Struct opencv::dnn::ConvolutionLayerInt8

pub struct ConvolutionLayerInt8 { /* private fields */ }

Implementations

impl ConvolutionLayerInt8

pub fn create( params: &impl LayerParamsTraitConst ) -> Result<Ptr<BaseConvolutionLayer>>

Trait Implementations

impl AlgorithmTrait for 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 AlgorithmTraitConst for 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 BaseConvolutionLayerTrait for 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 BaseConvolutionLayerTraitConst for 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 Boxed for ConvolutionLayerInt8

unsafe fn from_raw( ptr: <ConvolutionLayerInt8 as OpenCVFromExtern>::ExternReceive ) -> Self

Wrap the specified raw pointer

fn into_raw( self ) -> <ConvolutionLayerInt8 as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying raw pointer while consuming this wrapper.

fn as_raw( &self ) -> <ConvolutionLayerInt8 as OpenCVTypeExternContainer>::ExternSend

Return the underlying raw pointer.

fn as_raw_mut( &mut self ) -> <ConvolutionLayerInt8 as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying mutable raw pointer

impl ConvolutionLayerInt8Trait for 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 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 Debug for ConvolutionLayerInt8

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for ConvolutionLayerInt8

fn default() -> Self

Forwards to infallible Self::default()

impl Drop for ConvolutionLayerInt8

fn drop(&mut self)

Executes the destructor for this type.

impl From<ConvolutionLayerInt8> for Algorithm

fn from(s: ConvolutionLayerInt8) -> Self

Converts to this type from the input type.

impl From<ConvolutionLayerInt8> for BaseConvolutionLayer

fn from(s: ConvolutionLayerInt8) -> Self

Converts to this type from the input type.

impl From<ConvolutionLayerInt8> for Layer

fn from(s: ConvolutionLayerInt8) -> Self

Converts to this type from the input type.

impl LayerTrait for 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 LayerTraitConst for 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 TryFrom<Layer> for ConvolutionLayerInt8

type Error = Error

The type returned in the event of a conversion error.

fn try_from(s: Layer) -> Result<Self>

Performs the conversion.

impl Send for ConvolutionLayerInt8