn max_pos_buffer(&self) -> GpuMat

fn descriptor_size(&self) -> Result<i32>

returns the descriptor size in float’s (64 or 128)

fn default_norm(&self) -> Result<i32>

returns the default norm type

impl SVMSGDTrait for Ptr<SVMSGD>

fn as_raw_mut_SVMSGD(&mut self) -> *mut c_void

fn get_weights(&mut self) -> Result<Mat>

Returns

fn get_shift(&mut self) -> Result<f32>

Returns

fn set_optimal_parameters( &mut self, svmsgd_type: i32, margin_type: i32 ) -> Result<()>

Function sets optimal parameters values for chosen SVM SGD model.

fn set_optimal_parameters_def(&mut self) -> Result<()>

Function sets optimal parameters values for chosen SVM SGD model.

fn set_svmsgd_type(&mut self, svmsgd_type: i32) -> Result<()>

%Algorithm type, one of SVMSGD::SvmsgdType.

fn set_margin_type(&mut self, margin_type: i32) -> Result<()>

%Margin type, one of SVMSGD::MarginType.

fn set_margin_regularization( &mut self, margin_regularization: f32 ) -> Result<()>

Parameter marginRegularization of a %SVMSGD optimization problem.

fn set_initial_step_size(&mut self, initial_step_size: f32) -> Result<()>

Parameter initialStepSize of a %SVMSGD optimization problem.

fn set_step_decreasing_power( &mut self, step_decreasing_power: f32 ) -> Result<()>

Parameter stepDecreasingPower of a %SVMSGD optimization problem.

fn set_term_criteria(&mut self, val: TermCriteria) -> Result<()>

Termination criteria of the training algorithm. You can specify the maximum number of iterations (maxCount) and/or how much the error could change between the iterations to make the algorithm continue (epsilon).

impl SVMSGDTraitConst for Ptr<SVMSGD>

fn as_raw_SVMSGD(&self) -> *const c_void

fn get_svmsgd_type(&self) -> Result<i32>

%Algorithm type, one of SVMSGD::SvmsgdType.

fn get_margin_type(&self) -> Result<i32>

%Margin type, one of SVMSGD::MarginType.

fn get_margin_regularization(&self) -> Result<f32>

Parameter marginRegularization of a %SVMSGD optimization problem.

fn get_initial_step_size(&self) -> Result<f32>

Parameter initialStepSize of a %SVMSGD optimization problem.

fn get_step_decreasing_power(&self) -> Result<f32>

Parameter stepDecreasingPower of a %SVMSGD optimization problem.

fn get_term_criteria(&self) -> Result<TermCriteria>

Termination criteria of the training algorithm. You can specify the maximum number of iterations (maxCount) and/or how much the error could change between the iterations to make the algorithm continue (epsilon).

impl SVMTrait for Ptr<SVM>

fn as_raw_mut_SVM(&mut self) -> *mut c_void

fn set_type(&mut self, val: i32) -> Result<()>

Type of a %SVM formulation. See SVM::Types. Default value is SVM::C_SVC.

fn set_gamma(&mut self, val: f64) -> Result<()>

Parameter inline formula of a kernel function. For SVM::POLY, SVM::RBF, SVM::SIGMOID or SVM::CHI2. Default value is 1.

fn set_coef0(&mut self, val: f64) -> Result<()>

Parameter coef0 of a kernel function. For SVM::POLY or SVM::SIGMOID. Default value is 0.

fn set_degree(&mut self, val: f64) -> Result<()>

Parameter degree of a kernel function. For SVM::POLY. Default value is 0.

fn set_c(&mut self, val: f64) -> Result<()>

Parameter C of a %SVM optimization problem. For SVM::C_SVC, SVM::EPS_SVR or SVM::NU_SVR. Default value is 0.

fn set_nu(&mut self, val: f64) -> Result<()>

Parameter inline formula of a %SVM optimization problem. For SVM::NU_SVC, SVM::ONE_CLASS or SVM::NU_SVR. Default value is 0.

fn set_p(&mut self, val: f64) -> Result<()>

Parameter inline formula of a %SVM optimization problem. For SVM::EPS_SVR. Default value is 0.

fn set_class_weights(&mut self, val: &impl MatTraitConst) -> Result<()>

Optional weights in the SVM::C_SVC problem, assigned to particular classes. They are multiplied by C so the parameter C of class i becomes classWeights(i) * C. Thus these weights affect the misclassification penalty for different classes. The larger weight, the larger penalty on misclassification of data from the corresponding class. Default value is empty Mat.

fn set_term_criteria(&mut self, val: TermCriteria) -> Result<()>

Termination criteria of the iterative %SVM training procedure which solves a partial case of constrained quadratic optimization problem. You can specify tolerance and/or the maximum number of iterations. Default value is TermCriteria( TermCriteria::MAX_ITER + TermCriteria::EPS, 1000, FLT_EPSILON );

fn set_kernel(&mut self, kernel_type: i32) -> Result<()>

Initialize with one of predefined kernels. See SVM::KernelTypes.

fn set_custom_kernel(&mut self, _kernel: &Ptr<SVM_Kernel>) -> Result<()>

Initialize with custom kernel. See SVM::Kernel class for implementation details

fn train_auto( &mut self, data: &Ptr<TrainData>, k_fold: i32, cgrid: impl ParamGridTrait, gamma_grid: impl ParamGridTrait, p_grid: impl ParamGridTrait, nu_grid: impl ParamGridTrait, coeff_grid: impl ParamGridTrait, degree_grid: impl ParamGridTrait, balanced: bool ) -> Result<bool>

Trains an %SVM with optimal parameters.

fn train_auto_def(&mut self, data: &Ptr<TrainData>) -> Result<bool>

Trains an %SVM with optimal parameters.

fn train_auto_with_data( &mut self, samples: &impl ToInputArray, layout: i32, responses: &impl ToInputArray, k_fold: i32, cgrid: Ptr<ParamGrid>, gamma_grid: Ptr<ParamGrid>, p_grid: Ptr<ParamGrid>, nu_grid: Ptr<ParamGrid>, coeff_grid: Ptr<ParamGrid>, degree_grid: Ptr<ParamGrid>, balanced: bool ) -> Result<bool>

Trains an %SVM with optimal parameters

fn train_auto_with_data_def( &mut self, samples: &impl ToInputArray, layout: i32, responses: &impl ToInputArray ) -> Result<bool>

Trains an %SVM with optimal parameters

impl SVMTraitConst for Ptr<SVM>

fn as_raw_SVM(&self) -> *const c_void

fn get_type(&self) -> Result<i32>

Type of a %SVM formulation. See SVM::Types. Default value is SVM::C_SVC.

fn get_gamma(&self) -> Result<f64>

Parameter inline formula of a kernel function. For SVM::POLY, SVM::RBF, SVM::SIGMOID or SVM::CHI2. Default value is 1.

fn get_coef0(&self) -> Result<f64>

Parameter coef0 of a kernel function. For SVM::POLY or SVM::SIGMOID. Default value is 0.

fn get_degree(&self) -> Result<f64>

Parameter degree of a kernel function. For SVM::POLY. Default value is 0.

fn get_c(&self) -> Result<f64>

Parameter C of a %SVM optimization problem. For SVM::C_SVC, SVM::EPS_SVR or SVM::NU_SVR. Default value is 0.

fn get_nu(&self) -> Result<f64>

Parameter inline formula of a %SVM optimization problem. For SVM::NU_SVC, SVM::ONE_CLASS or SVM::NU_SVR. Default value is 0.

fn get_p(&self) -> Result<f64>

Parameter inline formula of a %SVM optimization problem. For SVM::EPS_SVR. Default value is 0.

fn get_class_weights(&self) -> Result<Mat>

Optional weights in the SVM::C_SVC problem, assigned to particular classes. They are multiplied by C so the parameter C of class i becomes classWeights(i) * C. Thus these weights affect the misclassification penalty for different classes. The larger weight, the larger penalty on misclassification of data from the corresponding class. Default value is empty Mat.

fn get_term_criteria(&self) -> Result<TermCriteria>

Termination criteria of the iterative %SVM training procedure which solves a partial case of constrained quadratic optimization problem. You can specify tolerance and/or the maximum number of iterations. Default value is TermCriteria( TermCriteria::MAX_ITER + TermCriteria::EPS, 1000, FLT_EPSILON );

fn get_kernel_type(&self) -> Result<i32>

Type of a %SVM kernel. See SVM::KernelTypes. Default value is SVM::RBF.

fn get_support_vectors(&self) -> Result<Mat>

Retrieves all the support vectors

fn get_uncompressed_support_vectors(&self) -> Result<Mat>

Retrieves all the uncompressed support vectors of a linear %SVM

fn get_decision_function( &self, i: i32, alpha: &mut impl ToOutputArray, svidx: &mut impl ToOutputArray ) -> Result<f64>

Retrieves the decision function

impl SVM_KernelTrait for Ptr<SVM_Kernel>

fn as_raw_mut_SVM_Kernel(&mut self) -> *mut c_void

fn calc( &mut self, vcount: i32, n: i32, vecs: &f32, another: &f32, results: &mut f32 ) -> Result<()>

impl SVM_KernelTraitConst for Ptr<SVM_Kernel>

fn as_raw_SVM_Kernel(&self) -> *const c_void

fn get_type(&self) -> Result<i32>

impl SaliencyTrait for Ptr<MotionSaliency>

fn as_raw_mut_Saliency(&mut self) -> *mut c_void

fn compute_saliency( &mut self, image: &impl ToInputArray, saliency_map: &mut impl ToOutputArray ) -> Result<bool>

\brief Compute the saliency \param image The image. \param saliencyMap The computed saliency map. \return true if the saliency map is computed, false otherwise

impl SaliencyTrait for Ptr<MotionSaliencyBinWangApr2014>

fn as_raw_mut_Saliency(&mut self) -> *mut c_void

fn compute_saliency( &mut self, image: &impl ToInputArray, saliency_map: &mut impl ToOutputArray ) -> Result<bool>

\brief Compute the saliency \param image The image. \param saliencyMap The computed saliency map. \return true if the saliency map is computed, false otherwise

impl SaliencyTrait for Ptr<Objectness>

fn as_raw_mut_Saliency(&mut self) -> *mut c_void

fn compute_saliency( &mut self, image: &impl ToInputArray, saliency_map: &mut impl ToOutputArray ) -> Result<bool>

\brief Compute the saliency \param image The image. \param saliencyMap The computed saliency map. \return true if the saliency map is computed, false otherwise

impl SaliencyTrait for Ptr<ObjectnessBING>

fn as_raw_mut_Saliency(&mut self) -> *mut c_void

fn compute_saliency( &mut self, image: &impl ToInputArray, saliency_map: &mut impl ToOutputArray ) -> Result<bool>

\brief Compute the saliency \param image The image. \param saliencyMap The computed saliency map. \return true if the saliency map is computed, false otherwise

impl SaliencyTrait for Ptr<Saliency>

fn as_raw_mut_Saliency(&mut self) -> *mut c_void

fn compute_saliency( &mut self, image: &impl ToInputArray, saliency_map: &mut impl ToOutputArray ) -> Result<bool>

\brief Compute the saliency \param image The image. \param saliencyMap The computed saliency map. \return true if the saliency map is computed, false otherwise

impl SaliencyTrait for Ptr<StaticSaliency>

fn as_raw_mut_Saliency(&mut self) -> *mut c_void

fn compute_saliency( &mut self, image: &impl ToInputArray, saliency_map: &mut impl ToOutputArray ) -> Result<bool>

\brief Compute the saliency \param image The image. \param saliencyMap The computed saliency map. \return true if the saliency map is computed, false otherwise

impl SaliencyTrait for Ptr<StaticSaliencyFineGrained>

fn as_raw_mut_Saliency(&mut self) -> *mut c_void

fn compute_saliency( &mut self, image: &impl ToInputArray, saliency_map: &mut impl ToOutputArray ) -> Result<bool>

\brief Compute the saliency \param image The image. \param saliencyMap The computed saliency map. \return true if the saliency map is computed, false otherwise

impl SaliencyTrait for Ptr<StaticSaliencySpectralResidual>

fn as_raw_mut_Saliency(&mut self) -> *mut c_void

fn compute_saliency( &mut self, image: &impl ToInputArray, saliency_map: &mut impl ToOutputArray ) -> Result<bool>

\brief Compute the saliency \param image The image. \param saliencyMap The computed saliency map. \return true if the saliency map is computed, false otherwise

impl SaliencyTraitConst for Ptr<MotionSaliency>

fn as_raw_Saliency(&self) -> *const c_void

impl SaliencyTraitConst for Ptr<MotionSaliencyBinWangApr2014>

fn as_raw_Saliency(&self) -> *const c_void

impl SaliencyTraitConst for Ptr<Objectness>

fn as_raw_Saliency(&self) -> *const c_void

impl SaliencyTraitConst for Ptr<ObjectnessBING>

fn as_raw_Saliency(&self) -> *const c_void

impl SaliencyTraitConst for Ptr<Saliency>

fn as_raw_Saliency(&self) -> *const c_void

impl SaliencyTraitConst for Ptr<StaticSaliency>

fn as_raw_Saliency(&self) -> *const c_void

impl SaliencyTraitConst for Ptr<StaticSaliencyFineGrained>

fn as_raw_Saliency(&self) -> *const c_void

impl SaliencyTraitConst for Ptr<StaticSaliencySpectralResidual>

fn as_raw_Saliency(&self) -> *const c_void

impl SavedIndexParamsTrait for Ptr<SavedIndexParams>

fn as_raw_mut_SavedIndexParams(&mut self) -> *mut c_void

impl SavedIndexParamsTraitConst for Ptr<SavedIndexParams>

fn as_raw_SavedIndexParams(&self) -> *const c_void

impl ScaleLayerInt8Trait for Ptr<ScaleLayerInt8>

fn as_raw_mut_ScaleLayerInt8(&mut self) -> *mut c_void

fn set_output_sc(&mut self, val: f32)

fn set_output_zp(&mut self, val: i32)

impl ScaleLayerInt8TraitConst for Ptr<ScaleLayerInt8>

fn as_raw_ScaleLayerInt8(&self) -> *const c_void

fn output_sc(&self) -> f32

fn output_zp(&self) -> i32

impl ScaleLayerTrait for Ptr<ScaleLayer>

fn as_raw_mut_ScaleLayer(&mut self) -> *mut c_void

fn set_has_bias(&mut self, val: bool)

fn set_axis(&mut self, val: i32)

fn set_mode(&mut self, val: &str)

impl ScaleLayerTrait for Ptr<ScaleLayerInt8>

fn as_raw_mut_ScaleLayer(&mut self) -> *mut c_void

fn set_has_bias(&mut self, val: bool)

fn set_axis(&mut self, val: i32)

fn set_mode(&mut self, val: &str)

impl ScaleLayerTraitConst for Ptr<ScaleLayer>

fn as_raw_ScaleLayer(&self) -> *const c_void

fn has_bias(&self) -> bool

fn axis(&self) -> i32

fn mode(&self) -> String

impl ScaleLayerTraitConst for Ptr<ScaleLayerInt8>

fn as_raw_ScaleLayer(&self) -> *const c_void

fn has_bias(&self) -> bool

fn axis(&self) -> i32

fn mode(&self) -> String

impl ScanSegmentTrait for Ptr<ScanSegment>

fn as_raw_mut_ScanSegment(&mut self) -> *mut c_void

fn get_number_of_superpixels(&mut self) -> Result<i32>

Returns the actual superpixel segmentation from the last image processed using iterate.

fn iterate(&mut self, img: &impl ToInputArray) -> Result<()>

Calculates the superpixel segmentation on a given image with the initialized parameters in the ScanSegment object.

fn get_labels(&mut self, labels_out: &mut impl ToOutputArray) -> Result<()>

Returns the segmentation labeling of the image.

fn get_label_contour_mask( &mut self, image: &mut impl ToOutputArray, thick_line: bool ) -> Result<()>

Returns the mask of the superpixel segmentation stored in the ScanSegment object.

fn get_label_contour_mask_def( &mut self, image: &mut impl ToOutputArray ) -> Result<()>

Returns the mask of the superpixel segmentation stored in the ScanSegment object.

impl ScanSegmentTraitConst for Ptr<ScanSegment>

fn as_raw_ScanSegment(&self) -> *const c_void

impl ScatterLayerTrait for Ptr<ScatterLayer>

fn as_raw_mut_ScatterLayer(&mut self) -> *mut c_void

impl ScatterLayerTraitConst for Ptr<ScatterLayer>

fn as_raw_ScatterLayer(&self) -> *const c_void

impl ScatterNDLayerTrait for Ptr<ScatterNDLayer>

fn as_raw_mut_ScatterNDLayer(&mut self) -> *mut c_void

impl ScatterNDLayerTraitConst for Ptr<ScatterNDLayer>

fn as_raw_ScatterNDLayer(&self) -> *const c_void

impl SearchParamsTrait for Ptr<SearchParams>

fn as_raw_mut_SearchParams(&mut self) -> *mut c_void

impl SearchParamsTraitConst for Ptr<SearchParams>

fn as_raw_SearchParams(&self) -> *const c_void

impl SelectiveSearchSegmentationStrategyColorTrait for Ptr<SelectiveSearchSegmentationStrategyColor>

fn as_raw_mut_SelectiveSearchSegmentationStrategyColor(&mut self) -> *mut c_void

impl SelectiveSearchSegmentationStrategyColorTraitConst for Ptr<SelectiveSearchSegmentationStrategyColor>

fn as_raw_SelectiveSearchSegmentationStrategyColor(&self) -> *const c_void

impl SelectiveSearchSegmentationStrategyFillTrait for Ptr<SelectiveSearchSegmentationStrategyFill>

fn as_raw_mut_SelectiveSearchSegmentationStrategyFill(&mut self) -> *mut c_void

impl SelectiveSearchSegmentationStrategyFillTraitConst for Ptr<SelectiveSearchSegmentationStrategyFill>

fn as_raw_SelectiveSearchSegmentationStrategyFill(&self) -> *const c_void

impl SelectiveSearchSegmentationStrategyMultipleTrait for Ptr<SelectiveSearchSegmentationStrategyMultiple>

fn as_raw_mut_SelectiveSearchSegmentationStrategyMultiple( &mut self ) -> *mut c_void

fn add_strategy( &mut self, g: Ptr<SelectiveSearchSegmentationStrategy>, weight: f32 ) -> Result<()>

Add a new sub-strategy

fn clear_strategies(&mut self) -> Result<()>

Remove all sub-strategies

impl SelectiveSearchSegmentationStrategyMultipleTraitConst for Ptr<SelectiveSearchSegmentationStrategyMultiple>

fn as_raw_SelectiveSearchSegmentationStrategyMultiple(&self) -> *const c_void

impl SelectiveSearchSegmentationStrategySizeTrait for Ptr<SelectiveSearchSegmentationStrategySize>

fn as_raw_mut_SelectiveSearchSegmentationStrategySize(&mut self) -> *mut c_void

impl SelectiveSearchSegmentationStrategySizeTraitConst for Ptr<SelectiveSearchSegmentationStrategySize>

fn as_raw_SelectiveSearchSegmentationStrategySize(&self) -> *const c_void

impl SelectiveSearchSegmentationStrategyTextureTrait for Ptr<SelectiveSearchSegmentationStrategyTexture>

fn as_raw_mut_SelectiveSearchSegmentationStrategyTexture( &mut self ) -> *mut c_void

impl SelectiveSearchSegmentationStrategyTextureTraitConst for Ptr<SelectiveSearchSegmentationStrategyTexture>

fn as_raw_SelectiveSearchSegmentationStrategyTexture(&self) -> *const c_void

impl SelectiveSearchSegmentationStrategyTrait for Ptr<SelectiveSearchSegmentationStrategy>

fn as_raw_mut_SelectiveSearchSegmentationStrategy(&mut self) -> *mut c_void

fn set_image( &mut self, img: &impl ToInputArray, regions: &impl ToInputArray, sizes: &impl ToInputArray, image_id: i32 ) -> Result<()>

Set a initial image, with a segmentation.

fn set_image_def( &mut self, img: &impl ToInputArray, regions: &impl ToInputArray, sizes: &impl ToInputArray ) -> Result<()>

Set a initial image, with a segmentation.

fn get(&mut self, r1: i32, r2: i32) -> Result<f32>

Return the score between two regions (between 0 and 1)

fn merge(&mut self, r1: i32, r2: i32) -> Result<()>

Inform the strategy that two regions will be merged

impl SelectiveSearchSegmentationStrategyTrait for Ptr<SelectiveSearchSegmentationStrategyColor>

fn as_raw_mut_SelectiveSearchSegmentationStrategy(&mut self) -> *mut c_void

fn set_image( &mut self, img: &impl ToInputArray, regions: &impl ToInputArray, sizes: &impl ToInputArray, image_id: i32 ) -> Result<()>

Set a initial image, with a segmentation.

fn set_image_def( &mut self, img: &impl ToInputArray, regions: &impl ToInputArray, sizes: &impl ToInputArray ) -> Result<()>

Set a initial image, with a segmentation.

fn get(&mut self, r1: i32, r2: i32) -> Result<f32>

Return the score between two regions (between 0 and 1)

fn merge(&mut self, r1: i32, r2: i32) -> Result<()>

Inform the strategy that two regions will be merged

impl SelectiveSearchSegmentationStrategyTrait for Ptr<SelectiveSearchSegmentationStrategyFill>

fn as_raw_mut_SelectiveSearchSegmentationStrategy(&mut self) -> *mut c_void

fn set_image( &mut self, img: &impl ToInputArray, regions: &impl ToInputArray, sizes: &impl ToInputArray, image_id: i32 ) -> Result<()>

Set a initial image, with a segmentation.

fn set_image_def( &mut self, img: &impl ToInputArray, regions: &impl ToInputArray, sizes: &impl ToInputArray ) -> Result<()>

Set a initial image, with a segmentation.

fn get(&mut self, r1: i32, r2: i32) -> Result<f32>

Return the score between two regions (between 0 and 1)

fn merge(&mut self, r1: i32, r2: i32) -> Result<()>

Inform the strategy that two regions will be merged

impl SelectiveSearchSegmentationStrategyTrait for Ptr<SelectiveSearchSegmentationStrategyMultiple>

fn as_raw_mut_SelectiveSearchSegmentationStrategy(&mut self) -> *mut c_void

fn set_image( &mut self, img: &impl ToInputArray, regions: &impl ToInputArray, sizes: &impl ToInputArray, image_id: i32 ) -> Result<()>

Set a initial image, with a segmentation.

fn set_image_def( &mut self, img: &impl ToInputArray, regions: &impl ToInputArray, sizes: &impl ToInputArray ) -> Result<()>

Set a initial image, with a segmentation.

fn get(&mut self, r1: i32, r2: i32) -> Result<f32>

Return the score between two regions (between 0 and 1)

fn merge(&mut self, r1: i32, r2: i32) -> Result<()>

Inform the strategy that two regions will be merged

impl SelectiveSearchSegmentationStrategyTrait for Ptr<SelectiveSearchSegmentationStrategySize>

fn as_raw_mut_SelectiveSearchSegmentationStrategy(&mut self) -> *mut c_void

fn set_image( &mut self, img: &impl ToInputArray, regions: &impl ToInputArray, sizes: &impl ToInputArray, image_id: i32 ) -> Result<()>

Set a initial image, with a segmentation.

fn set_image_def( &mut self, img: &impl ToInputArray, regions: &impl ToInputArray, sizes: &impl ToInputArray ) -> Result<()>

Set a initial image, with a segmentation.

fn get(&mut self, r1: i32, r2: i32) -> Result<f32>

Return the score between two regions (between 0 and 1)

fn merge(&mut self, r1: i32, r2: i32) -> Result<()>

Inform the strategy that two regions will be merged

impl SelectiveSearchSegmentationStrategyTrait for Ptr<SelectiveSearchSegmentationStrategyTexture>

fn as_raw_mut_SelectiveSearchSegmentationStrategy(&mut self) -> *mut c_void

fn set_image( &mut self, img: &impl ToInputArray, regions: &impl ToInputArray, sizes: &impl ToInputArray, image_id: i32 ) -> Result<()>

Set a initial image, with a segmentation.

fn set_image_def( &mut self, img: &impl ToInputArray, regions: &impl ToInputArray, sizes: &impl ToInputArray ) -> Result<()>

Set a initial image, with a segmentation.

fn get(&mut self, r1: i32, r2: i32) -> Result<f32>

Return the score between two regions (between 0 and 1)

fn merge(&mut self, r1: i32, r2: i32) -> Result<()>

Inform the strategy that two regions will be merged

impl SelectiveSearchSegmentationStrategyTraitConst for Ptr<SelectiveSearchSegmentationStrategy>

fn as_raw_SelectiveSearchSegmentationStrategy(&self) -> *const c_void

impl SelectiveSearchSegmentationStrategyTraitConst for Ptr<SelectiveSearchSegmentationStrategyColor>

fn as_raw_SelectiveSearchSegmentationStrategy(&self) -> *const c_void

impl SelectiveSearchSegmentationStrategyTraitConst for Ptr<SelectiveSearchSegmentationStrategyFill>

fn as_raw_SelectiveSearchSegmentationStrategy(&self) -> *const c_void

impl SelectiveSearchSegmentationStrategyTraitConst for Ptr<SelectiveSearchSegmentationStrategyMultiple>

fn as_raw_SelectiveSearchSegmentationStrategy(&self) -> *const c_void

impl SelectiveSearchSegmentationStrategyTraitConst for Ptr<SelectiveSearchSegmentationStrategySize>

fn as_raw_SelectiveSearchSegmentationStrategy(&self) -> *const c_void

impl SelectiveSearchSegmentationStrategyTraitConst for Ptr<SelectiveSearchSegmentationStrategyTexture>

fn as_raw_SelectiveSearchSegmentationStrategy(&self) -> *const c_void

impl SelectiveSearchSegmentationTrait for Ptr<SelectiveSearchSegmentation>

fn as_raw_mut_SelectiveSearchSegmentation(&mut self) -> *mut c_void

fn set_base_image(&mut self, img: &impl ToInputArray) -> Result<()>

Set a image used by switch* functions to initialize the class

fn switch_to_single_strategy(&mut self, k: i32, sigma: f32) -> Result<()>

Initialize the class with the ‘Single stragegy’ parameters describled in uijlings2013selective.

fn switch_to_single_strategy_def(&mut self) -> Result<()>

Initialize the class with the ‘Single stragegy’ parameters describled in uijlings2013selective.

fn switch_to_selective_search_fast( &mut self, base_k: i32, inc_k: i32, sigma: f32 ) -> Result<()>

Initialize the class with the ‘Selective search fast’ parameters describled in uijlings2013selective.

fn switch_to_selective_search_fast_def(&mut self) -> Result<()>

Initialize the class with the ‘Selective search fast’ parameters describled in uijlings2013selective.

fn switch_to_selective_search_quality( &mut self, base_k: i32, inc_k: i32, sigma: f32 ) -> Result<()>

Initialize the class with the ‘Selective search fast’ parameters describled in uijlings2013selective.

fn switch_to_selective_search_quality_def(&mut self) -> Result<()>

Initialize the class with the ‘Selective search fast’ parameters describled in uijlings2013selective.

fn add_image(&mut self, img: &impl ToInputArray) -> Result<()>

Add a new image in the list of images to process.

fn clear_images(&mut self) -> Result<()>

Clear the list of images to process

fn add_graph_segmentation(&mut self, g: Ptr<GraphSegmentation>) -> Result<()>

Add a new graph segmentation in the list of graph segementations to process.

fn clear_graph_segmentations(&mut self) -> Result<()>

Clear the list of graph segmentations to process;

fn add_strategy( &mut self, s: Ptr<SelectiveSearchSegmentationStrategy> ) -> Result<()>

Add a new strategy in the list of strategy to process.

fn clear_strategies(&mut self) -> Result<()>

Clear the list of strategy to process;

fn process(&mut self, rects: &mut Vector<Rect>) -> Result<()>

Based on all images, graph segmentations and stragies, computes all possible rects and return them

impl SelectiveSearchSegmentationTraitConst for Ptr<SelectiveSearchSegmentation>

fn as_raw_SelectiveSearchSegmentation(&self) -> *const c_void

impl SeluLayerTrait for Ptr<SeluLayer>

fn as_raw_mut_SeluLayer(&mut self) -> *mut c_void

fn set_alpha(&mut self, val: f32)

fn set_gamma(&mut self, val: f32)

impl SeluLayerTraitConst for Ptr<SeluLayer>

fn as_raw_SeluLayer(&self) -> *const c_void

fn alpha(&self) -> f32

fn gamma(&self) -> f32

impl ShapeContextDistanceExtractorTrait for Ptr<ShapeContextDistanceExtractor>

fn as_raw_mut_ShapeContextDistanceExtractor(&mut self) -> *mut c_void

fn set_angular_bins(&mut self, n_angular_bins: i32) -> Result<()>

Establish the number of angular bins for the Shape Context Descriptor used in the shape matching pipeline.

fn set_radial_bins(&mut self, n_radial_bins: i32) -> Result<()>

Establish the number of radial bins for the Shape Context Descriptor used in the shape matching pipeline.

fn set_inner_radius(&mut self, inner_radius: f32) -> Result<()>

Set the inner radius of the shape context descriptor.

fn set_outer_radius(&mut self, outer_radius: f32) -> Result<()>

Set the outer radius of the shape context descriptor.

fn set_rotation_invariant(&mut self, rotation_invariant: bool) -> Result<()>

fn set_shape_context_weight(&mut self, shape_context_weight: f32) -> Result<()>

Set the weight of the shape context distance in the final value of the shape distance. The shape context distance between two shapes is defined as the symmetric sum of shape context matching costs over best matching points. The final value of the shape distance is a user-defined linear combination of the shape context distance, an image appearance distance, and a bending energy.

fn set_image_appearance_weight( &mut self, image_appearance_weight: f32 ) -> Result<()>

Set the weight of the Image Appearance cost in the final value of the shape distance. The image appearance cost is defined as the sum of squared brightness differences in Gaussian windows around corresponding image points. The final value of the shape distance is a user-defined linear combination of the shape context distance, an image appearance distance, and a bending energy. If this value is set to a number different from 0, is mandatory to set the images that correspond to each shape.

fn set_bending_energy_weight( &mut self, bending_energy_weight: f32 ) -> Result<()>

Set the weight of the Bending Energy in the final value of the shape distance. The bending energy definition depends on what transformation is being used to align the shapes. The final value of the shape distance is a user-defined linear combination of the shape context distance, an image appearance distance, and a bending energy.

fn set_images( &mut self, image1: &impl ToInputArray, image2: &impl ToInputArray ) -> Result<()>

Set the images that correspond to each shape. This images are used in the calculation of the Image Appearance cost.

fn set_iterations(&mut self, iterations: i32) -> Result<()>

fn set_cost_extractor( &mut self, comparer: Ptr<HistogramCostExtractor> ) -> Result<()>

Set the algorithm used for building the shape context descriptor cost matrix.

fn set_std_dev(&mut self, sigma: f32) -> Result<()>

Set the value of the standard deviation for the Gaussian window for the image appearance cost.

fn set_transform_algorithm( &mut self, transformer: Ptr<ShapeTransformer> ) -> Result<()>

Set the algorithm used for aligning the shapes.

impl ShapeContextDistanceExtractorTraitConst for Ptr<ShapeContextDistanceExtractor>

fn as_raw_ShapeContextDistanceExtractor(&self) -> *const c_void

fn get_angular_bins(&self) -> Result<i32>

fn get_radial_bins(&self) -> Result<i32>

fn get_inner_radius(&self) -> Result<f32>

fn get_outer_radius(&self) -> Result<f32>

fn get_rotation_invariant(&self) -> Result<bool>

fn get_shape_context_weight(&self) -> Result<f32>

fn get_image_appearance_weight(&self) -> Result<f32>

fn get_bending_energy_weight(&self) -> Result<f32>

fn get_images( &self, image1: &mut impl ToOutputArray, image2: &mut impl ToOutputArray ) -> Result<()>

fn get_iterations(&self) -> Result<i32>

fn get_cost_extractor(&self) -> Result<Ptr<HistogramCostExtractor>>

fn get_std_dev(&self) -> Result<f32>

fn get_transform_algorithm(&self) -> Result<Ptr<ShapeTransformer>>

impl ShapeDistanceExtractorTrait for Ptr<HausdorffDistanceExtractor>

fn as_raw_mut_ShapeDistanceExtractor(&mut self) -> *mut c_void

fn compute_distance( &mut self, contour1: &impl ToInputArray, contour2: &impl ToInputArray ) -> Result<f32>

Compute the shape distance between two shapes defined by its contours.

impl ShapeDistanceExtractorTrait for Ptr<ShapeContextDistanceExtractor>

fn as_raw_mut_ShapeDistanceExtractor(&mut self) -> *mut c_void

fn compute_distance( &mut self, contour1: &impl ToInputArray, contour2: &impl ToInputArray ) -> Result<f32>

Compute the shape distance between two shapes defined by its contours.

impl ShapeDistanceExtractorTrait for Ptr<ShapeDistanceExtractor>

fn as_raw_mut_ShapeDistanceExtractor(&mut self) -> *mut c_void

fn compute_distance( &mut self, contour1: &impl ToInputArray, contour2: &impl ToInputArray ) -> Result<f32>

Compute the shape distance between two shapes defined by its contours.

impl ShapeDistanceExtractorTraitConst for Ptr<HausdorffDistanceExtractor>

fn as_raw_ShapeDistanceExtractor(&self) -> *const c_void

impl ShapeDistanceExtractorTraitConst for Ptr<ShapeContextDistanceExtractor>

fn as_raw_ShapeDistanceExtractor(&self) -> *const c_void

impl ShapeDistanceExtractorTraitConst for Ptr<ShapeDistanceExtractor>

fn as_raw_ShapeDistanceExtractor(&self) -> *const c_void

impl ShapeTransformerTrait for Ptr<AffineTransformer>

fn as_raw_mut_ShapeTransformer(&mut self) -> *mut c_void

fn estimate_transformation( &mut self, transforming_shape: &impl ToInputArray, target_shape: &impl ToInputArray, matches: &mut Vector<DMatch> ) -> Result<()>

Estimate the transformation parameters of the current transformer algorithm, based on point matches.

fn apply_transformation( &mut self, input: &impl ToInputArray, output: &mut impl ToOutputArray ) -> Result<f32>

Apply a transformation, given a pre-estimated transformation parameters.

fn apply_transformation_def(&mut self, input: &impl ToInputArray) -> Result<f32>

Apply a transformation, given a pre-estimated transformation parameters.

impl ShapeTransformerTrait for Ptr<ShapeTransformer>

fn as_raw_mut_ShapeTransformer(&mut self) -> *mut c_void

fn estimate_transformation( &mut self, transforming_shape: &impl ToInputArray, target_shape: &impl ToInputArray, matches: &mut Vector<DMatch> ) -> Result<()>

Estimate the transformation parameters of the current transformer algorithm, based on point matches.

fn apply_transformation( &mut self, input: &impl ToInputArray, output: &mut impl ToOutputArray ) -> Result<f32>

Apply a transformation, given a pre-estimated transformation parameters.

fn apply_transformation_def(&mut self, input: &impl ToInputArray) -> Result<f32>

Apply a transformation, given a pre-estimated transformation parameters.

impl ShapeTransformerTrait for Ptr<ThinPlateSplineShapeTransformer>

fn as_raw_mut_ShapeTransformer(&mut self) -> *mut c_void

fn estimate_transformation( &mut self, transforming_shape: &impl ToInputArray, target_shape: &impl ToInputArray, matches: &mut Vector<DMatch> ) -> Result<()>

Estimate the transformation parameters of the current transformer algorithm, based on point matches.

fn apply_transformation( &mut self, input: &impl ToInputArray, output: &mut impl ToOutputArray ) -> Result<f32>

Apply a transformation, given a pre-estimated transformation parameters.

fn apply_transformation_def(&mut self, input: &impl ToInputArray) -> Result<f32>

Apply a transformation, given a pre-estimated transformation parameters.

impl ShapeTransformerTraitConst for Ptr<AffineTransformer>

fn as_raw_ShapeTransformer(&self) -> *const c_void

fn warp_image( &self, transforming_image: &impl ToInputArray, output: &mut impl ToOutputArray, flags: i32, border_mode: i32, border_value: Scalar ) -> Result<()>

Apply a transformation, given a pre-estimated transformation parameters, to an Image.

fn warp_image_def( &self, transforming_image: &impl ToInputArray, output: &mut impl ToOutputArray ) -> Result<()>

Apply a transformation, given a pre-estimated transformation parameters, to an Image.

impl ShapeTransformerTraitConst for Ptr<ShapeTransformer>

fn as_raw_ShapeTransformer(&self) -> *const c_void

fn warp_image( &self, transforming_image: &impl ToInputArray, output: &mut impl ToOutputArray, flags: i32, border_mode: i32, border_value: Scalar ) -> Result<()>

Apply a transformation, given a pre-estimated transformation parameters, to an Image.

fn warp_image_def( &self, transforming_image: &impl ToInputArray, output: &mut impl ToOutputArray ) -> Result<()>

Apply a transformation, given a pre-estimated transformation parameters, to an Image.

impl ShapeTransformerTraitConst for Ptr<ThinPlateSplineShapeTransformer>

fn as_raw_ShapeTransformer(&self) -> *const c_void

fn warp_image( &self, transforming_image: &impl ToInputArray, output: &mut impl ToOutputArray, flags: i32, border_mode: i32, border_value: Scalar ) -> Result<()>

Apply a transformation, given a pre-estimated transformation parameters, to an Image.

fn warp_image_def( &self, transforming_image: &impl ToInputArray, output: &mut impl ToOutputArray ) -> Result<()>

Apply a transformation, given a pre-estimated transformation parameters, to an Image.

impl ShiftLayerInt8Trait for Ptr<ShiftLayerInt8>

fn as_raw_mut_ShiftLayerInt8(&mut self) -> *mut c_void

impl ShiftLayerInt8TraitConst for Ptr<ShiftLayerInt8>

fn as_raw_ShiftLayerInt8(&self) -> *const c_void

impl ShiftLayerTrait for Ptr<ShiftLayer>

fn as_raw_mut_ShiftLayer(&mut self) -> *mut c_void

impl ShiftLayerTraitConst for Ptr<ShiftLayer>

fn as_raw_ShiftLayer(&self) -> *const c_void

impl ShrinkLayerTrait for Ptr<ShrinkLayer>

fn as_raw_mut_ShrinkLayer(&mut self) -> *mut c_void

fn set_bias(&mut self, val: f32)

fn set_lambd(&mut self, val: f32)

impl ShrinkLayerTraitConst for Ptr<ShrinkLayer>

fn as_raw_ShrinkLayer(&self) -> *const c_void

fn bias(&self) -> f32

fn lambd(&self) -> f32

impl ShuffleChannelLayerTrait for Ptr<ShuffleChannelLayer>

fn as_raw_mut_ShuffleChannelLayer(&mut self) -> *mut c_void

fn set_group(&mut self, val: i32)

impl ShuffleChannelLayerTraitConst for Ptr<ShuffleChannelLayer>

fn as_raw_ShuffleChannelLayer(&self) -> *const c_void

fn group(&self) -> i32

impl SigmoidLayerTrait for Ptr<SigmoidLayer>

fn as_raw_mut_SigmoidLayer(&mut self) -> *mut c_void

impl SigmoidLayerTraitConst for Ptr<SigmoidLayer>

fn as_raw_SigmoidLayer(&self) -> *const c_void

impl SignLayerTrait for Ptr<SignLayer>

fn as_raw_mut_SignLayer(&mut self) -> *mut c_void

impl SignLayerTraitConst for Ptr<SignLayer>

fn as_raw_SignLayer(&self) -> *const c_void

impl SimpleBlobDetectorTrait for Ptr<SimpleBlobDetector>

fn as_raw_mut_SimpleBlobDetector(&mut self) -> *mut c_void

fn set_params(&mut self, params: SimpleBlobDetector_Params) -> Result<()>

impl SimpleBlobDetectorTraitConst for Ptr<SimpleBlobDetector>

fn as_raw_SimpleBlobDetector(&self) -> *const c_void

fn get_params(&self) -> Result<SimpleBlobDetector_Params>

fn get_default_name(&self) -> Result<String>

fn get_blob_contours(&self) -> Result<Vector<Vector<Point>>>

impl SimpleWBTrait for Ptr<SimpleWB>

fn as_raw_mut_SimpleWB(&mut self) -> *mut c_void

fn set_input_min(&mut self, val: f32) -> Result<()>

Input image range minimum value

fn set_input_max(&mut self, val: f32) -> Result<()>

Input image range maximum value

fn set_output_min(&mut self, val: f32) -> Result<()>

Output image range minimum value

fn set_output_max(&mut self, val: f32) -> Result<()>

Output image range maximum value

fn set_p(&mut self, val: f32) -> Result<()>

Percent of top/bottom values to ignore

impl SimpleWBTraitConst for Ptr<SimpleWB>

fn as_raw_SimpleWB(&self) -> *const c_void

fn get_input_min(&self) -> Result<f32>

Input image range minimum value

fn get_input_max(&self) -> Result<f32>

Input image range maximum value

fn get_output_min(&self) -> Result<f32>

Output image range minimum value

fn get_output_max(&self) -> Result<f32>

Output image range maximum value

fn get_p(&self) -> Result<f32>

Percent of top/bottom values to ignore

impl SinLayerTrait for Ptr<SinLayer>

fn as_raw_mut_SinLayer(&mut self) -> *mut c_void

impl SinLayerTraitConst for Ptr<SinLayer>

fn as_raw_SinLayer(&self) -> *const c_void

impl SinhLayerTrait for Ptr<SinhLayer>

fn as_raw_mut_SinhLayer(&mut self) -> *mut c_void

impl SinhLayerTraitConst for Ptr<SinhLayer>

fn as_raw_SinhLayer(&self) -> *const c_void

impl SinusoidalPatternTrait for Ptr<SinusoidalPattern>

fn as_raw_mut_SinusoidalPattern(&mut self) -> *mut c_void

fn compute_phase_map( &mut self, pattern_images: &impl ToInputArray, wrapped_phase_map: &mut impl ToOutputArray, shadow_mask: &mut impl ToOutputArray, fundamental: &impl ToInputArray ) -> Result<()>

Compute a wrapped phase map from sinusoidal patterns.

fn compute_phase_map_def( &mut self, pattern_images: &impl ToInputArray, wrapped_phase_map: &mut impl ToOutputArray ) -> Result<()>

Compute a wrapped phase map from sinusoidal patterns.

fn unwrap_phase_map( &mut self, wrapped_phase_map: &impl ToInputArray, unwrapped_phase_map: &mut impl ToOutputArray, cam_size: Size, shadow_mask: &impl ToInputArray ) -> Result<()>

Unwrap the wrapped phase map to remove phase ambiguities.

fn unwrap_phase_map_def( &mut self, wrapped_phase_map: &impl ToInputArray, unwrapped_phase_map: &mut impl ToOutputArray, cam_size: Size ) -> Result<()>

Unwrap the wrapped phase map to remove phase ambiguities.

fn find_pro_cam_matches( &mut self, proj_unwrapped_phase_map: &impl ToInputArray, cam_unwrapped_phase_map: &impl ToInputArray, matches: &mut impl ToOutputArray ) -> Result<()>

Find correspondences between the two devices thanks to unwrapped phase maps.

fn compute_data_modulation_term( &mut self, pattern_images: &impl ToInputArray, data_modulation_term: &mut impl ToOutputArray, shadow_mask: &impl ToInputArray ) -> Result<()>

compute the data modulation term.

impl SinusoidalPatternTraitConst for Ptr<SinusoidalPattern>

fn as_raw_SinusoidalPattern(&self) -> *const c_void

impl SinusoidalPattern_ParamsTrait for Ptr<SinusoidalPattern_Params>

fn as_raw_mut_SinusoidalPattern_Params(&mut self) -> *mut c_void

fn set_width(&mut self, val: i32)

fn set_height(&mut self, val: i32)

fn set_nbr_of_periods(&mut self, val: i32)

fn set_shift_value(&mut self, val: f32)

fn set_method_id(&mut self, val: i32)

fn set_nbr_of_pixels_between_markers(&mut self, val: i32)

fn set_horizontal(&mut self, val: bool)

fn set_set_markers(&mut self, val: bool)

fn set_markers_location(&mut self, val: Vector<Point2f>)

impl SinusoidalPattern_ParamsTraitConst for Ptr<SinusoidalPattern_Params>

fn as_raw_SinusoidalPattern_Params(&self) -> *const c_void

fn width(&self) -> i32

fn height(&self) -> i32

fn nbr_of_periods(&self) -> i32

fn shift_value(&self) -> f32

fn method_id(&self) -> i32

fn nbr_of_pixels_between_markers(&self) -> i32

fn horizontal(&self) -> bool

fn set_markers(&self) -> bool

fn markers_location(&self) -> Vector<Point2f>

impl SliceLayerTrait for Ptr<SliceLayer>

fn as_raw_mut_SliceLayer(&mut self) -> *mut c_void

fn set_slice_ranges(&mut self, val: Vector<Vector<Range>>)

Vector of slice ranges.

fn set_slice_steps(&mut self, val: Vector<Vector<i32>>)

fn set_axis(&mut self, val: i32)

fn set_num_split(&mut self, val: i32)

impl SliceLayerTraitConst for Ptr<SliceLayer>

fn as_raw_SliceLayer(&self) -> *const c_void

fn slice_ranges(&self) -> Vector<Vector<Range>>

Vector of slice ranges.

fn slice_steps(&self) -> Vector<Vector<i32>>

fn axis(&self) -> i32

fn num_split(&self) -> i32

impl SoftmaxLayerInt8Trait for Ptr<SoftmaxLayerInt8>

fn as_raw_mut_SoftmaxLayerInt8(&mut self) -> *mut c_void

fn set_output_sc(&mut self, val: f32)

fn set_output_zp(&mut self, val: i32)

impl SoftmaxLayerInt8TraitConst for Ptr<SoftmaxLayerInt8>

fn as_raw_SoftmaxLayerInt8(&self) -> *const c_void

fn output_sc(&self) -> f32

fn output_zp(&self) -> i32

impl SoftmaxLayerTrait for Ptr<SoftmaxLayer>

fn as_raw_mut_SoftmaxLayer(&mut self) -> *mut c_void

fn set_log_soft_max(&mut self, val: bool)

impl SoftmaxLayerTrait for Ptr<SoftmaxLayerInt8>

fn as_raw_mut_SoftmaxLayer(&mut self) -> *mut c_void

fn set_log_soft_max(&mut self, val: bool)

impl SoftmaxLayerTraitConst for Ptr<SoftmaxLayer>

fn as_raw_SoftmaxLayer(&self) -> *const c_void

fn log_soft_max(&self) -> bool

impl SoftmaxLayerTraitConst for Ptr<SoftmaxLayerInt8>

fn as_raw_SoftmaxLayer(&self) -> *const c_void

fn log_soft_max(&self) -> bool

impl SoftplusLayerTrait for Ptr<SoftplusLayer>

fn as_raw_mut_SoftplusLayer(&mut self) -> *mut c_void

impl SoftplusLayerTraitConst for Ptr<SoftplusLayer>

fn as_raw_SoftplusLayer(&self) -> *const c_void

impl SoftsignLayerTrait for Ptr<SoftsignLayer>

fn as_raw_mut_SoftsignLayer(&mut self) -> *mut c_void

impl SoftsignLayerTraitConst for Ptr<SoftsignLayer>

fn as_raw_SoftsignLayer(&self) -> *const c_void

impl SparseMatchInterpolatorTrait for Ptr<EdgeAwareInterpolator>

fn as_raw_mut_SparseMatchInterpolator(&mut self) -> *mut c_void

fn interpolate( &mut self, from_image: &impl ToInputArray, from_points: &impl ToInputArray, to_image: &impl ToInputArray, to_points: &impl ToInputArray, dense_flow: &mut impl ToOutputArray ) -> Result<()>

Interpolate input sparse matches.

impl SparseMatchInterpolatorTrait for Ptr<RICInterpolator>

fn as_raw_mut_SparseMatchInterpolator(&mut self) -> *mut c_void

fn interpolate( &mut self, from_image: &impl ToInputArray, from_points: &impl ToInputArray, to_image: &impl ToInputArray, to_points: &impl ToInputArray, dense_flow: &mut impl ToOutputArray ) -> Result<()>

Interpolate input sparse matches.

impl SparseMatchInterpolatorTrait for Ptr<SparseMatchInterpolator>

fn as_raw_mut_SparseMatchInterpolator(&mut self) -> *mut c_void

fn interpolate( &mut self, from_image: &impl ToInputArray, from_points: &impl ToInputArray, to_image: &impl ToInputArray, to_points: &impl ToInputArray, dense_flow: &mut impl ToOutputArray ) -> Result<()>

Interpolate input sparse matches.

impl SparseMatchInterpolatorTraitConst for Ptr<EdgeAwareInterpolator>

fn as_raw_SparseMatchInterpolator(&self) -> *const c_void

impl SparseMatchInterpolatorTraitConst for Ptr<RICInterpolator>

fn as_raw_SparseMatchInterpolator(&self) -> *const c_void

impl SparseMatchInterpolatorTraitConst for Ptr<SparseMatchInterpolator>

fn as_raw_SparseMatchInterpolator(&self) -> *const c_void

impl SparseOpticalFlowTrait for Ptr<SparseOpticalFlow>

fn as_raw_mut_SparseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, prev_img: &impl ToInputArray, next_img: &impl ToInputArray, prev_pts: &impl ToInputArray, next_pts: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray, err: &mut impl ToOutputArray ) -> Result<()>

Calculates a sparse optical flow.

fn calc_def( &mut self, prev_img: &impl ToInputArray, next_img: &impl ToInputArray, prev_pts: &impl ToInputArray, next_pts: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray ) -> Result<()>

Calculates a sparse optical flow.

impl SparseOpticalFlowTrait for Ptr<SparsePyrLKOpticalFlow>

fn as_raw_mut_SparseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, prev_img: &impl ToInputArray, next_img: &impl ToInputArray, prev_pts: &impl ToInputArray, next_pts: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray, err: &mut impl ToOutputArray ) -> Result<()>

Calculates a sparse optical flow.

fn calc_def( &mut self, prev_img: &impl ToInputArray, next_img: &impl ToInputArray, prev_pts: &impl ToInputArray, next_pts: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray ) -> Result<()>

Calculates a sparse optical flow.

impl SparseOpticalFlowTrait for Ptr<SparseRLOFOpticalFlow>

fn as_raw_mut_SparseOpticalFlow(&mut self) -> *mut c_void

fn calc( &mut self, prev_img: &impl ToInputArray, next_img: &impl ToInputArray, prev_pts: &impl ToInputArray, next_pts: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray, err: &mut impl ToOutputArray ) -> Result<()>

Calculates a sparse optical flow.

fn calc_def( &mut self, prev_img: &impl ToInputArray, next_img: &impl ToInputArray, prev_pts: &impl ToInputArray, next_pts: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray ) -> Result<()>

Calculates a sparse optical flow.

impl SparseOpticalFlowTraitConst for Ptr<SparseOpticalFlow>

fn as_raw_SparseOpticalFlow(&self) -> *const c_void

impl SparseOpticalFlowTraitConst for Ptr<SparsePyrLKOpticalFlow>

fn as_raw_SparseOpticalFlow(&self) -> *const c_void

impl SparseOpticalFlowTraitConst for Ptr<SparseRLOFOpticalFlow>

fn as_raw_SparseOpticalFlow(&self) -> *const c_void

impl SparsePyrLKOpticalFlowTrait for Ptr<SparsePyrLKOpticalFlow>

fn as_raw_mut_SparsePyrLKOpticalFlow(&mut self) -> *mut c_void

fn set_win_size(&mut self, win_size: Size) -> Result<()>

fn set_max_level(&mut self, max_level: i32) -> Result<()>

fn set_term_criteria(&mut self, crit: &mut TermCriteria) -> Result<()>

fn set_flags(&mut self, flags: i32) -> Result<()>

fn set_min_eig_threshold(&mut self, min_eig_threshold: f64) -> Result<()>

impl SparsePyrLKOpticalFlowTraitConst for Ptr<SparsePyrLKOpticalFlow>

fn as_raw_SparsePyrLKOpticalFlow(&self) -> *const c_void

fn get_win_size(&self) -> Result<Size>

fn get_max_level(&self) -> Result<i32>

fn get_term_criteria(&self) -> Result<TermCriteria>

fn get_flags(&self) -> Result<i32>

fn get_min_eig_threshold(&self) -> Result<f64>

impl SparsePyrLkOptFlowEstimatorGpuTrait for Ptr<SparsePyrLkOptFlowEstimatorGpu>

fn as_raw_mut_SparsePyrLkOptFlowEstimatorGpu(&mut self) -> *mut c_void

fn run( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, points0: &impl ToInputArray, points1: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray, errors: &mut impl ToOutputArray ) -> Result<()>

fn run_1( &mut self, frame0: &impl GpuMatTraitConst, frame1: &impl GpuMatTraitConst, points0: &impl GpuMatTraitConst, points1: &mut impl GpuMatTrait, status: &mut impl GpuMatTrait, errors: &mut impl GpuMatTrait ) -> Result<()>

fn run_2( &mut self, frame0: &impl GpuMatTraitConst, frame1: &impl GpuMatTraitConst, points0: &impl GpuMatTraitConst, points1: &mut impl GpuMatTrait, status: &mut impl GpuMatTrait ) -> Result<()>

impl SparsePyrLkOptFlowEstimatorGpuTraitConst for Ptr<SparsePyrLkOptFlowEstimatorGpu>

fn as_raw_SparsePyrLkOptFlowEstimatorGpu(&self) -> *const c_void

impl SparsePyrLkOptFlowEstimatorTrait for Ptr<SparsePyrLkOptFlowEstimator>

fn as_raw_mut_SparsePyrLkOptFlowEstimator(&mut self) -> *mut c_void

fn run( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, points0: &impl ToInputArray, points1: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray, errors: &mut impl ToOutputArray ) -> Result<()>

impl SparsePyrLkOptFlowEstimatorTraitConst for Ptr<SparsePyrLkOptFlowEstimator>

fn as_raw_SparsePyrLkOptFlowEstimator(&self) -> *const c_void

impl SparseRLOFOpticalFlowTrait for Ptr<SparseRLOFOpticalFlow>

fn as_raw_mut_SparseRLOFOpticalFlow(&mut self) -> *mut c_void

fn set_rlof_optical_flow_parameter( &mut self, val: Ptr<RLOFOpticalFlowParameter> ) -> Result<()>

@copydoc DenseRLOFOpticalFlow::setRLOFOpticalFlowParameter

fn set_forward_backward(&mut self, val: f32) -> Result<()>

Threshold for the forward backward confidence check For each feature point a motion vector inline formula is computed. * If the forward backward error block formula * is larger than threshold given by this function then the status will not be used by the following * vector field interpolation. inline formula denotes the backward flow. Note, the forward backward test * will only be applied if the threshold > 0. This may results into a doubled runtime for the motion estimation. * see also: setForwardBackward

impl SparseRLOFOpticalFlowTraitConst for Ptr<SparseRLOFOpticalFlow>

fn as_raw_SparseRLOFOpticalFlow(&self) -> *const c_void

fn get_rlof_optical_flow_parameter( &self ) -> Result<Ptr<RLOFOpticalFlowParameter>>

@copydoc DenseRLOFOpticalFlow::setRLOFOpticalFlowParameter

fn get_forward_backward(&self) -> Result<f32>

Threshold for the forward backward confidence check For each feature point a motion vector inline formula is computed. * If the forward backward error block formula * is larger than threshold given by this function then the status will not be used by the following * vector field interpolation. inline formula denotes the backward flow. Note, the forward backward test * will only be applied if the threshold > 0. This may results into a doubled runtime for the motion estimation. * setForwardBackward

impl SphericalWarperGpuTrait for Ptr<SphericalWarperGpu>

fn as_raw_mut_SphericalWarperGpu(&mut self) -> *mut c_void

impl SphericalWarperGpuTraitConst for Ptr<SphericalWarperGpu>

fn as_raw_SphericalWarperGpu(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl SphericalWarperTrait for Ptr<SphericalWarper>

fn as_raw_mut_SphericalWarper(&mut self) -> *mut c_void

impl SphericalWarperTraitConst for Ptr<SphericalWarper>

fn as_raw_SphericalWarper(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl SplitLayerTrait for Ptr<SplitLayer>

fn as_raw_mut_SplitLayer(&mut self) -> *mut c_void

fn set_outputs_count(&mut self, val: i32)

Number of copies that will be produced (is ignored when negative).

impl SplitLayerTraitConst for Ptr<SplitLayer>

fn as_raw_SplitLayer(&self) -> *const c_void

fn outputs_count(&self) -> i32

Number of copies that will be produced (is ignored when negative).

impl SqrtLayerTrait for Ptr<SqrtLayer>

fn as_raw_mut_SqrtLayer(&mut self) -> *mut c_void

impl SqrtLayerTraitConst for Ptr<SqrtLayer>

fn as_raw_SqrtLayer(&self) -> *const c_void

impl StabilizerBaseTrait for Ptr<OnePassStabilizer>

fn as_raw_mut_StabilizerBase(&mut self) -> *mut c_void

fn set_log(&mut self, ilog: Ptr<ILog>) -> Result<()>

fn set_radius(&mut self, val: i32) -> Result<()>

fn set_frame_source(&mut self, val: Ptr<IFrameSource>) -> Result<()>

fn set_mask_source(&mut self, val: &Ptr<IFrameSource>) -> Result<()>

fn set_motion_estimator( &mut self, val: Ptr<ImageMotionEstimatorBase> ) -> Result<()>

fn set_deblurer(&mut self, val: Ptr<DeblurerBase>) -> Result<()>

fn set_trim_ratio(&mut self, val: f32) -> Result<()>

fn set_correction_for_inclusion(&mut self, val: bool) -> Result<()>

fn set_border_mode(&mut self, val: i32) -> Result<()>

fn set_inpainter(&mut self, val: Ptr<InpainterBase>) -> Result<()>

impl StabilizerBaseTrait for Ptr<StabilizerBase>

fn as_raw_mut_StabilizerBase(&mut self) -> *mut c_void

fn set_log(&mut self, ilog: Ptr<ILog>) -> Result<()>

fn set_radius(&mut self, val: i32) -> Result<()>

fn set_frame_source(&mut self, val: Ptr<IFrameSource>) -> Result<()>

fn set_mask_source(&mut self, val: &Ptr<IFrameSource>) -> Result<()>

fn set_motion_estimator( &mut self, val: Ptr<ImageMotionEstimatorBase> ) -> Result<()>

fn set_deblurer(&mut self, val: Ptr<DeblurerBase>) -> Result<()>

fn set_trim_ratio(&mut self, val: f32) -> Result<()>

fn set_correction_for_inclusion(&mut self, val: bool) -> Result<()>

fn set_border_mode(&mut self, val: i32) -> Result<()>

fn set_inpainter(&mut self, val: Ptr<InpainterBase>) -> Result<()>

impl StabilizerBaseTrait for Ptr<TwoPassStabilizer>

fn as_raw_mut_StabilizerBase(&mut self) -> *mut c_void

fn set_log(&mut self, ilog: Ptr<ILog>) -> Result<()>

fn set_radius(&mut self, val: i32) -> Result<()>

fn set_frame_source(&mut self, val: Ptr<IFrameSource>) -> Result<()>

fn set_mask_source(&mut self, val: &Ptr<IFrameSource>) -> Result<()>

fn set_motion_estimator( &mut self, val: Ptr<ImageMotionEstimatorBase> ) -> Result<()>

fn set_deblurer(&mut self, val: Ptr<DeblurerBase>) -> Result<()>

fn set_trim_ratio(&mut self, val: f32) -> Result<()>

fn set_correction_for_inclusion(&mut self, val: bool) -> Result<()>

fn set_border_mode(&mut self, val: i32) -> Result<()>

fn set_inpainter(&mut self, val: Ptr<InpainterBase>) -> Result<()>

impl StabilizerBaseTraitConst for Ptr<OnePassStabilizer>

fn as_raw_StabilizerBase(&self) -> *const c_void

fn log(&self) -> Result<Ptr<ILog>>

fn radius(&self) -> Result<i32>

fn frame_source(&self) -> Result<Ptr<IFrameSource>>

fn mask_source(&self) -> Result<Ptr<IFrameSource>>

fn motion_estimator(&self) -> Result<Ptr<ImageMotionEstimatorBase>>

fn deblurrer(&self) -> Result<Ptr<DeblurerBase>>

fn trim_ratio(&self) -> Result<f32>

fn do_correction_for_inclusion(&self) -> Result<bool>

fn border_mode(&self) -> Result<i32>

fn inpainter(&self) -> Result<Ptr<InpainterBase>>

impl StabilizerBaseTraitConst for Ptr<StabilizerBase>

fn as_raw_StabilizerBase(&self) -> *const c_void

fn log(&self) -> Result<Ptr<ILog>>

fn radius(&self) -> Result<i32>

fn frame_source(&self) -> Result<Ptr<IFrameSource>>

fn mask_source(&self) -> Result<Ptr<IFrameSource>>

fn motion_estimator(&self) -> Result<Ptr<ImageMotionEstimatorBase>>

fn deblurrer(&self) -> Result<Ptr<DeblurerBase>>

fn trim_ratio(&self) -> Result<f32>

fn do_correction_for_inclusion(&self) -> Result<bool>

fn border_mode(&self) -> Result<i32>

fn inpainter(&self) -> Result<Ptr<InpainterBase>>

impl StabilizerBaseTraitConst for Ptr<TwoPassStabilizer>

fn as_raw_StabilizerBase(&self) -> *const c_void

fn log(&self) -> Result<Ptr<ILog>>

fn radius(&self) -> Result<i32>

fn frame_source(&self) -> Result<Ptr<IFrameSource>>

fn mask_source(&self) -> Result<Ptr<IFrameSource>>

fn motion_estimator(&self) -> Result<Ptr<ImageMotionEstimatorBase>>

fn deblurrer(&self) -> Result<Ptr<DeblurerBase>>

fn trim_ratio(&self) -> Result<f32>

fn do_correction_for_inclusion(&self) -> Result<bool>

fn border_mode(&self) -> Result<i32>

fn inpainter(&self) -> Result<Ptr<InpainterBase>>

impl StandardCollectorTrait for Ptr<StandardCollector>

fn as_raw_mut_StandardCollector(&mut self) -> *mut c_void

fn init(&mut self, size: size_t) -> Result<()>

overloaded interface method

fn collect(&mut self, label: i32, dist: f64) -> Result<bool>

overloaded interface method

impl StandardCollectorTraitConst for Ptr<StandardCollector>

fn as_raw_StandardCollector(&self) -> *const c_void

fn get_min_label(&self) -> Result<i32>

Returns label with minimal distance

fn get_min_dist(&self) -> Result<f64>

Returns minimal distance value

fn get_results(&self, sorted: bool) -> Result<Vector<Tuple<(i32, f64)>>>

Return results as vector

fn get_results_def(&self) -> Result<Vector<Tuple<(i32, f64)>>>

Return results as vector

impl StarDetectorTrait for Ptr<StarDetector>

fn as_raw_mut_StarDetector(&mut self) -> *mut c_void

fn set_max_size(&mut self, _max_size: i32) -> Result<()>

fn set_response_threshold(&mut self, _response_threshold: i32) -> Result<()>

fn set_line_threshold_projected( &mut self, _line_threshold_projected: i32 ) -> Result<()>

fn set_line_threshold_binarized( &mut self, _line_threshold_binarized: i32 ) -> Result<()>

fn set_suppress_nonmax_size(&mut self, _suppress_nonmax_size: i32) -> Result<()>

impl StarDetectorTraitConst for Ptr<StarDetector>

fn as_raw_StarDetector(&self) -> *const c_void

fn get_max_size(&self) -> Result<i32>

fn get_response_threshold(&self) -> Result<i32>

fn get_line_threshold_projected(&self) -> Result<i32>

fn get_line_threshold_binarized(&self) -> Result<i32>

fn get_suppress_nonmax_size(&self) -> Result<i32>

fn get_default_name(&self) -> Result<String>

impl StatModelTrait for Ptr<ANN_MLP>

fn as_raw_mut_StatModel(&mut self) -> *mut c_void

fn train_with_data( &mut self, train_data: &Ptr<TrainData>, flags: i32 ) -> Result<bool>

Trains the statistical model

fn train_with_data_def(&mut self, train_data: &Ptr<TrainData>) -> Result<bool>

Trains the statistical model

fn train( &mut self, samples: &impl ToInputArray, layout: i32, responses: &impl ToInputArray ) -> Result<bool>

Trains the statistical model

impl StatModelTrait for Ptr<Boost>

fn as_raw_mut_StatModel(&mut self) -> *mut c_void

fn train_with_data( &mut self, train_data: &Ptr<TrainData>, flags: i32 ) -> Result<bool>

Trains the statistical model

fn train_with_data_def(&mut self, train_data: &Ptr<TrainData>) -> Result<bool>

Trains the statistical model

fn train( &mut self, samples: &impl ToInputArray, layout: i32, responses: &impl ToInputArray ) -> Result<bool>

Trains the statistical model

impl StatModelTrait for Ptr<DTrees>

fn as_raw_mut_StatModel(&mut self) -> *mut c_void

fn train_with_data( &mut self, train_data: &Ptr<TrainData>, flags: i32 ) -> Result<bool>

Trains the statistical model

fn train_with_data_def(&mut self, train_data: &Ptr<TrainData>) -> Result<bool>

Trains the statistical model

fn train( &mut self, samples: &impl ToInputArray, layout: i32, responses: &impl ToInputArray ) -> Result<bool>

Trains the statistical model

impl StatModelTrait for Ptr<EM>

fn as_raw_mut_StatModel(&mut self) -> *mut c_void

fn train_with_data( &mut self, train_data: &Ptr<TrainData>, flags: i32 ) -> Result<bool>

Trains the statistical model

fn train_with_data_def(&mut self, train_data: &Ptr<TrainData>) -> Result<bool>

Trains the statistical model

fn train( &mut self, samples: &impl ToInputArray, layout: i32, responses: &impl ToInputArray ) -> Result<bool>

Trains the statistical model

impl StatModelTrait for Ptr<KNearest>

fn as_raw_mut_StatModel(&mut self) -> *mut c_void

fn train_with_data( &mut self, train_data: &Ptr<TrainData>, flags: i32 ) -> Result<bool>

Trains the statistical model

fn train_with_data_def(&mut self, train_data: &Ptr<TrainData>) -> Result<bool>

Trains the statistical model

fn train( &mut self, samples: &impl ToInputArray, layout: i32, responses: &impl ToInputArray ) -> Result<bool>

Trains the statistical model

impl StatModelTrait for Ptr<LogisticRegression>

fn as_raw_mut_StatModel(&mut self) -> *mut c_void

fn train_with_data( &mut self, train_data: &Ptr<TrainData>, flags: i32 ) -> Result<bool>

Trains the statistical model

fn train_with_data_def(&mut self, train_data: &Ptr<TrainData>) -> Result<bool>

Trains the statistical model

fn train( &mut self, samples: &impl ToInputArray, layout: i32, responses: &impl ToInputArray ) -> Result<bool>

Trains the statistical model

impl StatModelTrait for Ptr<NormalBayesClassifier>

fn as_raw_mut_StatModel(&mut self) -> *mut c_void

fn train_with_data( &mut self, train_data: &Ptr<TrainData>, flags: i32 ) -> Result<bool>

Trains the statistical model

fn train_with_data_def(&mut self, train_data: &Ptr<TrainData>) -> Result<bool>

Trains the statistical model

fn train( &mut self, samples: &impl ToInputArray, layout: i32, responses: &impl ToInputArray ) -> Result<bool>

Trains the statistical model

impl StatModelTrait for Ptr<RTrees>

fn as_raw_mut_StatModel(&mut self) -> *mut c_void

fn train_with_data( &mut self, train_data: &Ptr<TrainData>, flags: i32 ) -> Result<bool>

Trains the statistical model

fn train_with_data_def(&mut self, train_data: &Ptr<TrainData>) -> Result<bool>

Trains the statistical model

fn train( &mut self, samples: &impl ToInputArray, layout: i32, responses: &impl ToInputArray ) -> Result<bool>

Trains the statistical model

impl StatModelTrait for Ptr<SVM>

fn as_raw_mut_StatModel(&mut self) -> *mut c_void

fn train_with_data( &mut self, train_data: &Ptr<TrainData>, flags: i32 ) -> Result<bool>

Trains the statistical model

fn train_with_data_def(&mut self, train_data: &Ptr<TrainData>) -> Result<bool>

Trains the statistical model

fn train( &mut self, samples: &impl ToInputArray, layout: i32, responses: &impl ToInputArray ) -> Result<bool>

Trains the statistical model

impl StatModelTrait for Ptr<SVMSGD>

fn as_raw_mut_StatModel(&mut self) -> *mut c_void

fn train_with_data( &mut self, train_data: &Ptr<TrainData>, flags: i32 ) -> Result<bool>

Trains the statistical model

fn train_with_data_def(&mut self, train_data: &Ptr<TrainData>) -> Result<bool>

Trains the statistical model

fn train( &mut self, samples: &impl ToInputArray, layout: i32, responses: &impl ToInputArray ) -> Result<bool>

Trains the statistical model

impl StatModelTrait for Ptr<StatModel>

fn as_raw_mut_StatModel(&mut self) -> *mut c_void

fn train_with_data( &mut self, train_data: &Ptr<TrainData>, flags: i32 ) -> Result<bool>

Trains the statistical model

fn train_with_data_def(&mut self, train_data: &Ptr<TrainData>) -> Result<bool>

Trains the statistical model

fn train( &mut self, samples: &impl ToInputArray, layout: i32, responses: &impl ToInputArray ) -> Result<bool>

Trains the statistical model

impl StatModelTraitConst for Ptr<ANN_MLP>

fn as_raw_StatModel(&self) -> *const c_void

fn get_var_count(&self) -> Result<i32>

Returns the number of variables in training samples

fn empty(&self) -> Result<bool>

fn is_trained(&self) -> Result<bool>

Returns true if the model is trained

fn is_classifier(&self) -> Result<bool>

Returns true if the model is classifier

fn calc_error( &self, data: &Ptr<TrainData>, test: bool, resp: &mut impl ToOutputArray ) -> Result<f32>

Computes error on the training or test dataset

fn predict( &self, samples: &impl ToInputArray, results: &mut impl ToOutputArray, flags: i32 ) -> Result<f32>

Predicts response(s) for the provided sample(s)

fn predict_def(&self, samples: &impl ToInputArray) -> Result<f32>

Predicts response(s) for the provided sample(s)

impl StatModelTraitConst for Ptr<Boost>

fn as_raw_StatModel(&self) -> *const c_void

fn get_var_count(&self) -> Result<i32>

Returns the number of variables in training samples

fn empty(&self) -> Result<bool>

fn is_trained(&self) -> Result<bool>

Returns true if the model is trained

fn is_classifier(&self) -> Result<bool>

Returns true if the model is classifier

fn calc_error( &self, data: &Ptr<TrainData>, test: bool, resp: &mut impl ToOutputArray ) -> Result<f32>

Computes error on the training or test dataset

fn predict( &self, samples: &impl ToInputArray, results: &mut impl ToOutputArray, flags: i32 ) -> Result<f32>

Predicts response(s) for the provided sample(s)

fn predict_def(&self, samples: &impl ToInputArray) -> Result<f32>

Predicts response(s) for the provided sample(s)

impl StatModelTraitConst for Ptr<DTrees>

fn as_raw_StatModel(&self) -> *const c_void

fn get_var_count(&self) -> Result<i32>

Returns the number of variables in training samples

fn empty(&self) -> Result<bool>

fn is_trained(&self) -> Result<bool>

Returns true if the model is trained

fn is_classifier(&self) -> Result<bool>

Returns true if the model is classifier

fn calc_error( &self, data: &Ptr<TrainData>, test: bool, resp: &mut impl ToOutputArray ) -> Result<f32>

Computes error on the training or test dataset

fn predict( &self, samples: &impl ToInputArray, results: &mut impl ToOutputArray, flags: i32 ) -> Result<f32>

Predicts response(s) for the provided sample(s)

fn predict_def(&self, samples: &impl ToInputArray) -> Result<f32>

Predicts response(s) for the provided sample(s)

impl StatModelTraitConst for Ptr<EM>

fn as_raw_StatModel(&self) -> *const c_void

fn get_var_count(&self) -> Result<i32>

Returns the number of variables in training samples

fn empty(&self) -> Result<bool>

fn is_trained(&self) -> Result<bool>

Returns true if the model is trained

fn is_classifier(&self) -> Result<bool>

Returns true if the model is classifier

fn calc_error( &self, data: &Ptr<TrainData>, test: bool, resp: &mut impl ToOutputArray ) -> Result<f32>

Computes error on the training or test dataset

fn predict( &self, samples: &impl ToInputArray, results: &mut impl ToOutputArray, flags: i32 ) -> Result<f32>

Predicts response(s) for the provided sample(s)

fn predict_def(&self, samples: &impl ToInputArray) -> Result<f32>

Predicts response(s) for the provided sample(s)

impl StatModelTraitConst for Ptr<KNearest>

fn as_raw_StatModel(&self) -> *const c_void

fn get_var_count(&self) -> Result<i32>

Returns the number of variables in training samples

fn empty(&self) -> Result<bool>

fn is_trained(&self) -> Result<bool>

Returns true if the model is trained

fn is_classifier(&self) -> Result<bool>

Returns true if the model is classifier

fn calc_error( &self, data: &Ptr<TrainData>, test: bool, resp: &mut impl ToOutputArray ) -> Result<f32>

Computes error on the training or test dataset

fn predict( &self, samples: &impl ToInputArray, results: &mut impl ToOutputArray, flags: i32 ) -> Result<f32>

Predicts response(s) for the provided sample(s)

fn predict_def(&self, samples: &impl ToInputArray) -> Result<f32>

Predicts response(s) for the provided sample(s)

impl StatModelTraitConst for Ptr<LogisticRegression>

fn as_raw_StatModel(&self) -> *const c_void

fn get_var_count(&self) -> Result<i32>

Returns the number of variables in training samples

fn empty(&self) -> Result<bool>

fn is_trained(&self) -> Result<bool>

Returns true if the model is trained

fn is_classifier(&self) -> Result<bool>

Returns true if the model is classifier

fn calc_error( &self, data: &Ptr<TrainData>, test: bool, resp: &mut impl ToOutputArray ) -> Result<f32>

Computes error on the training or test dataset

fn predict( &self, samples: &impl ToInputArray, results: &mut impl ToOutputArray, flags: i32 ) -> Result<f32>

Predicts response(s) for the provided sample(s)

fn predict_def(&self, samples: &impl ToInputArray) -> Result<f32>

Predicts response(s) for the provided sample(s)

impl StatModelTraitConst for Ptr<NormalBayesClassifier>

fn as_raw_StatModel(&self) -> *const c_void

fn get_var_count(&self) -> Result<i32>

Returns the number of variables in training samples

fn empty(&self) -> Result<bool>

fn is_trained(&self) -> Result<bool>

Returns true if the model is trained

fn is_classifier(&self) -> Result<bool>

Returns true if the model is classifier

fn calc_error( &self, data: &Ptr<TrainData>, test: bool, resp: &mut impl ToOutputArray ) -> Result<f32>

Computes error on the training or test dataset

fn predict( &self, samples: &impl ToInputArray, results: &mut impl ToOutputArray, flags: i32 ) -> Result<f32>

Predicts response(s) for the provided sample(s)

fn predict_def(&self, samples: &impl ToInputArray) -> Result<f32>

Predicts response(s) for the provided sample(s)

impl StatModelTraitConst for Ptr<RTrees>

fn as_raw_StatModel(&self) -> *const c_void

fn get_var_count(&self) -> Result<i32>

Returns the number of variables in training samples

fn empty(&self) -> Result<bool>

fn is_trained(&self) -> Result<bool>

Returns true if the model is trained

fn is_classifier(&self) -> Result<bool>

Returns true if the model is classifier

fn calc_error( &self, data: &Ptr<TrainData>, test: bool, resp: &mut impl ToOutputArray ) -> Result<f32>

Computes error on the training or test dataset

fn predict( &self, samples: &impl ToInputArray, results: &mut impl ToOutputArray, flags: i32 ) -> Result<f32>

Predicts response(s) for the provided sample(s)

fn predict_def(&self, samples: &impl ToInputArray) -> Result<f32>

Predicts response(s) for the provided sample(s)

impl StatModelTraitConst for Ptr<SVM>

fn as_raw_StatModel(&self) -> *const c_void

fn get_var_count(&self) -> Result<i32>

Returns the number of variables in training samples

fn empty(&self) -> Result<bool>

fn is_trained(&self) -> Result<bool>

Returns true if the model is trained

fn is_classifier(&self) -> Result<bool>

Returns true if the model is classifier

fn calc_error( &self, data: &Ptr<TrainData>, test: bool, resp: &mut impl ToOutputArray ) -> Result<f32>

Computes error on the training or test dataset

fn predict( &self, samples: &impl ToInputArray, results: &mut impl ToOutputArray, flags: i32 ) -> Result<f32>

Predicts response(s) for the provided sample(s)

fn predict_def(&self, samples: &impl ToInputArray) -> Result<f32>

Predicts response(s) for the provided sample(s)

impl StatModelTraitConst for Ptr<SVMSGD>

fn as_raw_StatModel(&self) -> *const c_void

fn get_var_count(&self) -> Result<i32>

Returns the number of variables in training samples

fn empty(&self) -> Result<bool>

fn is_trained(&self) -> Result<bool>

Returns true if the model is trained

fn is_classifier(&self) -> Result<bool>

Returns true if the model is classifier

fn calc_error( &self, data: &Ptr<TrainData>, test: bool, resp: &mut impl ToOutputArray ) -> Result<f32>

Computes error on the training or test dataset

fn predict( &self, samples: &impl ToInputArray, results: &mut impl ToOutputArray, flags: i32 ) -> Result<f32>

Predicts response(s) for the provided sample(s)

fn predict_def(&self, samples: &impl ToInputArray) -> Result<f32>

Predicts response(s) for the provided sample(s)

impl StatModelTraitConst for Ptr<StatModel>

fn as_raw_StatModel(&self) -> *const c_void

fn get_var_count(&self) -> Result<i32>

Returns the number of variables in training samples

fn empty(&self) -> Result<bool>

fn is_trained(&self) -> Result<bool>

Returns true if the model is trained

fn is_classifier(&self) -> Result<bool>

Returns true if the model is classifier

fn calc_error( &self, data: &Ptr<TrainData>, test: bool, resp: &mut impl ToOutputArray ) -> Result<f32>

Computes error on the training or test dataset

fn predict( &self, samples: &impl ToInputArray, results: &mut impl ToOutputArray, flags: i32 ) -> Result<f32>

Predicts response(s) for the provided sample(s)

fn predict_def(&self, samples: &impl ToInputArray) -> Result<f32>

Predicts response(s) for the provided sample(s)

impl StaticSaliencyFineGrainedTrait for Ptr<StaticSaliencyFineGrained>

fn as_raw_mut_StaticSaliencyFineGrained(&mut self) -> *mut c_void

fn compute_saliency( &mut self, image: &impl ToInputArray, saliency_map: &mut impl ToOutputArray ) -> Result<bool>

impl StaticSaliencyFineGrainedTraitConst for Ptr<StaticSaliencyFineGrained>

fn as_raw_StaticSaliencyFineGrained(&self) -> *const c_void

impl StaticSaliencySpectralResidualTrait for Ptr<StaticSaliencySpectralResidual>

fn as_raw_mut_StaticSaliencySpectralResidual(&mut self) -> *mut c_void

fn compute_saliency( &mut self, image: &impl ToInputArray, saliency_map: &mut impl ToOutputArray ) -> Result<bool>

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

fn set_image_width(&mut self, val: i32) -> Result<()>

fn set_image_height(&mut self, val: i32) -> Result<()>

impl StaticSaliencySpectralResidualTraitConst for Ptr<StaticSaliencySpectralResidual>

fn as_raw_StaticSaliencySpectralResidual(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

fn get_image_width(&self) -> Result<i32>

fn get_image_height(&self) -> Result<i32>

impl StaticSaliencyTrait for Ptr<StaticSaliency>

fn as_raw_mut_StaticSaliency(&mut self) -> *mut c_void

fn compute_binary_map( &mut self, _saliency_map: &impl ToInputArray, _binary_map: &mut impl ToOutputArray ) -> Result<bool>

This function perform a binary map of given saliency map. This is obtained in this way:

impl StaticSaliencyTrait for Ptr<StaticSaliencyFineGrained>

fn as_raw_mut_StaticSaliency(&mut self) -> *mut c_void

fn compute_binary_map( &mut self, _saliency_map: &impl ToInputArray, _binary_map: &mut impl ToOutputArray ) -> Result<bool>

This function perform a binary map of given saliency map. This is obtained in this way:

impl StaticSaliencyTrait for Ptr<StaticSaliencySpectralResidual>

fn as_raw_mut_StaticSaliency(&mut self) -> *mut c_void

fn compute_binary_map( &mut self, _saliency_map: &impl ToInputArray, _binary_map: &mut impl ToOutputArray ) -> Result<bool>

This function perform a binary map of given saliency map. This is obtained in this way:

impl StaticSaliencyTraitConst for Ptr<StaticSaliency>

fn as_raw_StaticSaliency(&self) -> *const c_void

impl StaticSaliencyTraitConst for Ptr<StaticSaliencyFineGrained>

fn as_raw_StaticSaliency(&self) -> *const c_void

impl StaticSaliencyTraitConst for Ptr<StaticSaliencySpectralResidual>

fn as_raw_StaticSaliency(&self) -> *const c_void

impl StereoBMTrait for Ptr<CUDA_StereoBM>

fn as_raw_mut_StereoBM(&mut self) -> *mut c_void

fn set_pre_filter_type(&mut self, pre_filter_type: i32) -> Result<()>

fn set_pre_filter_size(&mut self, pre_filter_size: i32) -> Result<()>

fn set_pre_filter_cap(&mut self, pre_filter_cap: i32) -> Result<()>

fn set_texture_threshold(&mut self, texture_threshold: i32) -> Result<()>

fn set_uniqueness_ratio(&mut self, uniqueness_ratio: i32) -> Result<()>

fn set_smaller_block_size(&mut self, block_size: i32) -> Result<()>

fn set_roi1(&mut self, roi1: Rect) -> Result<()>

fn set_roi2(&mut self, roi2: Rect) -> Result<()>

impl StereoBMTrait for Ptr<StereoBM>

fn as_raw_mut_StereoBM(&mut self) -> *mut c_void

fn set_pre_filter_type(&mut self, pre_filter_type: i32) -> Result<()>

fn set_pre_filter_size(&mut self, pre_filter_size: i32) -> Result<()>

fn set_pre_filter_cap(&mut self, pre_filter_cap: i32) -> Result<()>

fn set_texture_threshold(&mut self, texture_threshold: i32) -> Result<()>

fn set_uniqueness_ratio(&mut self, uniqueness_ratio: i32) -> Result<()>

fn set_smaller_block_size(&mut self, block_size: i32) -> Result<()>

fn set_roi1(&mut self, roi1: Rect) -> Result<()>

fn set_roi2(&mut self, roi2: Rect) -> Result<()>

impl StereoBMTraitConst for Ptr<CUDA_StereoBM>

fn as_raw_StereoBM(&self) -> *const c_void

fn get_pre_filter_type(&self) -> Result<i32>

fn get_pre_filter_size(&self) -> Result<i32>

fn get_pre_filter_cap(&self) -> Result<i32>

fn get_texture_threshold(&self) -> Result<i32>

fn get_uniqueness_ratio(&self) -> Result<i32>

fn get_smaller_block_size(&self) -> Result<i32>

fn get_roi1(&self) -> Result<Rect>

fn get_roi2(&self) -> Result<Rect>

impl StereoBMTraitConst for Ptr<StereoBM>

fn as_raw_StereoBM(&self) -> *const c_void

fn get_pre_filter_type(&self) -> Result<i32>

fn get_pre_filter_size(&self) -> Result<i32>

fn get_pre_filter_cap(&self) -> Result<i32>

fn get_texture_threshold(&self) -> Result<i32>

fn get_uniqueness_ratio(&self) -> Result<i32>

fn get_smaller_block_size(&self) -> Result<i32>

fn get_roi1(&self) -> Result<Rect>

fn get_roi2(&self) -> Result<Rect>

impl StereoMatcherTrait for Ptr<CUDA_StereoBM>

fn as_raw_mut_StereoMatcher(&mut self) -> *mut c_void

fn compute( &mut self, left: &impl ToInputArray, right: &impl ToInputArray, disparity: &mut impl ToOutputArray ) -> Result<()>

Computes disparity map for the specified stereo pair

fn set_min_disparity(&mut self, min_disparity: i32) -> Result<()>

fn set_num_disparities(&mut self, num_disparities: i32) -> Result<()>

fn set_block_size(&mut self, block_size: i32) -> Result<()>

fn set_speckle_window_size(&mut self, speckle_window_size: i32) -> Result<()>

fn set_speckle_range(&mut self, speckle_range: i32) -> Result<()>

fn set_disp12_max_diff(&mut self, disp12_max_diff: i32) -> Result<()>

impl StereoMatcherTrait for Ptr<CUDA_StereoBeliefPropagation>

fn as_raw_mut_StereoMatcher(&mut self) -> *mut c_void

fn compute( &mut self, left: &impl ToInputArray, right: &impl ToInputArray, disparity: &mut impl ToOutputArray ) -> Result<()>

Computes disparity map for the specified stereo pair

fn set_min_disparity(&mut self, min_disparity: i32) -> Result<()>

fn set_num_disparities(&mut self, num_disparities: i32) -> Result<()>

fn set_block_size(&mut self, block_size: i32) -> Result<()>

fn set_speckle_window_size(&mut self, speckle_window_size: i32) -> Result<()>

fn set_speckle_range(&mut self, speckle_range: i32) -> Result<()>

fn set_disp12_max_diff(&mut self, disp12_max_diff: i32) -> Result<()>

impl StereoMatcherTrait for Ptr<CUDA_StereoConstantSpaceBP>

fn as_raw_mut_StereoMatcher(&mut self) -> *mut c_void

fn compute( &mut self, left: &impl ToInputArray, right: &impl ToInputArray, disparity: &mut impl ToOutputArray ) -> Result<()>

Computes disparity map for the specified stereo pair

fn set_min_disparity(&mut self, min_disparity: i32) -> Result<()>

fn set_num_disparities(&mut self, num_disparities: i32) -> Result<()>

fn set_block_size(&mut self, block_size: i32) -> Result<()>

fn set_speckle_window_size(&mut self, speckle_window_size: i32) -> Result<()>

fn set_speckle_range(&mut self, speckle_range: i32) -> Result<()>

fn set_disp12_max_diff(&mut self, disp12_max_diff: i32) -> Result<()>

impl StereoMatcherTrait for Ptr<CUDA_StereoSGM>

fn as_raw_mut_StereoMatcher(&mut self) -> *mut c_void

fn compute( &mut self, left: &impl ToInputArray, right: &impl ToInputArray, disparity: &mut impl ToOutputArray ) -> Result<()>

Computes disparity map for the specified stereo pair

fn set_min_disparity(&mut self, min_disparity: i32) -> Result<()>

fn set_num_disparities(&mut self, num_disparities: i32) -> Result<()>

fn set_block_size(&mut self, block_size: i32) -> Result<()>

fn set_speckle_window_size(&mut self, speckle_window_size: i32) -> Result<()>

fn set_speckle_range(&mut self, speckle_range: i32) -> Result<()>

fn set_disp12_max_diff(&mut self, disp12_max_diff: i32) -> Result<()>

impl StereoMatcherTrait for Ptr<StereoBM>

fn as_raw_mut_StereoMatcher(&mut self) -> *mut c_void

fn compute( &mut self, left: &impl ToInputArray, right: &impl ToInputArray, disparity: &mut impl ToOutputArray ) -> Result<()>

Computes disparity map for the specified stereo pair

fn set_min_disparity(&mut self, min_disparity: i32) -> Result<()>

fn set_num_disparities(&mut self, num_disparities: i32) -> Result<()>

fn set_block_size(&mut self, block_size: i32) -> Result<()>

fn set_speckle_window_size(&mut self, speckle_window_size: i32) -> Result<()>

fn set_speckle_range(&mut self, speckle_range: i32) -> Result<()>

fn set_disp12_max_diff(&mut self, disp12_max_diff: i32) -> Result<()>

impl StereoMatcherTrait for Ptr<StereoMatcher>

fn as_raw_mut_StereoMatcher(&mut self) -> *mut c_void

fn compute( &mut self, left: &impl ToInputArray, right: &impl ToInputArray, disparity: &mut impl ToOutputArray ) -> Result<()>

Computes disparity map for the specified stereo pair

fn set_min_disparity(&mut self, min_disparity: i32) -> Result<()>

fn set_num_disparities(&mut self, num_disparities: i32) -> Result<()>

fn set_block_size(&mut self, block_size: i32) -> Result<()>

fn set_speckle_window_size(&mut self, speckle_window_size: i32) -> Result<()>

fn set_speckle_range(&mut self, speckle_range: i32) -> Result<()>

fn set_disp12_max_diff(&mut self, disp12_max_diff: i32) -> Result<()>

impl StereoMatcherTrait for Ptr<StereoSGBM>

fn as_raw_mut_StereoMatcher(&mut self) -> *mut c_void

fn compute( &mut self, left: &impl ToInputArray, right: &impl ToInputArray, disparity: &mut impl ToOutputArray ) -> Result<()>

Computes disparity map for the specified stereo pair

fn set_min_disparity(&mut self, min_disparity: i32) -> Result<()>

fn set_num_disparities(&mut self, num_disparities: i32) -> Result<()>

fn set_block_size(&mut self, block_size: i32) -> Result<()>

fn set_speckle_window_size(&mut self, speckle_window_size: i32) -> Result<()>

fn set_speckle_range(&mut self, speckle_range: i32) -> Result<()>

fn set_disp12_max_diff(&mut self, disp12_max_diff: i32) -> Result<()>

impl StereoMatcherTraitConst for Ptr<CUDA_StereoBM>

fn as_raw_StereoMatcher(&self) -> *const c_void

fn get_min_disparity(&self) -> Result<i32>

fn get_num_disparities(&self) -> Result<i32>

fn get_block_size(&self) -> Result<i32>

fn get_speckle_window_size(&self) -> Result<i32>

fn get_speckle_range(&self) -> Result<i32>

fn get_disp12_max_diff(&self) -> Result<i32>

impl StereoMatcherTraitConst for Ptr<CUDA_StereoBeliefPropagation>

fn as_raw_StereoMatcher(&self) -> *const c_void

fn get_min_disparity(&self) -> Result<i32>

fn get_num_disparities(&self) -> Result<i32>

fn get_block_size(&self) -> Result<i32>

fn get_speckle_window_size(&self) -> Result<i32>

fn get_speckle_range(&self) -> Result<i32>

fn get_disp12_max_diff(&self) -> Result<i32>

impl StereoMatcherTraitConst for Ptr<CUDA_StereoConstantSpaceBP>

fn as_raw_StereoMatcher(&self) -> *const c_void

fn get_min_disparity(&self) -> Result<i32>

fn get_num_disparities(&self) -> Result<i32>

fn get_block_size(&self) -> Result<i32>

fn get_speckle_window_size(&self) -> Result<i32>

fn get_speckle_range(&self) -> Result<i32>

fn get_disp12_max_diff(&self) -> Result<i32>

impl StereoMatcherTraitConst for Ptr<CUDA_StereoSGM>

fn as_raw_StereoMatcher(&self) -> *const c_void

fn get_min_disparity(&self) -> Result<i32>

fn get_num_disparities(&self) -> Result<i32>

fn get_block_size(&self) -> Result<i32>

fn get_speckle_window_size(&self) -> Result<i32>

fn get_speckle_range(&self) -> Result<i32>

fn get_disp12_max_diff(&self) -> Result<i32>

impl StereoMatcherTraitConst for Ptr<StereoBM>

fn as_raw_StereoMatcher(&self) -> *const c_void

fn get_min_disparity(&self) -> Result<i32>

fn get_num_disparities(&self) -> Result<i32>

fn get_block_size(&self) -> Result<i32>

fn get_speckle_window_size(&self) -> Result<i32>

fn get_speckle_range(&self) -> Result<i32>

fn get_disp12_max_diff(&self) -> Result<i32>

impl StereoMatcherTraitConst for Ptr<StereoMatcher>

fn as_raw_StereoMatcher(&self) -> *const c_void

fn get_min_disparity(&self) -> Result<i32>

fn get_num_disparities(&self) -> Result<i32>

fn get_block_size(&self) -> Result<i32>

fn get_speckle_window_size(&self) -> Result<i32>

fn get_speckle_range(&self) -> Result<i32>

fn get_disp12_max_diff(&self) -> Result<i32>

impl StereoMatcherTraitConst for Ptr<StereoSGBM>

fn as_raw_StereoMatcher(&self) -> *const c_void

fn get_min_disparity(&self) -> Result<i32>

fn get_num_disparities(&self) -> Result<i32>

fn get_block_size(&self) -> Result<i32>

fn get_speckle_window_size(&self) -> Result<i32>

fn get_speckle_range(&self) -> Result<i32>

fn get_disp12_max_diff(&self) -> Result<i32>

impl StereoSGBMTrait for Ptr<CUDA_StereoSGM>

fn as_raw_mut_StereoSGBM(&mut self) -> *mut c_void

fn set_pre_filter_cap(&mut self, pre_filter_cap: i32) -> Result<()>

fn set_uniqueness_ratio(&mut self, uniqueness_ratio: i32) -> Result<()>

fn set_p1(&mut self, p1: i32) -> Result<()>

fn set_p2(&mut self, p2: i32) -> Result<()>

fn set_mode(&mut self, mode: i32) -> Result<()>

impl StereoSGBMTrait for Ptr<StereoSGBM>

fn as_raw_mut_StereoSGBM(&mut self) -> *mut c_void

fn set_pre_filter_cap(&mut self, pre_filter_cap: i32) -> Result<()>

fn set_uniqueness_ratio(&mut self, uniqueness_ratio: i32) -> Result<()>

fn set_p1(&mut self, p1: i32) -> Result<()>

fn set_p2(&mut self, p2: i32) -> Result<()>

fn set_mode(&mut self, mode: i32) -> Result<()>

impl StereoSGBMTraitConst for Ptr<CUDA_StereoSGM>

fn as_raw_StereoSGBM(&self) -> *const c_void

fn get_pre_filter_cap(&self) -> Result<i32>

fn get_uniqueness_ratio(&self) -> Result<i32>

fn get_p1(&self) -> Result<i32>

fn get_p2(&self) -> Result<i32>

fn get_mode(&self) -> Result<i32>

impl StereoSGBMTraitConst for Ptr<StereoSGBM>

fn as_raw_StereoSGBM(&self) -> *const c_void

fn get_pre_filter_cap(&self) -> Result<i32>

fn get_uniqueness_ratio(&self) -> Result<i32>

fn get_p1(&self) -> Result<i32>

fn get_p2(&self) -> Result<i32>

fn get_mode(&self) -> Result<i32>

impl StereographicWarperTrait for Ptr<StereographicWarper>

fn as_raw_mut_StereographicWarper(&mut self) -> *mut c_void

impl StereographicWarperTraitConst for Ptr<StereographicWarper>

fn as_raw_StereographicWarper(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl StitcherTrait for Ptr<Stitcher>

fn as_raw_mut_Stitcher(&mut self) -> *mut c_void

fn set_registration_resol(&mut self, resol_mpx: f64) -> Result<()>

fn set_seam_estimation_resol(&mut self, resol_mpx: f64) -> Result<()>

fn set_compositing_resol(&mut self, resol_mpx: f64) -> Result<()>

fn set_pano_confidence_thresh(&mut self, conf_thresh: f64) -> Result<()>

fn set_wave_correction(&mut self, flag: bool) -> Result<()>

fn set_interpolation_flags( &mut self, interp_flags: InterpolationFlags ) -> Result<()>

fn set_wave_correct_kind(&mut self, kind: Detail_WaveCorrectKind) -> Result<()>

fn features_finder_1(&mut self) -> Result<Ptr<Feature2D>>

fn set_features_finder(&mut self, features_finder: Ptr<Feature2D>) -> Result<()>

fn features_matcher_1(&mut self) -> Result<Ptr<Detail_FeaturesMatcher>>

fn set_features_matcher( &mut self, features_matcher: Ptr<Detail_FeaturesMatcher> ) -> Result<()>

fn set_matching_mask(&mut self, mask: &impl UMatTraitConst) -> Result<()>

fn bundle_adjuster_1(&mut self) -> Result<Ptr<Detail_BundleAdjusterBase>>

fn set_bundle_adjuster( &mut self, bundle_adjuster: Ptr<Detail_BundleAdjusterBase> ) -> Result<()>

fn estimator_1(&mut self) -> Result<Ptr<Detail_Estimator>>

fn set_estimator(&mut self, estimator: Ptr<Detail_Estimator>) -> Result<()>

fn warper_1(&mut self) -> Result<Ptr<WarperCreator>>

fn set_warper(&mut self, creator: Ptr<WarperCreator>) -> Result<()>

fn exposure_compensator_1(&mut self) -> Result<Ptr<Detail_ExposureCompensator>>

fn set_exposure_compensator( &mut self, exposure_comp: Ptr<Detail_ExposureCompensator> ) -> Result<()>

fn seam_finder_1(&mut self) -> Result<Ptr<Detail_SeamFinder>>

fn set_seam_finder(&mut self, seam_finder: Ptr<Detail_SeamFinder>) -> Result<()>

fn blender_1(&mut self) -> Result<Ptr<Detail_Blender>>

fn set_blender(&mut self, b: Ptr<Detail_Blender>) -> Result<()>

fn estimate_transform( &mut self, images: &impl ToInputArray, masks: &impl ToInputArray ) -> Result<Stitcher_Status>

These functions try to match the given images and to estimate rotations of each camera.

fn estimate_transform_def( &mut self, images: &impl ToInputArray ) -> Result<Stitcher_Status>

These functions try to match the given images and to estimate rotations of each camera.

fn set_transform( &mut self, images: &impl ToInputArray, cameras: &Vector<Detail_CameraParams>, component: &Vector<i32> ) -> Result<Stitcher_Status>

These function restors camera rotation and camera intrinsics of each camera that can be got with Stitcher::cameras call

fn set_transform_1( &mut self, images: &impl ToInputArray, cameras: &Vector<Detail_CameraParams> ) -> Result<Stitcher_Status>

These function restors camera rotation and camera intrinsics of each camera that can be got with Stitcher::cameras call

fn compose_panorama( &mut self, pano: &mut impl ToOutputArray ) -> Result<Stitcher_Status>

These functions try to compose the given images (or images stored internally from the other function calls) into the final pano under the assumption that the image transformations were estimated before.

fn compose_panorama_images( &mut self, images: &impl ToInputArray, pano: &mut impl ToOutputArray ) -> Result<Stitcher_Status>

These functions try to compose the given images (or images stored internally from the other function calls) into the final pano under the assumption that the image transformations were estimated before.

fn stitch( &mut self, images: &impl ToInputArray, pano: &mut impl ToOutputArray ) -> Result<Stitcher_Status>

These functions try to stitch the given images.

fn stitch_mask( &mut self, images: &impl ToInputArray, masks: &impl ToInputArray, pano: &mut impl ToOutputArray ) -> Result<Stitcher_Status>

These functions try to stitch the given images.

impl StitcherTraitConst for Ptr<Stitcher>

fn as_raw_Stitcher(&self) -> *const c_void

fn registration_resol(&self) -> Result<f64>

fn seam_estimation_resol(&self) -> Result<f64>

fn compositing_resol(&self) -> Result<f64>

fn pano_confidence_thresh(&self) -> Result<f64>

fn wave_correction(&self) -> Result<bool>

fn interpolation_flags(&self) -> Result<InterpolationFlags>

fn wave_correct_kind(&self) -> Result<Detail_WaveCorrectKind>

fn features_finder(&self) -> Result<Ptr<Feature2D>>

fn features_matcher(&self) -> Result<Ptr<Detail_FeaturesMatcher>>

fn matching_mask(&self) -> Result<UMat>

fn bundle_adjuster(&self) -> Result<Ptr<Detail_BundleAdjusterBase>>

fn estimator(&self) -> Result<Ptr<Detail_Estimator>>

fn warper(&self) -> Result<Ptr<WarperCreator>>

fn exposure_compensator(&self) -> Result<Ptr<Detail_ExposureCompensator>>

fn seam_finder(&self) -> Result<Ptr<Detail_SeamFinder>>

fn blender(&self) -> Result<Ptr<Detail_Blender>>

fn component(&self) -> Result<Vector<i32>>

fn cameras(&self) -> Result<Vector<Detail_CameraParams>>

fn work_scale(&self) -> Result<f64>

fn result_mask(&self) -> Result<UMat>

Return the mask of the panorama.

impl StructuredEdgeDetectionTrait for Ptr<StructuredEdgeDetection>

fn as_raw_mut_StructuredEdgeDetection(&mut self) -> *mut c_void

impl StructuredEdgeDetectionTraitConst for Ptr<StructuredEdgeDetection>

fn as_raw_StructuredEdgeDetection(&self) -> *const c_void

fn detect_edges( &self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

The function detects edges in src and draw them to dst.

fn compute_orientation( &self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

The function computes orientation from edge image.

fn edges_nms( &self, edge_image: &impl ToInputArray, orientation_image: &impl ToInputArray, dst: &mut impl ToOutputArray, r: i32, s: i32, m: f32, is_parallel: bool ) -> Result<()>

The function edgenms in edge image and suppress edges where edge is stronger in orthogonal direction.

fn edges_nms_def( &self, edge_image: &impl ToInputArray, orientation_image: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

The function edgenms in edge image and suppress edges where edge is stronger in orthogonal direction.

impl StructuredLightPatternTrait for Ptr<GrayCodePattern>

fn as_raw_mut_StructuredLightPattern(&mut self) -> *mut c_void

fn generate(&mut self, pattern_images: &mut impl ToOutputArray) -> Result<bool>

Generates the structured light pattern to project.

impl StructuredLightPatternTrait for Ptr<SinusoidalPattern>

fn as_raw_mut_StructuredLightPattern(&mut self) -> *mut c_void

fn generate(&mut self, pattern_images: &mut impl ToOutputArray) -> Result<bool>

Generates the structured light pattern to project.

impl StructuredLightPatternTrait for Ptr<StructuredLightPattern>

fn as_raw_mut_StructuredLightPattern(&mut self) -> *mut c_void

fn generate(&mut self, pattern_images: &mut impl ToOutputArray) -> Result<bool>

Generates the structured light pattern to project.

impl StructuredLightPatternTraitConst for Ptr<GrayCodePattern>

fn as_raw_StructuredLightPattern(&self) -> *const c_void

fn decode( &self, pattern_images: &Vector<Vector<Mat>>, disparity_map: &mut impl ToOutputArray, black_images: &impl ToInputArray, white_images: &impl ToInputArray, flags: i32 ) -> Result<bool>

Decodes the structured light pattern, generating a disparity map

fn decode_def( &self, pattern_images: &Vector<Vector<Mat>>, disparity_map: &mut impl ToOutputArray ) -> Result<bool>

Decodes the structured light pattern, generating a disparity map

impl StructuredLightPatternTraitConst for Ptr<SinusoidalPattern>

fn as_raw_StructuredLightPattern(&self) -> *const c_void

fn decode( &self, pattern_images: &Vector<Vector<Mat>>, disparity_map: &mut impl ToOutputArray, black_images: &impl ToInputArray, white_images: &impl ToInputArray, flags: i32 ) -> Result<bool>

Decodes the structured light pattern, generating a disparity map

fn decode_def( &self, pattern_images: &Vector<Vector<Mat>>, disparity_map: &mut impl ToOutputArray ) -> Result<bool>

Decodes the structured light pattern, generating a disparity map

impl StructuredLightPatternTraitConst for Ptr<StructuredLightPattern>

fn as_raw_StructuredLightPattern(&self) -> *const c_void

fn decode( &self, pattern_images: &Vector<Vector<Mat>>, disparity_map: &mut impl ToOutputArray, black_images: &impl ToInputArray, white_images: &impl ToInputArray, flags: i32 ) -> Result<bool>

Decodes the structured light pattern, generating a disparity map

fn decode_def( &self, pattern_images: &Vector<Vector<Mat>>, disparity_map: &mut impl ToOutputArray ) -> Result<bool>

Decodes the structured light pattern, generating a disparity map

impl SuperRes_BroxOpticalFlowTrait for Ptr<SuperRes_BroxOpticalFlow>

fn as_raw_mut_SuperRes_BroxOpticalFlow(&mut self) -> *mut c_void

fn set_alpha(&mut self, val: f64) -> Result<()>

Flow smoothness

fn set_gamma(&mut self, val: f64) -> Result<()>

Gradient constancy importance

fn set_scale_factor(&mut self, val: f64) -> Result<()>

Pyramid scale factor

fn set_inner_iterations(&mut self, val: i32) -> Result<()>

Number of lagged non-linearity iterations (inner loop)

fn set_outer_iterations(&mut self, val: i32) -> Result<()>

Number of warping iterations (number of pyramid levels)

fn set_solver_iterations(&mut self, val: i32) -> Result<()>

Number of linear system solver iterations

impl SuperRes_BroxOpticalFlowTraitConst for Ptr<SuperRes_BroxOpticalFlow>

fn as_raw_SuperRes_BroxOpticalFlow(&self) -> *const c_void

fn get_alpha(&self) -> Result<f64>

Flow smoothness

fn get_gamma(&self) -> Result<f64>

Gradient constancy importance

fn get_scale_factor(&self) -> Result<f64>

Pyramid scale factor

fn get_inner_iterations(&self) -> Result<i32>

Number of lagged non-linearity iterations (inner loop)

fn get_outer_iterations(&self) -> Result<i32>

Number of warping iterations (number of pyramid levels)

fn get_solver_iterations(&self) -> Result<i32>

Number of linear system solver iterations

impl SuperRes_DenseOpticalFlowExtTrait for Ptr<SuperRes_BroxOpticalFlow>

fn as_raw_mut_SuperRes_DenseOpticalFlowExt(&mut self) -> *mut c_void

fn calc( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, flow1: &mut impl ToOutputArray, flow2: &mut impl ToOutputArray ) -> Result<()>

C++ default parameters

fn calc_def( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, flow1: &mut impl ToOutputArray ) -> Result<()>

Note

fn collect_garbage(&mut self) -> Result<()>

impl SuperRes_DenseOpticalFlowExtTrait for Ptr<SuperRes_DenseOpticalFlowExt>

fn as_raw_mut_SuperRes_DenseOpticalFlowExt(&mut self) -> *mut c_void

fn calc( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, flow1: &mut impl ToOutputArray, flow2: &mut impl ToOutputArray ) -> Result<()>

C++ default parameters

fn calc_def( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, flow1: &mut impl ToOutputArray ) -> Result<()>

Note

fn collect_garbage(&mut self) -> Result<()>

impl SuperRes_DenseOpticalFlowExtTrait for Ptr<SuperRes_DualTVL1OpticalFlow>

fn as_raw_mut_SuperRes_DenseOpticalFlowExt(&mut self) -> *mut c_void

fn calc( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, flow1: &mut impl ToOutputArray, flow2: &mut impl ToOutputArray ) -> Result<()>

C++ default parameters

fn calc_def( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, flow1: &mut impl ToOutputArray ) -> Result<()>

Note

fn collect_garbage(&mut self) -> Result<()>

impl SuperRes_DenseOpticalFlowExtTrait for Ptr<SuperRes_FarnebackOpticalFlow>

fn as_raw_mut_SuperRes_DenseOpticalFlowExt(&mut self) -> *mut c_void

fn calc( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, flow1: &mut impl ToOutputArray, flow2: &mut impl ToOutputArray ) -> Result<()>

C++ default parameters

fn calc_def( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, flow1: &mut impl ToOutputArray ) -> Result<()>

Note

fn collect_garbage(&mut self) -> Result<()>

impl SuperRes_DenseOpticalFlowExtTrait for Ptr<SuperRes_PyrLKOpticalFlow>

fn as_raw_mut_SuperRes_DenseOpticalFlowExt(&mut self) -> *mut c_void

fn calc( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, flow1: &mut impl ToOutputArray, flow2: &mut impl ToOutputArray ) -> Result<()>

C++ default parameters

fn calc_def( &mut self, frame0: &impl ToInputArray, frame1: &impl ToInputArray, flow1: &mut impl ToOutputArray ) -> Result<()>

Note

fn collect_garbage(&mut self) -> Result<()>

impl SuperRes_DenseOpticalFlowExtTraitConst for Ptr<SuperRes_BroxOpticalFlow>

fn as_raw_SuperRes_DenseOpticalFlowExt(&self) -> *const c_void

impl SuperRes_DenseOpticalFlowExtTraitConst for Ptr<SuperRes_DenseOpticalFlowExt>

fn as_raw_SuperRes_DenseOpticalFlowExt(&self) -> *const c_void

impl SuperRes_DenseOpticalFlowExtTraitConst for Ptr<SuperRes_DualTVL1OpticalFlow>

fn as_raw_SuperRes_DenseOpticalFlowExt(&self) -> *const c_void

impl SuperRes_DenseOpticalFlowExtTraitConst for Ptr<SuperRes_FarnebackOpticalFlow>

fn as_raw_SuperRes_DenseOpticalFlowExt(&self) -> *const c_void

impl SuperRes_DenseOpticalFlowExtTraitConst for Ptr<SuperRes_PyrLKOpticalFlow>

fn as_raw_SuperRes_DenseOpticalFlowExt(&self) -> *const c_void

impl SuperRes_DualTVL1OpticalFlowTrait for Ptr<SuperRes_DualTVL1OpticalFlow>

fn as_raw_mut_SuperRes_DualTVL1OpticalFlow(&mut self) -> *mut c_void

fn set_tau(&mut self, val: f64) -> Result<()>

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fn set_lambda(&mut self, val: f64) -> Result<()>

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fn set_theta(&mut self, val: f64) -> Result<()>

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fn set_scales_number(&mut self, val: i32) -> Result<()>

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fn set_warpings_number(&mut self, val: i32) -> Result<()>

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fn set_epsilon(&mut self, val: f64) -> Result<()>

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fn set_iterations(&mut self, val: i32) -> Result<()>

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fn set_use_initial_flow(&mut self, val: bool) -> Result<()>

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impl SuperRes_DualTVL1OpticalFlowTraitConst for Ptr<SuperRes_DualTVL1OpticalFlow>

fn as_raw_SuperRes_DualTVL1OpticalFlow(&self) -> *const c_void

fn get_tau(&self) -> Result<f64>

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fn get_lambda(&self) -> Result<f64>

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fn get_theta(&self) -> Result<f64>

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fn get_scales_number(&self) -> Result<i32>

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fn get_warpings_number(&self) -> Result<i32>

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fn get_epsilon(&self) -> Result<f64>

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fn get_iterations(&self) -> Result<i32>

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fn get_use_initial_flow(&self) -> Result<bool>

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impl SuperRes_FarnebackOpticalFlowTrait for Ptr<SuperRes_FarnebackOpticalFlow>

fn as_raw_mut_SuperRes_FarnebackOpticalFlow(&mut self) -> *mut c_void

fn set_pyr_scale(&mut self, val: f64) -> Result<()>

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fn set_levels_number(&mut self, val: i32) -> Result<()>

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fn set_window_size(&mut self, val: i32) -> Result<()>

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fn set_iterations(&mut self, val: i32) -> Result<()>

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fn set_poly_n(&mut self, val: i32) -> Result<()>

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fn set_poly_sigma(&mut self, val: f64) -> Result<()>

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fn set_flags(&mut self, val: i32) -> Result<()>

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impl SuperRes_FarnebackOpticalFlowTraitConst for Ptr<SuperRes_FarnebackOpticalFlow>

fn as_raw_SuperRes_FarnebackOpticalFlow(&self) -> *const c_void

fn get_pyr_scale(&self) -> Result<f64>

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fn get_levels_number(&self) -> Result<i32>

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fn get_window_size(&self) -> Result<i32>

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fn get_iterations(&self) -> Result<i32>

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fn get_poly_n(&self) -> Result<i32>

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fn get_poly_sigma(&self) -> Result<f64>

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fn get_flags(&self) -> Result<i32>

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impl SuperRes_FrameSourceTrait for Ptr<SuperRes_FrameSource>

fn as_raw_mut_SuperRes_FrameSource(&mut self) -> *mut c_void

fn next_frame(&mut self, frame: &mut impl ToOutputArray) -> Result<()>

fn reset(&mut self) -> Result<()>

impl SuperRes_FrameSourceTrait for Ptr<SuperRes_SuperResolution>

fn as_raw_mut_SuperRes_FrameSource(&mut self) -> *mut c_void

fn next_frame(&mut self, frame: &mut impl ToOutputArray) -> Result<()>

fn reset(&mut self) -> Result<()>

impl SuperRes_FrameSourceTraitConst for Ptr<SuperRes_FrameSource>

fn as_raw_SuperRes_FrameSource(&self) -> *const c_void

impl SuperRes_FrameSourceTraitConst for Ptr<SuperRes_SuperResolution>

fn as_raw_SuperRes_FrameSource(&self) -> *const c_void

impl SuperRes_PyrLKOpticalFlowTrait for Ptr<SuperRes_PyrLKOpticalFlow>

fn as_raw_mut_SuperRes_PyrLKOpticalFlow(&mut self) -> *mut c_void

fn set_window_size(&mut self, val: i32) -> Result<()>

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fn set_max_level(&mut self, val: i32) -> Result<()>

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fn set_iterations(&mut self, val: i32) -> Result<()>

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impl SuperRes_PyrLKOpticalFlowTraitConst for Ptr<SuperRes_PyrLKOpticalFlow>

fn as_raw_SuperRes_PyrLKOpticalFlow(&self) -> *const c_void

fn get_window_size(&self) -> Result<i32>

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fn get_max_level(&self) -> Result<i32>

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fn get_iterations(&self) -> Result<i32>

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impl SuperRes_SuperResolutionTrait for Ptr<SuperRes_SuperResolution>

fn as_raw_mut_SuperRes_SuperResolution(&mut self) -> *mut c_void

fn set_input(&mut self, frame_source: &Ptr<SuperRes_FrameSource>) -> Result<()>

Set input frame source for Super Resolution algorithm.

fn next_frame(&mut self, frame: &mut impl ToOutputArray) -> Result<()>

Process next frame from input and return output result.

fn reset(&mut self) -> Result<()>

fn collect_garbage(&mut self) -> Result<()>

Clear all inner buffers.

fn set_scale(&mut self, val: i32) -> Result<()>

Scale factor

fn set_iterations(&mut self, val: i32) -> Result<()>

Iterations count

fn set_tau(&mut self, val: f64) -> Result<()>

Asymptotic value of steepest descent method

fn set_lambda(&mut self, val: f64) -> Result<()>

Weight parameter to balance data term and smoothness term

fn set_alpha(&mut self, val: f64) -> Result<()>

Parameter of spacial distribution in Bilateral-TV

fn set_kernel_size(&mut self, val: i32) -> Result<()>

Kernel size of Bilateral-TV filter

fn set_blur_kernel_size(&mut self, val: i32) -> Result<()>

Gaussian blur kernel size

fn set_blur_sigma(&mut self, val: f64) -> Result<()>

Gaussian blur sigma

fn set_temporal_area_radius(&mut self, val: i32) -> Result<()>

Radius of the temporal search area

fn set_optical_flow( &mut self, val: &Ptr<SuperRes_DenseOpticalFlowExt> ) -> Result<()>

Dense optical flow algorithm

impl SuperRes_SuperResolutionTraitConst for Ptr<SuperRes_SuperResolution>

fn as_raw_SuperRes_SuperResolution(&self) -> *const c_void

fn get_scale(&self) -> Result<i32>

Scale factor

fn get_iterations(&self) -> Result<i32>

Iterations count

fn get_tau(&self) -> Result<f64>

Asymptotic value of steepest descent method

fn get_lambda(&self) -> Result<f64>

Weight parameter to balance data term and smoothness term

fn get_alpha(&self) -> Result<f64>

Parameter of spacial distribution in Bilateral-TV

fn get_kernel_size(&self) -> Result<i32>

Kernel size of Bilateral-TV filter

fn get_blur_kernel_size(&self) -> Result<i32>

Gaussian blur kernel size

fn get_blur_sigma(&self) -> Result<f64>

Gaussian blur sigma

fn get_temporal_area_radius(&self) -> Result<i32>

Radius of the temporal search area

fn get_optical_flow(&self) -> Result<Ptr<SuperRes_DenseOpticalFlowExt>>

Dense optical flow algorithm

impl SuperpixelLSCTrait for Ptr<SuperpixelLSC>

fn as_raw_mut_SuperpixelLSC(&mut self) -> *mut c_void

fn iterate(&mut self, num_iterations: i32) -> Result<()>

Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelLSC object.

fn iterate_def(&mut self) -> Result<()>

Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelLSC object.

fn enforce_label_connectivity(&mut self, min_element_size: i32) -> Result<()>

Enforce label connectivity.

fn enforce_label_connectivity_def(&mut self) -> Result<()>

Enforce label connectivity.

impl SuperpixelLSCTraitConst for Ptr<SuperpixelLSC>

fn as_raw_SuperpixelLSC(&self) -> *const c_void

fn get_number_of_superpixels(&self) -> Result<i32>

Calculates the actual amount of superpixels on a given segmentation computed and stored in SuperpixelLSC object.

fn get_labels(&self, labels_out: &mut impl ToOutputArray) -> Result<()>

Returns the segmentation labeling of the image.

fn get_label_contour_mask( &self, image: &mut impl ToOutputArray, thick_line: bool ) -> Result<()>

Returns the mask of the superpixel segmentation stored in SuperpixelLSC object.

fn get_label_contour_mask_def( &self, image: &mut impl ToOutputArray ) -> Result<()>

Returns the mask of the superpixel segmentation stored in SuperpixelLSC object.

impl SuperpixelSEEDSTrait for Ptr<SuperpixelSEEDS>

fn as_raw_mut_SuperpixelSEEDS(&mut self) -> *mut c_void

fn get_number_of_superpixels(&mut self) -> Result<i32>

Calculates the superpixel segmentation on a given image stored in SuperpixelSEEDS object.

fn iterate( &mut self, img: &impl ToInputArray, num_iterations: i32 ) -> Result<()>

Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelSEEDS object.

fn iterate_def(&mut self, img: &impl ToInputArray) -> Result<()>

Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelSEEDS object.

fn get_labels(&mut self, labels_out: &mut impl ToOutputArray) -> Result<()>

Returns the segmentation labeling of the image.

fn get_label_contour_mask( &mut self, image: &mut impl ToOutputArray, thick_line: bool ) -> Result<()>

Returns the mask of the superpixel segmentation stored in SuperpixelSEEDS object.

fn get_label_contour_mask_def( &mut self, image: &mut impl ToOutputArray ) -> Result<()>

Returns the mask of the superpixel segmentation stored in SuperpixelSEEDS object.

impl SuperpixelSEEDSTraitConst for Ptr<SuperpixelSEEDS>

fn as_raw_SuperpixelSEEDS(&self) -> *const c_void

impl SuperpixelSLICTrait for Ptr<SuperpixelSLIC>

fn as_raw_mut_SuperpixelSLIC(&mut self) -> *mut c_void

fn iterate(&mut self, num_iterations: i32) -> Result<()>

Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelSLIC object.

fn iterate_def(&mut self) -> Result<()>

Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelSLIC object.

fn enforce_label_connectivity(&mut self, min_element_size: i32) -> Result<()>

Enforce label connectivity.

fn enforce_label_connectivity_def(&mut self) -> Result<()>

Enforce label connectivity.

impl SuperpixelSLICTraitConst for Ptr<SuperpixelSLIC>

fn as_raw_SuperpixelSLIC(&self) -> *const c_void

fn get_number_of_superpixels(&self) -> Result<i32>

Calculates the actual amount of superpixels on a given segmentation computed and stored in SuperpixelSLIC object.

fn get_labels(&self, labels_out: &mut impl ToOutputArray) -> Result<()>

Returns the segmentation labeling of the image.

fn get_label_contour_mask( &self, image: &mut impl ToOutputArray, thick_line: bool ) -> Result<()>

Returns the mask of the superpixel segmentation stored in SuperpixelSLIC object.

fn get_label_contour_mask_def( &self, image: &mut impl ToOutputArray ) -> Result<()>

Returns the mask of the superpixel segmentation stored in SuperpixelSLIC object.

impl SwishLayerTrait for Ptr<SwishLayer>

fn as_raw_mut_SwishLayer(&mut self) -> *mut c_void

impl SwishLayerTraitConst for Ptr<SwishLayer>

fn as_raw_SwishLayer(&self) -> *const c_void

impl SyntheticSequenceGeneratorTrait for Ptr<SyntheticSequenceGenerator>

fn as_raw_mut_SyntheticSequenceGenerator(&mut self) -> *mut c_void

fn get_next_frame( &mut self, frame: &mut impl ToOutputArray, gt_mask: &mut impl ToOutputArray ) -> Result<()>

Obtain the next frame in the sequence.

impl SyntheticSequenceGeneratorTraitConst for Ptr<SyntheticSequenceGenerator>

fn as_raw_SyntheticSequenceGenerator(&self) -> *const c_void

impl TBMRTrait for Ptr<TBMR>

fn as_raw_mut_TBMR(&mut self) -> *mut c_void

fn set_min_area(&mut self, min_area: i32) -> Result<()>

fn set_max_area_relative(&mut self, max_area: f32) -> Result<()>

fn set_scale_factor(&mut self, scale_factor: f32) -> Result<()>

fn set_n_scales(&mut self, n_scales: i32) -> Result<()>

impl TBMRTraitConst for Ptr<TBMR>

fn as_raw_TBMR(&self) -> *const c_void

fn get_min_area(&self) -> Result<i32>

fn get_max_area_relative(&self) -> Result<f32>

fn get_scale_factor(&self) -> Result<f32>

fn get_n_scales(&self) -> Result<i32>

impl TEBLIDTrait for Ptr<TEBLID>

fn as_raw_mut_TEBLID(&mut self) -> *mut c_void

impl TEBLIDTraitConst for Ptr<TEBLID>

fn as_raw_TEBLID(&self) -> *const c_void

fn get_default_name(&self) -> Result<String>

impl TanHLayerTrait for Ptr<TanHLayer>

fn as_raw_mut_TanHLayer(&mut self) -> *mut c_void

impl TanHLayerTraitConst for Ptr<TanHLayer>

fn as_raw_TanHLayer(&self) -> *const c_void

impl TanLayerTrait for Ptr<TanLayer>

fn as_raw_mut_TanLayer(&mut self) -> *mut c_void

impl TanLayerTraitConst for Ptr<TanLayer>

fn as_raw_TanLayer(&self) -> *const c_void

impl TextDetectorCNNTrait for Ptr<TextDetectorCNN>

fn as_raw_mut_TextDetectorCNN(&mut self) -> *mut c_void

fn detect( &mut self, input_image: &impl ToInputArray, bbox: &mut Vector<Rect>, confidence: &mut Vector<f32> ) -> Result<()>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

impl TextDetectorCNNTraitConst for Ptr<TextDetectorCNN>

fn as_raw_TextDetectorCNN(&self) -> *const c_void

impl TextDetectorTrait for Ptr<TextDetector>

fn as_raw_mut_TextDetector(&mut self) -> *mut c_void

fn detect( &mut self, input_image: &impl ToInputArray, bbox: &mut Vector<Rect>, confidence: &mut Vector<f32> ) -> Result<()>

Method that provides a quick and simple interface to detect text inside an image

impl TextDetectorTrait for Ptr<TextDetectorCNN>

fn as_raw_mut_TextDetector(&mut self) -> *mut c_void

fn detect( &mut self, input_image: &impl ToInputArray, bbox: &mut Vector<Rect>, confidence: &mut Vector<f32> ) -> Result<()>

Method that provides a quick and simple interface to detect text inside an image

impl TextDetectorTraitConst for Ptr<TextDetector>

fn as_raw_TextDetector(&self) -> *const c_void

impl TextDetectorTraitConst for Ptr<TextDetectorCNN>

fn as_raw_TextDetector(&self) -> *const c_void

impl ThinPlateSplineShapeTransformerTrait for Ptr<ThinPlateSplineShapeTransformer>

fn as_raw_mut_ThinPlateSplineShapeTransformer(&mut self) -> *mut c_void

fn set_regularization_parameter(&mut self, beta: f64) -> Result<()>

Set the regularization parameter for relaxing the exact interpolation requirements of the TPS algorithm.

impl ThinPlateSplineShapeTransformerTraitConst for Ptr<ThinPlateSplineShapeTransformer>

fn as_raw_ThinPlateSplineShapeTransformer(&self) -> *const c_void

fn get_regularization_parameter(&self) -> Result<f64>

impl ThresholdedReluLayerTrait for Ptr<ThresholdedReluLayer>

fn as_raw_mut_ThresholdedReluLayer(&mut self) -> *mut c_void

fn set_alpha(&mut self, val: f32)

impl ThresholdedReluLayerTraitConst for Ptr<ThresholdedReluLayer>

fn as_raw_ThresholdedReluLayer(&self) -> *const c_void

fn alpha(&self) -> f32

impl TileLayerTrait for Ptr<TileLayer>

fn as_raw_mut_TileLayer(&mut self) -> *mut c_void

impl TileLayerTraitConst for Ptr<TileLayer>

fn as_raw_TileLayer(&self) -> *const c_void

impl ToFileMotionWriterTrait for Ptr<ToFileMotionWriter>

fn as_raw_mut_ToFileMotionWriter(&mut self) -> *mut c_void

fn set_motion_model(&mut self, val: MotionModel) -> Result<()>

fn set_frame_mask(&mut self, mask: &impl ToInputArray) -> Result<()>

fn estimate( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst, ok: &mut bool ) -> Result<Mat>

C++ default parameters

fn estimate_def( &mut self, frame0: &impl MatTraitConst, frame1: &impl MatTraitConst ) -> Result<Mat>

Note

impl ToFileMotionWriterTraitConst for Ptr<ToFileMotionWriter>

fn as_raw_ToFileMotionWriter(&self) -> *const c_void

fn motion_model(&self) -> Result<MotionModel>

impl TonemapDragoTrait for Ptr<TonemapDrago>

fn as_raw_mut_TonemapDrago(&mut self) -> *mut c_void

fn set_saturation(&mut self, saturation: f32) -> Result<()>

fn set_bias(&mut self, bias: f32) -> Result<()>

impl TonemapDragoTraitConst for Ptr<TonemapDrago>

fn as_raw_TonemapDrago(&self) -> *const c_void

fn get_saturation(&self) -> Result<f32>

fn get_bias(&self) -> Result<f32>

impl TonemapDurandTrait for Ptr<TonemapDurand>

fn as_raw_mut_TonemapDurand(&mut self) -> *mut c_void

fn set_saturation(&mut self, saturation: f32) -> Result<()>

fn set_contrast(&mut self, contrast: f32) -> Result<()>

fn set_sigma_space(&mut self, sigma_space: f32) -> Result<()>

fn set_sigma_color(&mut self, sigma_color: f32) -> Result<()>

impl TonemapDurandTraitConst for Ptr<TonemapDurand>

fn as_raw_TonemapDurand(&self) -> *const c_void

fn get_saturation(&self) -> Result<f32>

fn get_contrast(&self) -> Result<f32>

fn get_sigma_space(&self) -> Result<f32>

fn get_sigma_color(&self) -> Result<f32>

impl TonemapMantiukTrait for Ptr<TonemapMantiuk>

fn as_raw_mut_TonemapMantiuk(&mut self) -> *mut c_void

fn set_scale(&mut self, scale: f32) -> Result<()>

fn set_saturation(&mut self, saturation: f32) -> Result<()>

impl TonemapMantiukTraitConst for Ptr<TonemapMantiuk>

fn as_raw_TonemapMantiuk(&self) -> *const c_void

fn get_scale(&self) -> Result<f32>

fn get_saturation(&self) -> Result<f32>

impl TonemapReinhardTrait for Ptr<TonemapReinhard>

fn as_raw_mut_TonemapReinhard(&mut self) -> *mut c_void

fn set_intensity(&mut self, intensity: f32) -> Result<()>

fn set_light_adaptation(&mut self, light_adapt: f32) -> Result<()>

fn set_color_adaptation(&mut self, color_adapt: f32) -> Result<()>

impl TonemapReinhardTraitConst for Ptr<TonemapReinhard>

fn as_raw_TonemapReinhard(&self) -> *const c_void

fn get_intensity(&self) -> Result<f32>

fn get_light_adaptation(&self) -> Result<f32>

fn get_color_adaptation(&self) -> Result<f32>

impl TonemapTrait for Ptr<Tonemap>

fn as_raw_mut_Tonemap(&mut self) -> *mut c_void

fn process( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Tonemaps image

fn set_gamma(&mut self, gamma: f32) -> Result<()>

impl TonemapTrait for Ptr<TonemapDrago>

fn as_raw_mut_Tonemap(&mut self) -> *mut c_void

fn process( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Tonemaps image

fn set_gamma(&mut self, gamma: f32) -> Result<()>

impl TonemapTrait for Ptr<TonemapDurand>

fn as_raw_mut_Tonemap(&mut self) -> *mut c_void

fn process( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Tonemaps image

fn set_gamma(&mut self, gamma: f32) -> Result<()>

impl TonemapTrait for Ptr<TonemapMantiuk>

fn as_raw_mut_Tonemap(&mut self) -> *mut c_void

fn process( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Tonemaps image

fn set_gamma(&mut self, gamma: f32) -> Result<()>

impl TonemapTrait for Ptr<TonemapReinhard>

fn as_raw_mut_Tonemap(&mut self) -> *mut c_void

fn process( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Tonemaps image

fn set_gamma(&mut self, gamma: f32) -> Result<()>

impl TonemapTraitConst for Ptr<Tonemap>

fn as_raw_Tonemap(&self) -> *const c_void

fn get_gamma(&self) -> Result<f32>

impl TonemapTraitConst for Ptr<TonemapDrago>

fn as_raw_Tonemap(&self) -> *const c_void

fn get_gamma(&self) -> Result<f32>

impl TonemapTraitConst for Ptr<TonemapDurand>

fn as_raw_Tonemap(&self) -> *const c_void

fn get_gamma(&self) -> Result<f32>

impl TonemapTraitConst for Ptr<TonemapMantiuk>

fn as_raw_Tonemap(&self) -> *const c_void

fn get_gamma(&self) -> Result<f32>

impl TonemapTraitConst for Ptr<TonemapReinhard>

fn as_raw_Tonemap(&self) -> *const c_void

fn get_gamma(&self) -> Result<f32>

impl TrackerCSRTTrait for Ptr<TrackerCSRT>

fn as_raw_mut_TrackerCSRT(&mut self) -> *mut c_void

fn set_initial_mask(&mut self, mask: &impl ToInputArray) -> Result<()>

impl TrackerCSRTTraitConst for Ptr<TrackerCSRT>

fn as_raw_TrackerCSRT(&self) -> *const c_void

impl TrackerDaSiamRPNTrait for Ptr<TrackerDaSiamRPN>

fn as_raw_mut_TrackerDaSiamRPN(&mut self) -> *mut c_void

fn get_tracking_score(&mut self) -> Result<f32>

Return tracking score

impl TrackerDaSiamRPNTraitConst for Ptr<TrackerDaSiamRPN>

fn as_raw_TrackerDaSiamRPN(&self) -> *const c_void

impl TrackerGOTURNTrait for Ptr<TrackerGOTURN>

fn as_raw_mut_TrackerGOTURN(&mut self) -> *mut c_void

impl TrackerGOTURNTraitConst for Ptr<TrackerGOTURN>

fn as_raw_TrackerGOTURN(&self) -> *const c_void

impl TrackerKCFTrait for Ptr<TrackerKCF>

fn as_raw_mut_TrackerKCF(&mut self) -> *mut c_void

fn set_feature_extractor( &mut self, callback: TrackerKCF_FeatureExtractorCallbackFN, pca_func: bool ) -> Result<()>

C++ default parameters

fn set_feature_extractor_def( &mut self, callback: TrackerKCF_FeatureExtractorCallbackFN ) -> Result<()>

Note

impl TrackerKCFTraitConst for Ptr<TrackerKCF>

fn as_raw_TrackerKCF(&self) -> *const c_void

impl TrackerMILTrait for Ptr<TrackerMIL>

fn as_raw_mut_TrackerMIL(&mut self) -> *mut c_void

impl TrackerMILTraitConst for Ptr<TrackerMIL>

fn as_raw_TrackerMIL(&self) -> *const c_void

impl TrackerNanoTrait for Ptr<TrackerNano>

fn as_raw_mut_TrackerNano(&mut self) -> *mut c_void

fn get_tracking_score(&mut self) -> Result<f32>

Return tracking score

impl TrackerNanoTraitConst for Ptr<TrackerNano>

fn as_raw_TrackerNano(&self) -> *const c_void

impl TrackerTrait for Ptr<Tracker>

fn as_raw_mut_Tracker(&mut self) -> *mut c_void

fn init(&mut self, image: &impl ToInputArray, bounding_box: Rect) -> Result<()>

Initialize the tracker with a known bounding box that surrounded the target

fn update( &mut self, image: &impl ToInputArray, bounding_box: &mut Rect ) -> Result<bool>

Update the tracker, find the new most likely bounding box for the target

impl TrackerTrait for Ptr<TrackerCSRT>

fn as_raw_mut_Tracker(&mut self) -> *mut c_void

fn init(&mut self, image: &impl ToInputArray, bounding_box: Rect) -> Result<()>

Initialize the tracker with a known bounding box that surrounded the target

fn update( &mut self, image: &impl ToInputArray, bounding_box: &mut Rect ) -> Result<bool>

Update the tracker, find the new most likely bounding box for the target

impl TrackerTrait for Ptr<TrackerDaSiamRPN>

fn as_raw_mut_Tracker(&mut self) -> *mut c_void

fn init(&mut self, image: &impl ToInputArray, bounding_box: Rect) -> Result<()>

Initialize the tracker with a known bounding box that surrounded the target

fn update( &mut self, image: &impl ToInputArray, bounding_box: &mut Rect ) -> Result<bool>

Update the tracker, find the new most likely bounding box for the target

impl TrackerTrait for Ptr<TrackerGOTURN>

fn as_raw_mut_Tracker(&mut self) -> *mut c_void

fn init(&mut self, image: &impl ToInputArray, bounding_box: Rect) -> Result<()>

Initialize the tracker with a known bounding box that surrounded the target

fn update( &mut self, image: &impl ToInputArray, bounding_box: &mut Rect ) -> Result<bool>

Update the tracker, find the new most likely bounding box for the target

impl TrackerTrait for Ptr<TrackerKCF>

fn as_raw_mut_Tracker(&mut self) -> *mut c_void

fn init(&mut self, image: &impl ToInputArray, bounding_box: Rect) -> Result<()>

Initialize the tracker with a known bounding box that surrounded the target

fn update( &mut self, image: &impl ToInputArray, bounding_box: &mut Rect ) -> Result<bool>

Update the tracker, find the new most likely bounding box for the target

impl TrackerTrait for Ptr<TrackerMIL>

fn as_raw_mut_Tracker(&mut self) -> *mut c_void

fn init(&mut self, image: &impl ToInputArray, bounding_box: Rect) -> Result<()>

Initialize the tracker with a known bounding box that surrounded the target

fn update( &mut self, image: &impl ToInputArray, bounding_box: &mut Rect ) -> Result<bool>

Update the tracker, find the new most likely bounding box for the target

impl TrackerTrait for Ptr<TrackerNano>

fn as_raw_mut_Tracker(&mut self) -> *mut c_void

fn init(&mut self, image: &impl ToInputArray, bounding_box: Rect) -> Result<()>

Initialize the tracker with a known bounding box that surrounded the target

fn update( &mut self, image: &impl ToInputArray, bounding_box: &mut Rect ) -> Result<bool>

Update the tracker, find the new most likely bounding box for the target

impl TrackerTrait for Ptr<TrackerVit>

fn as_raw_mut_Tracker(&mut self) -> *mut c_void

fn init(&mut self, image: &impl ToInputArray, bounding_box: Rect) -> Result<()>

Initialize the tracker with a known bounding box that surrounded the target

fn update( &mut self, image: &impl ToInputArray, bounding_box: &mut Rect ) -> Result<bool>

Update the tracker, find the new most likely bounding box for the target

impl TrackerTraitConst for Ptr<Tracker>

fn as_raw_Tracker(&self) -> *const c_void

impl TrackerTraitConst for Ptr<TrackerCSRT>

fn as_raw_Tracker(&self) -> *const c_void

impl TrackerTraitConst for Ptr<TrackerDaSiamRPN>

fn as_raw_Tracker(&self) -> *const c_void

impl TrackerTraitConst for Ptr<TrackerGOTURN>

fn as_raw_Tracker(&self) -> *const c_void

impl TrackerTraitConst for Ptr<TrackerKCF>

fn as_raw_Tracker(&self) -> *const c_void

impl TrackerTraitConst for Ptr<TrackerMIL>

fn as_raw_Tracker(&self) -> *const c_void

impl TrackerTraitConst for Ptr<TrackerNano>

fn as_raw_Tracker(&self) -> *const c_void

impl TrackerTraitConst for Ptr<TrackerVit>

fn as_raw_Tracker(&self) -> *const c_void

impl TrackerVitTrait for Ptr<TrackerVit>

fn as_raw_mut_TrackerVit(&mut self) -> *mut c_void

fn get_tracking_score(&mut self) -> Result<f32>

Return tracking score

impl TrackerVitTraitConst for Ptr<TrackerVit>

fn as_raw_TrackerVit(&self) -> *const c_void

impl TrainDataTrait for Ptr<TrainData>

fn as_raw_mut_TrainData(&mut self) -> *mut c_void

fn set_train_test_split(&mut self, count: i32, shuffle: bool) -> Result<()>

Splits the training data into the training and test parts

fn set_train_test_split_def(&mut self, count: i32) -> Result<()>

Splits the training data into the training and test parts

fn set_train_test_split_ratio( &mut self, ratio: f64, shuffle: bool ) -> Result<()>

Splits the training data into the training and test parts

fn set_train_test_split_ratio_def(&mut self, ratio: f64) -> Result<()>

Splits the training data into the training and test parts

fn shuffle_train_test(&mut self) -> Result<()>

impl TrainDataTraitConst for Ptr<TrainData>

fn as_raw_TrainData(&self) -> *const c_void

fn get_layout(&self) -> Result<i32>

fn get_n_train_samples(&self) -> Result<i32>

fn get_n_test_samples(&self) -> Result<i32>

fn get_n_samples(&self) -> Result<i32>

fn get_n_vars(&self) -> Result<i32>

fn get_n_all_vars(&self) -> Result<i32>

fn get_sample( &self, var_idx: &impl ToInputArray, sidx: i32, buf: &mut f32 ) -> Result<()>

fn get_samples(&self) -> Result<Mat>

fn get_missing(&self) -> Result<Mat>

fn get_train_samples( &self, layout: i32, compress_samples: bool, compress_vars: bool ) -> Result<Mat>

Returns matrix of train samples

fn get_train_samples_def(&self) -> Result<Mat>

Returns matrix of train samples

fn get_train_responses(&self) -> Result<Mat>

Returns the vector of responses

fn get_train_norm_cat_responses(&self) -> Result<Mat>

Returns the vector of normalized categorical responses

fn get_test_responses(&self) -> Result<Mat>

fn get_test_norm_cat_responses(&self) -> Result<Mat>

fn get_responses(&self) -> Result<Mat>

fn get_norm_cat_responses(&self) -> Result<Mat>

fn get_sample_weights(&self) -> Result<Mat>

fn get_train_sample_weights(&self) -> Result<Mat>

fn get_test_sample_weights(&self) -> Result<Mat>

fn get_var_idx(&self) -> Result<Mat>

fn get_var_type(&self) -> Result<Mat>

fn get_var_symbol_flags(&self) -> Result<Mat>

fn get_response_type(&self) -> Result<i32>

fn get_train_sample_idx(&self) -> Result<Mat>

fn get_test_sample_idx(&self) -> Result<Mat>

fn get_values( &self, vi: i32, sidx: &impl ToInputArray, values: &mut f32 ) -> Result<()>

fn get_norm_cat_values( &self, vi: i32, sidx: &impl ToInputArray, values: &mut i32 ) -> Result<()>

fn get_default_subst_values(&self) -> Result<Mat>

fn get_cat_count(&self, vi: i32) -> Result<i32>

fn get_class_labels(&self) -> Result<Mat>

Returns the vector of class labels

fn get_cat_ofs(&self) -> Result<Mat>

fn get_cat_map(&self) -> Result<Mat>

fn get_test_samples(&self) -> Result<Mat>

Returns matrix of test samples

fn get_names(&self, names: &mut Vector<String>) -> Result<()>

Returns vector of symbolic names captured in loadFromCSV()

impl TransientAreasSegmentationModuleTrait for Ptr<TransientAreasSegmentationModule>

fn as_raw_mut_TransientAreasSegmentationModule(&mut self) -> *mut c_void

fn get_size(&mut self) -> Result<Size>

return the sze of the manage input and output images

fn setup_from_file( &mut self, segmentation_parameter_file: &str, apply_default_setup_on_failure: bool ) -> Result<()>

try to open an XML segmentation parameters file to adjust current segmentation instance setup

fn setup_from_file_def(&mut self) -> Result<()>

try to open an XML segmentation parameters file to adjust current segmentation instance setup

fn setup_from_storage( &mut self, fs: &mut impl FileStorageTrait, apply_default_setup_on_failure: bool ) -> Result<()>

try to open an XML segmentation parameters file to adjust current segmentation instance setup

fn setup_from_storage_def( &mut self, fs: &mut impl FileStorageTrait ) -> Result<()>

try to open an XML segmentation parameters file to adjust current segmentation instance setup

fn setup(&mut self, new_parameters: SegmentationParameters) -> Result<()>

try to open an XML segmentation parameters file to adjust current segmentation instance setup

fn get_parameters(&mut self) -> Result<SegmentationParameters>

return the current parameters setup

fn print_setup(&mut self) -> Result<String>

parameters setup display method

fn run( &mut self, input_to_segment: &impl ToInputArray, channel_index: i32 ) -> Result<()>

main processing method, get result using methods getSegmentationPicture()

fn run_def(&mut self, input_to_segment: &impl ToInputArray) -> Result<()>

main processing method, get result using methods getSegmentationPicture()

fn get_segmentation_picture( &mut self, transient_areas: &mut impl ToOutputArray ) -> Result<()>

access function return the last segmentation result: a boolean picture which is resampled between 0 and 255 for a display purpose

fn clear_all_buffers(&mut self) -> Result<()>

cleans all the buffers of the instance

impl TransientAreasSegmentationModuleTraitConst for Ptr<TransientAreasSegmentationModule>

fn as_raw_TransientAreasSegmentationModule(&self) -> *const c_void

fn write(&self, fs: &str) -> Result<()>

write xml/yml formated parameters information

fn write_to_storage(&self, fs: &mut impl FileStorageTrait) -> Result<()>

write xml/yml formated parameters information

impl TranslationBasedLocalOutlierRejectorTrait for Ptr<TranslationBasedLocalOutlierRejector>

fn as_raw_mut_TranslationBasedLocalOutlierRejector(&mut self) -> *mut c_void

fn set_cell_size(&mut self, val: Size) -> Result<()>

fn set_ransac_params(&mut self, val: impl RansacParamsTrait) -> Result<()>

fn process( &mut self, frame_size: Size, points0: &impl ToInputArray, points1: &impl ToInputArray, mask: &mut impl ToOutputArray ) -> Result<()>

impl TranslationBasedLocalOutlierRejectorTraitConst for Ptr<TranslationBasedLocalOutlierRejector>

fn as_raw_TranslationBasedLocalOutlierRejector(&self) -> *const c_void

fn cell_size(&self) -> Result<Size>

fn ransac_params(&self) -> Result<RansacParams>

impl TransverseMercatorWarperTrait for Ptr<TransverseMercatorWarper>

fn as_raw_mut_TransverseMercatorWarper(&mut self) -> *mut c_void

impl TransverseMercatorWarperTraitConst for Ptr<TransverseMercatorWarper>

fn as_raw_TransverseMercatorWarper(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl TwoPassStabilizerTrait for Ptr<TwoPassStabilizer>

fn as_raw_mut_TwoPassStabilizer(&mut self) -> *mut c_void

fn set_motion_stabilizer(&mut self, val: Ptr<IMotionStabilizer>) -> Result<()>

fn set_wobble_suppressor( &mut self, val: Ptr<WobbleSuppressorBase> ) -> Result<()>

fn set_estimate_trim_ratio(&mut self, val: bool) -> Result<()>

fn reset(&mut self) -> Result<()>

fn next_frame(&mut self) -> Result<Mat>

impl TwoPassStabilizerTraitConst for Ptr<TwoPassStabilizer>

fn as_raw_TwoPassStabilizer(&self) -> *const c_void

fn motion_stabilizer(&self) -> Result<Ptr<IMotionStabilizer>>

fn wobble_suppressor(&self) -> Result<Ptr<WobbleSuppressorBase>>

fn must_estimate_trima_ratio(&self) -> Result<bool>

impl VGGTrait for Ptr<VGG>

fn as_raw_mut_VGG(&mut self) -> *mut c_void

fn set_sigma(&mut self, isigma: f32) -> Result<()>

fn set_use_normalize_image(&mut self, img_normalize: bool) -> Result<()>

fn set_use_scale_orientation( &mut self, use_scale_orientation: bool ) -> Result<()>

fn set_scale_factor(&mut self, scale_factor: f32) -> Result<()>

fn set_use_normalize_descriptor(&mut self, dsc_normalize: bool) -> Result<()>

impl VGGTraitConst for Ptr<VGG>

fn as_raw_VGG(&self) -> *const c_void

fn get_default_name(&self) -> Result<String>

fn get_sigma(&self) -> Result<f32>

fn get_use_normalize_image(&self) -> Result<bool>

fn get_use_scale_orientation(&self) -> Result<bool>

fn get_scale_factor(&self) -> Result<f32>

fn get_use_normalize_descriptor(&self) -> Result<bool>

impl VariationalRefinementTrait for Ptr<VariationalRefinement>

fn as_raw_mut_VariationalRefinement(&mut self) -> *mut c_void

fn calc_uv( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow_u: &mut impl ToInputOutputArray, flow_v: &mut impl ToInputOutputArray ) -> Result<()>

[calc] function overload to handle separate horizontal (u) and vertical (v) flow components (to avoid extra splits/merges)

fn set_fixed_point_iterations(&mut self, val: i32) -> Result<()>

Number of outer (fixed-point) iterations in the minimization procedure.

fn set_sor_iterations(&mut self, val: i32) -> Result<()>

Number of inner successive over-relaxation (SOR) iterations in the minimization procedure to solve the respective linear system.

fn set_omega(&mut self, val: f32) -> Result<()>

Relaxation factor in SOR

fn set_alpha(&mut self, val: f32) -> Result<()>

Weight of the smoothness term

fn set_delta(&mut self, val: f32) -> Result<()>

Weight of the color constancy term

fn set_gamma(&mut self, val: f32) -> Result<()>

Weight of the gradient constancy term

impl VariationalRefinementTraitConst for Ptr<VariationalRefinement>

fn as_raw_VariationalRefinement(&self) -> *const c_void

fn get_fixed_point_iterations(&self) -> Result<i32>

Number of outer (fixed-point) iterations in the minimization procedure.

fn get_sor_iterations(&self) -> Result<i32>

Number of inner successive over-relaxation (SOR) iterations in the minimization procedure to solve the respective linear system.

fn get_omega(&self) -> Result<f32>

Relaxation factor in SOR

fn get_alpha(&self) -> Result<f32>

Weight of the smoothness term

fn get_delta(&self) -> Result<f32>

Weight of the color constancy term

fn get_gamma(&self) -> Result<f32>

Weight of the gradient constancy term

impl VideoFileSourceTrait for Ptr<VideoFileSource>

fn as_raw_mut_VideoFileSource(&mut self) -> *mut c_void

fn reset(&mut self) -> Result<()>

fn next_frame(&mut self) -> Result<Mat>

fn width(&mut self) -> Result<i32>

fn height(&mut self) -> Result<i32>

fn count(&mut self) -> Result<i32>

fn fps(&mut self) -> Result<f64>

impl VideoFileSourceTraitConst for Ptr<VideoFileSource>

fn as_raw_VideoFileSource(&self) -> *const c_void

impl WBDetectorTrait for Ptr<WBDetector>

fn as_raw_mut_WBDetector(&mut self) -> *mut c_void

fn read(&mut self, node: &impl FileNodeTraitConst) -> Result<()>

Read detector from FileNode.

fn train(&mut self, pos_samples: &str, neg_imgs: &str) -> Result<()>

Train WaldBoost detector

fn detect( &mut self, img: &impl MatTraitConst, bboxes: &mut Vector<Rect>, confidences: &mut Vector<f64> ) -> Result<()>

Detect objects on image using WaldBoost detector

impl WBDetectorTraitConst for Ptr<WBDetector>

fn as_raw_WBDetector(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Write detector to FileStorage.

impl WarperCreatorTrait for Ptr<AffineWarper>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTrait for Ptr<CompressedRectilinearPortraitWarper>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTrait for Ptr<CompressedRectilinearWarper>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTrait for Ptr<CylindricalWarper>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTrait for Ptr<CylindricalWarperGpu>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTrait for Ptr<FisheyeWarper>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTrait for Ptr<MercatorWarper>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTrait for Ptr<PaniniPortraitWarper>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTrait for Ptr<PaniniWarper>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTrait for Ptr<PlaneWarper>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTrait for Ptr<PlaneWarperGpu>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTrait for Ptr<SphericalWarper>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTrait for Ptr<SphericalWarperGpu>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTrait for Ptr<StereographicWarper>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTrait for Ptr<TransverseMercatorWarper>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTrait for Ptr<WarperCreator>

fn as_raw_mut_WarperCreator(&mut self) -> *mut c_void

impl WarperCreatorTraitConst for Ptr<AffineWarper>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WarperCreatorTraitConst for Ptr<CompressedRectilinearPortraitWarper>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WarperCreatorTraitConst for Ptr<CompressedRectilinearWarper>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WarperCreatorTraitConst for Ptr<CylindricalWarper>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WarperCreatorTraitConst for Ptr<CylindricalWarperGpu>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WarperCreatorTraitConst for Ptr<FisheyeWarper>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WarperCreatorTraitConst for Ptr<MercatorWarper>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WarperCreatorTraitConst for Ptr<PaniniPortraitWarper>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WarperCreatorTraitConst for Ptr<PaniniWarper>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WarperCreatorTraitConst for Ptr<PlaneWarper>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WarperCreatorTraitConst for Ptr<PlaneWarperGpu>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WarperCreatorTraitConst for Ptr<SphericalWarper>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WarperCreatorTraitConst for Ptr<SphericalWarperGpu>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WarperCreatorTraitConst for Ptr<StereographicWarper>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WarperCreatorTraitConst for Ptr<TransverseMercatorWarper>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WarperCreatorTraitConst for Ptr<WarperCreator>

fn as_raw_WarperCreator(&self) -> *const c_void

fn create(&self, scale: f32) -> Result<Ptr<Detail_RotationWarper>>

impl WeightingDeblurerTrait for Ptr<WeightingDeblurer>

fn as_raw_mut_WeightingDeblurer(&mut self) -> *mut c_void

fn set_sensitivity(&mut self, val: f32) -> Result<()>

fn deblur( &mut self, idx: i32, frame: &mut impl MatTrait, range: &impl RangeTraitConst ) -> Result<()>

impl WeightingDeblurerTraitConst for Ptr<WeightingDeblurer>

fn as_raw_WeightingDeblurer(&self) -> *const c_void

fn sensitivity(&self) -> Result<f32>

impl WhiteBalancerTrait for Ptr<GrayworldWB>

fn as_raw_mut_WhiteBalancer(&mut self) -> *mut c_void

fn balance_white( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Applies white balancing to the input image

impl WhiteBalancerTrait for Ptr<LearningBasedWB>

fn as_raw_mut_WhiteBalancer(&mut self) -> *mut c_void

fn balance_white( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Applies white balancing to the input image

impl WhiteBalancerTrait for Ptr<SimpleWB>

fn as_raw_mut_WhiteBalancer(&mut self) -> *mut c_void

fn balance_white( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Applies white balancing to the input image

impl WhiteBalancerTrait for Ptr<WhiteBalancer>

fn as_raw_mut_WhiteBalancer(&mut self) -> *mut c_void

fn balance_white( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray ) -> Result<()>

Applies white balancing to the input image

impl WhiteBalancerTraitConst for Ptr<GrayworldWB>

fn as_raw_WhiteBalancer(&self) -> *const c_void

impl WhiteBalancerTraitConst for Ptr<LearningBasedWB>

fn as_raw_WhiteBalancer(&self) -> *const c_void

impl WhiteBalancerTraitConst for Ptr<SimpleWB>

fn as_raw_WhiteBalancer(&self) -> *const c_void

impl WhiteBalancerTraitConst for Ptr<WhiteBalancer>

fn as_raw_WhiteBalancer(&self) -> *const c_void

impl WindowSceneTrait for Ptr<WindowScene>

fn as_raw_mut_WindowScene(&mut self) -> *mut c_void

fn set_background(&mut self, image: &impl ToInputArray) -> Result<()>

set window background to custom image/ color

fn set_background_color(&mut self, color: Scalar) -> Result<()>

set window background to custom image/ color

fn set_compositors(&mut self, names: &Vector<String>) -> Result<()>

enable an ordered chain of full-screen post processing effects

fn create_entity( &mut self, name: &str, meshname: &str, tvec: &impl ToInputArray, rot: &impl ToInputArray ) -> Result<()>

place an entity of a mesh in the scene

fn create_entity_def(&mut self, name: &str, meshname: &str) -> Result<()>

place an entity of a mesh in the scene

fn remove_entity(&mut self, name: &str) -> Result<()>

remove an entity from the scene

fn set_entity_property( &mut self, name: &str, prop: i32, value: &str, sub_entity_idx: i32 ) -> Result<()>

set the property of an entity to the given value

fn set_entity_property_def( &mut self, name: &str, prop: i32, value: &str ) -> Result<()>

set the property of an entity to the given value

fn set_entity_property_1( &mut self, name: &str, prop: i32, value: Scalar ) -> Result<()>

set the property of an entity to the given value

fn get_entity_property( &mut self, name: &str, prop: i32, value: &mut impl ToOutputArray ) -> Result<()>

get the property of an entity

fn create_camera_entity( &mut self, name: &str, k: &impl ToInputArray, imsize: Size, z_far: f32, tvec: &impl ToInputArray, rot: &impl ToInputArray, color: Scalar ) -> Result<Rect2d>

convenience method to visualize a camera position

fn create_camera_entity_def( &mut self, name: &str, k: &impl ToInputArray, imsize: Size, z_far: f32 ) -> Result<Rect2d>

convenience method to visualize a camera position

fn create_light_entity( &mut self, name: &str, tvec: &impl ToInputArray, rot: &impl ToInputArray, diffuse_color: Scalar, specular_color: Scalar ) -> Result<()>

creates a point light in the scene

fn create_light_entity_def(&mut self, name: &str) -> Result<()>

creates a point light in the scene

fn update_entity_pose( &mut self, name: &str, tvec: &impl ToInputArray, rot: &impl ToInputArray ) -> Result<()>

update entity pose by transformation in the parent coordinate space. (pre-rotation)

fn update_entity_pose_def(&mut self, name: &str) -> Result<()>

update entity pose by transformation in the parent coordinate space. (pre-rotation)

fn set_entity_pose( &mut self, name: &str, tvec: &impl ToInputArray, rot: &impl ToInputArray, invert: bool ) -> Result<()>

set entity pose in the world coordinate space.

fn set_entity_pose_def(&mut self, name: &str) -> Result<()>

set entity pose in the world coordinate space.

fn get_entity_pose( &mut self, name: &str, r: &mut impl ToOutputArray, tvec: &mut impl ToOutputArray, invert: bool ) -> Result<()>

Retrieves the current pose of an entity

fn get_entity_pose_def(&mut self, name: &str) -> Result<()>

Retrieves the current pose of an entity

fn get_entity_animations( &mut self, name: &str, out: &mut Vector<String> ) -> Result<()>

get a list of available entity animations

fn play_entity_animation( &mut self, name: &str, animname: &str, loop_: bool ) -> Result<()>

play entity animation

fn play_entity_animation_def( &mut self, name: &str, animname: &str ) -> Result<()>

play entity animation

fn stop_entity_animation(&mut self, name: &str, animname: &str) -> Result<()>

stop entity animation

fn get_screenshot(&mut self, frame: &mut impl ToOutputArray) -> Result<()>

read back the image generated by the last call to [waitKey]

fn get_compositor_texture( &mut self, compname: &str, texname: &str, out: &mut impl ToOutputArray, mrt_index: i32 ) -> Result<()>

read back the texture of an active compositor

fn get_compositor_texture_def( &mut self, compname: &str, texname: &str, out: &mut impl ToOutputArray ) -> Result<()>

read back the texture of an active compositor

fn get_depth(&mut self, depth: &mut impl ToOutputArray) -> Result<()>

get the depth for the current frame.

fn fix_camera_yaw_axis( &mut self, use_fixed: bool, up: &impl ToInputArray ) -> Result<()>

convenience method to force the “up” axis to stay fixed

fn fix_camera_yaw_axis_def(&mut self, use_fixed: bool) -> Result<()>

convenience method to force the “up” axis to stay fixed

fn set_camera_pose( &mut self, tvec: &impl ToInputArray, rot: &impl ToInputArray, invert: bool ) -> Result<()>

Sets the current camera pose

fn set_camera_pose_def(&mut self) -> Result<()>

Sets the current camera pose

fn set_camera_look_at( &mut self, target: &str, offset: &impl ToInputArray ) -> Result<()>

convenience method to orient the camera to a specific entity

fn set_camera_look_at_def(&mut self, target: &str) -> Result<()>

convenience method to orient the camera to a specific entity

fn set_entity_look_at( &mut self, origin: &str, target: &str, offset: &impl ToInputArray ) -> Result<()>

convenience method to orient an entity to a specific entity. If target is an empty string the entity looks at the given offset point

fn set_entity_look_at_def(&mut self, origin: &str, target: &str) -> Result<()>

convenience method to orient an entity to a specific entity. If target is an empty string the entity looks at the given offset point

fn get_camera_pose( &mut self, r: &mut impl ToOutputArray, tvec: &mut impl ToOutputArray, invert: bool ) -> Result<()>

Retrieves the current camera pose

fn get_camera_pose_def(&mut self) -> Result<()>

Retrieves the current camera pose

fn set_camera_intrinsics( &mut self, k: &impl ToInputArray, imsize: Size, z_near: f32, z_far: f32 ) -> Result<()>

set intrinsics of the camera

fn set_camera_intrinsics_def( &mut self, k: &impl ToInputArray, imsize: Size ) -> Result<()>

set intrinsics of the camera

fn update(&mut self) -> Result<()>

render this window, but do not swap buffers. Automatically called by [ovis::waitKey]

impl WindowSceneTraitConst for Ptr<WindowScene>

fn as_raw_WindowScene(&self) -> *const c_void

impl WobbleSuppressorBaseTrait for Ptr<MoreAccurateMotionWobbleSuppressor>

fn as_raw_mut_WobbleSuppressorBase(&mut self) -> *mut c_void

fn set_motion_estimator( &mut self, val: Ptr<ImageMotionEstimatorBase> ) -> Result<()>

fn suppress( &mut self, idx: i32, frame: &impl MatTraitConst, result: &mut impl MatTrait ) -> Result<()>

fn set_frame_count(&mut self, val: i32) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions2(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilization_motions(&mut self, val: &Vector<Mat>) -> Result<()>

impl WobbleSuppressorBaseTrait for Ptr<MoreAccurateMotionWobbleSuppressorBase>

fn as_raw_mut_WobbleSuppressorBase(&mut self) -> *mut c_void

fn set_motion_estimator( &mut self, val: Ptr<ImageMotionEstimatorBase> ) -> Result<()>

fn suppress( &mut self, idx: i32, frame: &impl MatTraitConst, result: &mut impl MatTrait ) -> Result<()>

fn set_frame_count(&mut self, val: i32) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions2(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilization_motions(&mut self, val: &Vector<Mat>) -> Result<()>

impl WobbleSuppressorBaseTrait for Ptr<MoreAccurateMotionWobbleSuppressorGpu>

fn as_raw_mut_WobbleSuppressorBase(&mut self) -> *mut c_void

fn set_motion_estimator( &mut self, val: Ptr<ImageMotionEstimatorBase> ) -> Result<()>

fn suppress( &mut self, idx: i32, frame: &impl MatTraitConst, result: &mut impl MatTrait ) -> Result<()>

fn set_frame_count(&mut self, val: i32) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions2(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilization_motions(&mut self, val: &Vector<Mat>) -> Result<()>

impl WobbleSuppressorBaseTrait for Ptr<NullWobbleSuppressor>

fn as_raw_mut_WobbleSuppressorBase(&mut self) -> *mut c_void

fn set_motion_estimator( &mut self, val: Ptr<ImageMotionEstimatorBase> ) -> Result<()>

fn suppress( &mut self, idx: i32, frame: &impl MatTraitConst, result: &mut impl MatTrait ) -> Result<()>

fn set_frame_count(&mut self, val: i32) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions2(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilization_motions(&mut self, val: &Vector<Mat>) -> Result<()>

impl WobbleSuppressorBaseTrait for Ptr<WobbleSuppressorBase>

fn as_raw_mut_WobbleSuppressorBase(&mut self) -> *mut c_void

fn set_motion_estimator( &mut self, val: Ptr<ImageMotionEstimatorBase> ) -> Result<()>

fn suppress( &mut self, idx: i32, frame: &impl MatTraitConst, result: &mut impl MatTrait ) -> Result<()>

fn set_frame_count(&mut self, val: i32) -> Result<()>

fn set_motions(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_motions2(&mut self, val: &Vector<Mat>) -> Result<()>

fn set_stabilization_motions(&mut self, val: &Vector<Mat>) -> Result<()>

impl WobbleSuppressorBaseTraitConst for Ptr<MoreAccurateMotionWobbleSuppressor>

fn as_raw_WobbleSuppressorBase(&self) -> *const c_void

fn motion_estimator(&self) -> Result<Ptr<ImageMotionEstimatorBase>>

fn frame_count(&self) -> Result<i32>

fn motions(&self) -> Result<Vector<Mat>>

fn motions2(&self) -> Result<Vector<Mat>>

fn stabilization_motions(&self) -> Result<Vector<Mat>>

impl WobbleSuppressorBaseTraitConst for Ptr<MoreAccurateMotionWobbleSuppressorBase>

fn as_raw_WobbleSuppressorBase(&self) -> *const c_void

fn motion_estimator(&self) -> Result<Ptr<ImageMotionEstimatorBase>>

fn frame_count(&self) -> Result<i32>

fn motions(&self) -> Result<Vector<Mat>>

fn motions2(&self) -> Result<Vector<Mat>>

fn stabilization_motions(&self) -> Result<Vector<Mat>>

impl WobbleSuppressorBaseTraitConst for Ptr<MoreAccurateMotionWobbleSuppressorGpu>

fn as_raw_WobbleSuppressorBase(&self) -> *const c_void

fn motion_estimator(&self) -> Result<Ptr<ImageMotionEstimatorBase>>

fn frame_count(&self) -> Result<i32>

fn motions(&self) -> Result<Vector<Mat>>

fn motions2(&self) -> Result<Vector<Mat>>

fn stabilization_motions(&self) -> Result<Vector<Mat>>

impl WobbleSuppressorBaseTraitConst for Ptr<NullWobbleSuppressor>

fn as_raw_WobbleSuppressorBase(&self) -> *const c_void

fn motion_estimator(&self) -> Result<Ptr<ImageMotionEstimatorBase>>

fn frame_count(&self) -> Result<i32>

fn motions(&self) -> Result<Vector<Mat>>

fn motions2(&self) -> Result<Vector<Mat>>

fn stabilization_motions(&self) -> Result<Vector<Mat>>

impl WobbleSuppressorBaseTraitConst for Ptr<WobbleSuppressorBase>

fn as_raw_WobbleSuppressorBase(&self) -> *const c_void

fn motion_estimator(&self) -> Result<Ptr<ImageMotionEstimatorBase>>

fn frame_count(&self) -> Result<i32>

fn motions(&self) -> Result<Vector<Mat>>

fn motions2(&self) -> Result<Vector<Mat>>

fn stabilization_motions(&self) -> Result<Vector<Mat>>