Module dnn

Source
Expand description

§Deep Neural Network module

This module contains: - API for new layers creation, layers are building bricks of neural networks; - set of built-in most-useful Layers; - API to construct and modify comprehensive neural networks from layers; - functionality for loading serialized networks models from different frameworks.

Functionality of this module is designed only for forward pass computations (i.e. network testing). A network training is in principle not supported.

Modules§

prelude

Structs§

AbsLayer
AccumLayer
AcosLayer
AcoshLayer
ActivationLayer
ActivationLayerInt8
ArgLayer
ArgMax/ArgMin layer
AsinLayer
AsinhLayer
AtanLayer
AtanhLayer
AttentionLayer
BNLLLayer
BackendNode
Derivatives of this class encapsulates functions of certain backends.
BackendWrapper
Derivatives of this class wraps cv::Mat for different backends and targets.
BaseConvolutionLayer
BatchNormLayer
BatchNormLayerInt8
BlankLayer
Partial List of Implemented Layers
CeilLayer
CeluLayer
ChannelsPReLULayer
ClassificationModel
This class represents high-level API for classification models.
CompareLayer
ConcatLayer
ConstLayer
Constant layer produces the same data blob at an every forward pass.
ConvolutionLayer
ConvolutionLayerInt8
CorrelationLayer
CosLayer
CoshLayer
CropAndResizeLayer
CropLayer
CumSumLayer
DataAugmentationLayer
DeconvolutionLayer
DepthToSpaceLayer
DequantizeLayer
DetectionModel
This class represents high-level API for object detection networks.
DetectionOutputLayer
Detection output layer.
Dict
This class implements name-value dictionary, values are instances of DictValue.
DictValue
This struct stores the scalar value (or array) of one of the following type: double, cv::String or int64. @todo Maybe int64 is useless because double type exactly stores at least 2^52 integers.
ELULayer
EinsumLayer
This function performs array summation based on the Einstein summation convention. The function allows for concise expressions of various mathematical operations using subscripts.
EltwiseLayer
Element wise operation on inputs
EltwiseLayerInt8
ErfLayer
ExpLayer
ExpandLayer
FlattenLayer
FloorLayer
FlowWarpLayer
GRULayer
GRU recurrent one-layer
GatherElementsLayer
GatherElements layer GatherElements takes two inputs data and indices of the same rank r >= 1 and an optional attribute axis and works such that: output[i][j][k] = data[index[i][j][k]][j][k] if axis = 0 and r = 3 output[i][j][k] = data[i][index[i][j][k]][k] if axis = 1 and r = 3 output[i][j][k] = data[i][j][index[i][j][k]] if axis = 2 and r = 3
GatherLayer
Gather layer
GeluApproximationLayer
GeluLayer
GemmLayer
GroupNormLayer
HardSigmoidLayer
HardSwishLayer
Image2BlobParams
Processing params of image to blob.
InnerProductLayer
InnerProduct, MatMul and Gemm operations are all implemented by Fully Connected Layer. Parameter is_matmul is used to distinguish MatMul and Gemm from InnerProduct.
InnerProductLayerInt8
InstanceNormLayer
InterpLayer
Bilinear resize layer from https://github.com/cdmh/deeplab-public-ver2
KeypointsModel
This class represents high-level API for keypoints models
LRNLayer
LSTMLayer
LSTM recurrent layer
Layer
This interface class allows to build new Layers - are building blocks of networks.
LayerFactory
%Layer factory allows to create instances of registered layers.
LayerNormLayer
LayerParams
This class provides all data needed to initialize layer.
LogLayer
MVNLayer
MatMulLayer
MaxUnpoolLayer
MishLayer
Model
This class is presented high-level API for neural networks.
NaryEltwiseLayer
Net
This class allows to create and manipulate comprehensive artificial neural networks.
NormalizeBBoxLayer
inline formula - normalization layer.
NotLayer
PaddingLayer
Adds extra values for specific axes.
PermuteLayer
PoolingLayer
PoolingLayerInt8
PowerLayer
PriorBoxLayer
ProposalLayer
QuantizeLayer
RNNLayer
Classical recurrent layer
ReLU6Layer
ReLULayer
ReciprocalLayer
ReduceLayer
RegionLayer
ReorgLayer
RequantizeLayer
ReshapeLayer
ResizeLayer
Resize input 4-dimensional blob by nearest neighbor or bilinear strategy.
RoundLayer
ScaleLayer
ScaleLayerInt8
ScatterLayer
ScatterNDLayer
SegmentationModel
This class represents high-level API for segmentation models
SeluLayer
ShiftLayer
ShiftLayerInt8
ShrinkLayer
ShuffleChannelLayer
Permute channels of 4-dimensional input blob.
SigmoidLayer
SignLayer
SinLayer
SinhLayer
SliceLayer
Slice layer has several modes:
SoftmaxLayer
SoftmaxLayerInt8
SoftplusLayer
SoftsignLayer
SpaceToDepthLayer
SplitLayer
SqrtLayer
SwishLayer
TanHLayer
TanLayer
TextDetectionModel
Base class for text detection networks
TextDetectionModel_DB
This class represents high-level API for text detection DL networks compatible with DB model.
TextDetectionModel_EAST
This class represents high-level API for text detection DL networks compatible with EAST model.
TextRecognitionModel
This class represents high-level API for text recognition networks.
ThresholdedReluLayer
TileLayer
TopKLayer
_Range

Enums§

Backend
Enum of computation backends supported by layers.
DataLayout
Enum of data layout for model inference.
ImagePaddingMode
Enum of image processing mode. To facilitate the specialization pre-processing requirements of the dnn model. For example, the letter box often used in the Yolo series of models.
SoftNMSMethod
Enum of Soft NMS methods.
Target
Enum of target devices for computations.

Constants§

CV_DNN_BACKEND_INFERENCE_ENGINE_NGRAPH
CV_DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_API
CV_DNN_INFERENCE_ENGINE_CPU_TYPE_ARM_COMPUTE
CV_DNN_INFERENCE_ENGINE_CPU_TYPE_X86
CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_2
CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X
CV_DNN_INFERENCE_ENGINE_VPU_TYPE_UNSPECIFIED
DNN_BACKEND_CANN
DNN_BACKEND_CUDA
DNN_BACKEND_DEFAULT
DNN_BACKEND_DEFAULT equals to OPENCV_DNN_BACKEND_DEFAULT, which can be defined using CMake or a configuration parameter
DNN_BACKEND_HALIDE
DNN_BACKEND_DEFAULT equals to OPENCV_DNN_BACKEND_DEFAULT, which can be defined using CMake or a configuration parameter
DNN_BACKEND_INFERENCE_ENGINE
Intel OpenVINO computational backend
DNN_BACKEND_OPENCV
DNN_BACKEND_TIMVX
DNN_BACKEND_VKCOM
DNN_BACKEND_WEBNN
DNN_LAYOUT_NCDHW
OpenCV data layout for 5D data.
DNN_LAYOUT_NCHW
OpenCV data layout for 4D data.
DNN_LAYOUT_ND
OpenCV data layout for 2D data.
DNN_LAYOUT_NDHWC
Tensorflow-like data layout for 5D data.
DNN_LAYOUT_NHWC
Tensorflow-like data layout for 4D data.
DNN_LAYOUT_PLANAR
Tensorflow-like data layout, it should only be used at tf or tflite model parsing.
DNN_LAYOUT_UNKNOWN
DNN_PMODE_CROP_CENTER
DNN_PMODE_LETTERBOX
DNN_PMODE_NULL
DNN_TARGET_CPU
DNN_TARGET_CPU_FP16
DNN_TARGET_CUDA
DNN_TARGET_CUDA_FP16
DNN_TARGET_FPGA
FPGA device with CPU fallbacks using Inference Engine’s Heterogeneous plugin.
DNN_TARGET_HDDL
DNN_TARGET_MYRIAD
DNN_TARGET_NPU
DNN_TARGET_OPENCL
DNN_TARGET_OPENCL_FP16
DNN_TARGET_VULKAN
OPENCV_DNN_API_VERSION
SoftNMSMethod_SOFTNMS_GAUSSIAN
SoftNMSMethod_SOFTNMS_LINEAR

Traits§

AbsLayerTrait
Mutable methods for crate::dnn::AbsLayer
AbsLayerTraitConst
Constant methods for crate::dnn::AbsLayer
AccumLayerTrait
Mutable methods for crate::dnn::AccumLayer
AccumLayerTraitConst
Constant methods for crate::dnn::AccumLayer
AcosLayerTrait
Mutable methods for crate::dnn::AcosLayer
AcosLayerTraitConst
Constant methods for crate::dnn::AcosLayer
AcoshLayerTrait
Mutable methods for crate::dnn::AcoshLayer
AcoshLayerTraitConst
Constant methods for crate::dnn::AcoshLayer
ActivationLayerInt8Trait
Mutable methods for crate::dnn::ActivationLayerInt8
ActivationLayerInt8TraitConst
Constant methods for crate::dnn::ActivationLayerInt8
ActivationLayerTrait
Mutable methods for crate::dnn::ActivationLayer
ActivationLayerTraitConst
Constant methods for crate::dnn::ActivationLayer
ArgLayerTrait
Mutable methods for crate::dnn::ArgLayer
ArgLayerTraitConst
Constant methods for crate::dnn::ArgLayer
AsinLayerTrait
Mutable methods for crate::dnn::AsinLayer
AsinLayerTraitConst
Constant methods for crate::dnn::AsinLayer
AsinhLayerTrait
Mutable methods for crate::dnn::AsinhLayer
AsinhLayerTraitConst
Constant methods for crate::dnn::AsinhLayer
AtanLayerTrait
Mutable methods for crate::dnn::AtanLayer
AtanLayerTraitConst
Constant methods for crate::dnn::AtanLayer
AtanhLayerTrait
Mutable methods for crate::dnn::AtanhLayer
AtanhLayerTraitConst
Constant methods for crate::dnn::AtanhLayer
AttentionLayerTrait
Mutable methods for crate::dnn::AttentionLayer
AttentionLayerTraitConst
Constant methods for crate::dnn::AttentionLayer
BNLLLayerTrait
Mutable methods for crate::dnn::BNLLLayer
BNLLLayerTraitConst
Constant methods for crate::dnn::BNLLLayer
BackendNodeTrait
Mutable methods for crate::dnn::BackendNode
BackendNodeTraitConst
Constant methods for crate::dnn::BackendNode
BackendWrapperTrait
Mutable methods for crate::dnn::BackendWrapper
BackendWrapperTraitConst
Constant methods for crate::dnn::BackendWrapper
BaseConvolutionLayerTrait
Mutable methods for crate::dnn::BaseConvolutionLayer
BaseConvolutionLayerTraitConst
Constant methods for crate::dnn::BaseConvolutionLayer
BatchNormLayerInt8Trait
Mutable methods for crate::dnn::BatchNormLayerInt8
BatchNormLayerInt8TraitConst
Constant methods for crate::dnn::BatchNormLayerInt8
BatchNormLayerTrait
Mutable methods for crate::dnn::BatchNormLayer
BatchNormLayerTraitConst
Constant methods for crate::dnn::BatchNormLayer
BlankLayerTrait
Mutable methods for crate::dnn::BlankLayer
BlankLayerTraitConst
Constant methods for crate::dnn::BlankLayer
CeilLayerTrait
Mutable methods for crate::dnn::CeilLayer
CeilLayerTraitConst
Constant methods for crate::dnn::CeilLayer
CeluLayerTrait
Mutable methods for crate::dnn::CeluLayer
CeluLayerTraitConst
Constant methods for crate::dnn::CeluLayer
ChannelsPReLULayerTrait
Mutable methods for crate::dnn::ChannelsPReLULayer
ChannelsPReLULayerTraitConst
Constant methods for crate::dnn::ChannelsPReLULayer
ClassificationModelTrait
Mutable methods for crate::dnn::ClassificationModel
ClassificationModelTraitConst
Constant methods for crate::dnn::ClassificationModel
CompareLayerTrait
Mutable methods for crate::dnn::CompareLayer
CompareLayerTraitConst
Constant methods for crate::dnn::CompareLayer
ConcatLayerTrait
Mutable methods for crate::dnn::ConcatLayer
ConcatLayerTraitConst
Constant methods for crate::dnn::ConcatLayer
ConstLayerTrait
Mutable methods for crate::dnn::ConstLayer
ConstLayerTraitConst
Constant methods for crate::dnn::ConstLayer
ConvolutionLayerInt8Trait
Mutable methods for crate::dnn::ConvolutionLayerInt8
ConvolutionLayerInt8TraitConst
Constant methods for crate::dnn::ConvolutionLayerInt8
ConvolutionLayerTrait
Mutable methods for crate::dnn::ConvolutionLayer
ConvolutionLayerTraitConst
Constant methods for crate::dnn::ConvolutionLayer
CorrelationLayerTrait
Mutable methods for crate::dnn::CorrelationLayer
CorrelationLayerTraitConst
Constant methods for crate::dnn::CorrelationLayer
CosLayerTrait
Mutable methods for crate::dnn::CosLayer
CosLayerTraitConst
Constant methods for crate::dnn::CosLayer
CoshLayerTrait
Mutable methods for crate::dnn::CoshLayer
CoshLayerTraitConst
Constant methods for crate::dnn::CoshLayer
CropAndResizeLayerTrait
Mutable methods for crate::dnn::CropAndResizeLayer
CropAndResizeLayerTraitConst
Constant methods for crate::dnn::CropAndResizeLayer
CropLayerTrait
Mutable methods for crate::dnn::CropLayer
CropLayerTraitConst
Constant methods for crate::dnn::CropLayer
CumSumLayerTrait
Mutable methods for crate::dnn::CumSumLayer
CumSumLayerTraitConst
Constant methods for crate::dnn::CumSumLayer
DataAugmentationLayerTrait
Mutable methods for crate::dnn::DataAugmentationLayer
DataAugmentationLayerTraitConst
Constant methods for crate::dnn::DataAugmentationLayer
DeconvolutionLayerTrait
Mutable methods for crate::dnn::DeconvolutionLayer
DeconvolutionLayerTraitConst
Constant methods for crate::dnn::DeconvolutionLayer
DepthToSpaceLayerTrait
Mutable methods for crate::dnn::DepthToSpaceLayer
DepthToSpaceLayerTraitConst
Constant methods for crate::dnn::DepthToSpaceLayer
DequantizeLayerTrait
Mutable methods for crate::dnn::DequantizeLayer
DequantizeLayerTraitConst
Constant methods for crate::dnn::DequantizeLayer
DetectionModelTrait
Mutable methods for crate::dnn::DetectionModel
DetectionModelTraitConst
Constant methods for crate::dnn::DetectionModel
DetectionOutputLayerTrait
Mutable methods for crate::dnn::DetectionOutputLayer
DetectionOutputLayerTraitConst
Constant methods for crate::dnn::DetectionOutputLayer
DictTrait
Mutable methods for crate::dnn::Dict
DictTraitConst
Constant methods for crate::dnn::Dict
DictValueTrait
Mutable methods for crate::dnn::DictValue
DictValueTraitConst
Constant methods for crate::dnn::DictValue
ELULayerTrait
Mutable methods for crate::dnn::ELULayer
ELULayerTraitConst
Constant methods for crate::dnn::ELULayer
EinsumLayerTrait
Mutable methods for crate::dnn::EinsumLayer
EinsumLayerTraitConst
Constant methods for crate::dnn::EinsumLayer
EltwiseLayerInt8Trait
Mutable methods for crate::dnn::EltwiseLayerInt8
EltwiseLayerInt8TraitConst
Constant methods for crate::dnn::EltwiseLayerInt8
EltwiseLayerTrait
Mutable methods for crate::dnn::EltwiseLayer
EltwiseLayerTraitConst
Constant methods for crate::dnn::EltwiseLayer
ErfLayerTrait
Mutable methods for crate::dnn::ErfLayer
ErfLayerTraitConst
Constant methods for crate::dnn::ErfLayer
ExpLayerTrait
Mutable methods for crate::dnn::ExpLayer
ExpLayerTraitConst
Constant methods for crate::dnn::ExpLayer
ExpandLayerTrait
Mutable methods for crate::dnn::ExpandLayer
ExpandLayerTraitConst
Constant methods for crate::dnn::ExpandLayer
FlattenLayerTrait
Mutable methods for crate::dnn::FlattenLayer
FlattenLayerTraitConst
Constant methods for crate::dnn::FlattenLayer
FloorLayerTrait
Mutable methods for crate::dnn::FloorLayer
FloorLayerTraitConst
Constant methods for crate::dnn::FloorLayer
FlowWarpLayerTrait
Mutable methods for crate::dnn::FlowWarpLayer
FlowWarpLayerTraitConst
Constant methods for crate::dnn::FlowWarpLayer
GRULayerTrait
Mutable methods for crate::dnn::GRULayer
GRULayerTraitConst
Constant methods for crate::dnn::GRULayer
GatherElementsLayerTrait
Mutable methods for crate::dnn::GatherElementsLayer
GatherElementsLayerTraitConst
Constant methods for crate::dnn::GatherElementsLayer
GatherLayerTrait
Mutable methods for crate::dnn::GatherLayer
GatherLayerTraitConst
Constant methods for crate::dnn::GatherLayer
GeluApproximationLayerTrait
Mutable methods for crate::dnn::GeluApproximationLayer
GeluApproximationLayerTraitConst
Constant methods for crate::dnn::GeluApproximationLayer
GeluLayerTrait
Mutable methods for crate::dnn::GeluLayer
GeluLayerTraitConst
Constant methods for crate::dnn::GeluLayer
GemmLayerTrait
Mutable methods for crate::dnn::GemmLayer
GemmLayerTraitConst
Constant methods for crate::dnn::GemmLayer
GroupNormLayerTrait
Mutable methods for crate::dnn::GroupNormLayer
GroupNormLayerTraitConst
Constant methods for crate::dnn::GroupNormLayer
HardSigmoidLayerTrait
Mutable methods for crate::dnn::HardSigmoidLayer
HardSigmoidLayerTraitConst
Constant methods for crate::dnn::HardSigmoidLayer
HardSwishLayerTrait
Mutable methods for crate::dnn::HardSwishLayer
HardSwishLayerTraitConst
Constant methods for crate::dnn::HardSwishLayer
InnerProductLayerInt8Trait
Mutable methods for crate::dnn::InnerProductLayerInt8
InnerProductLayerInt8TraitConst
Constant methods for crate::dnn::InnerProductLayerInt8
InnerProductLayerTrait
Mutable methods for crate::dnn::InnerProductLayer
InnerProductLayerTraitConst
Constant methods for crate::dnn::InnerProductLayer
InstanceNormLayerTrait
Mutable methods for crate::dnn::InstanceNormLayer
InstanceNormLayerTraitConst
Constant methods for crate::dnn::InstanceNormLayer
InterpLayerTrait
Mutable methods for crate::dnn::InterpLayer
InterpLayerTraitConst
Constant methods for crate::dnn::InterpLayer
KeypointsModelTrait
Mutable methods for crate::dnn::KeypointsModel
KeypointsModelTraitConst
Constant methods for crate::dnn::KeypointsModel
LRNLayerTrait
Mutable methods for crate::dnn::LRNLayer
LRNLayerTraitConst
Constant methods for crate::dnn::LRNLayer
LSTMLayerTrait
Mutable methods for crate::dnn::LSTMLayer
LSTMLayerTraitConst
Constant methods for crate::dnn::LSTMLayer
LayerFactoryTrait
Mutable methods for crate::dnn::LayerFactory
LayerFactoryTraitConst
Constant methods for crate::dnn::LayerFactory
LayerNormLayerTrait
Mutable methods for crate::dnn::LayerNormLayer
LayerNormLayerTraitConst
Constant methods for crate::dnn::LayerNormLayer
LayerParamsTrait
Mutable methods for crate::dnn::LayerParams
LayerParamsTraitConst
Constant methods for crate::dnn::LayerParams
LayerTrait
Mutable methods for crate::dnn::Layer
LayerTraitConst
Constant methods for crate::dnn::Layer
LogLayerTrait
Mutable methods for crate::dnn::LogLayer
LogLayerTraitConst
Constant methods for crate::dnn::LogLayer
MVNLayerTrait
Mutable methods for crate::dnn::MVNLayer
MVNLayerTraitConst
Constant methods for crate::dnn::MVNLayer
MatMulLayerTrait
Mutable methods for crate::dnn::MatMulLayer
MatMulLayerTraitConst
Constant methods for crate::dnn::MatMulLayer
MaxUnpoolLayerTrait
Mutable methods for crate::dnn::MaxUnpoolLayer
MaxUnpoolLayerTraitConst
Constant methods for crate::dnn::MaxUnpoolLayer
MishLayerTrait
Mutable methods for crate::dnn::MishLayer
MishLayerTraitConst
Constant methods for crate::dnn::MishLayer
ModelTrait
Mutable methods for crate::dnn::Model
ModelTraitConst
Constant methods for crate::dnn::Model
NaryEltwiseLayerTrait
Mutable methods for crate::dnn::NaryEltwiseLayer
NaryEltwiseLayerTraitConst
Constant methods for crate::dnn::NaryEltwiseLayer
NetTrait
Mutable methods for crate::dnn::Net
NetTraitConst
Constant methods for crate::dnn::Net
NormalizeBBoxLayerTrait
Mutable methods for crate::dnn::NormalizeBBoxLayer
NormalizeBBoxLayerTraitConst
Constant methods for crate::dnn::NormalizeBBoxLayer
NotLayerTrait
Mutable methods for crate::dnn::NotLayer
NotLayerTraitConst
Constant methods for crate::dnn::NotLayer
PaddingLayerTrait
Mutable methods for crate::dnn::PaddingLayer
PaddingLayerTraitConst
Constant methods for crate::dnn::PaddingLayer
PermuteLayerTrait
Mutable methods for crate::dnn::PermuteLayer
PermuteLayerTraitConst
Constant methods for crate::dnn::PermuteLayer
PoolingLayerInt8Trait
Mutable methods for crate::dnn::PoolingLayerInt8
PoolingLayerInt8TraitConst
Constant methods for crate::dnn::PoolingLayerInt8
PoolingLayerTrait
Mutable methods for crate::dnn::PoolingLayer
PoolingLayerTraitConst
Constant methods for crate::dnn::PoolingLayer
PowerLayerTrait
Mutable methods for crate::dnn::PowerLayer
PowerLayerTraitConst
Constant methods for crate::dnn::PowerLayer
PriorBoxLayerTrait
Mutable methods for crate::dnn::PriorBoxLayer
PriorBoxLayerTraitConst
Constant methods for crate::dnn::PriorBoxLayer
ProposalLayerTrait
Mutable methods for crate::dnn::ProposalLayer
ProposalLayerTraitConst
Constant methods for crate::dnn::ProposalLayer
QuantizeLayerTrait
Mutable methods for crate::dnn::QuantizeLayer
QuantizeLayerTraitConst
Constant methods for crate::dnn::QuantizeLayer
RNNLayerTrait
Mutable methods for crate::dnn::RNNLayer
RNNLayerTraitConst
Constant methods for crate::dnn::RNNLayer
ReLU6LayerTrait
Mutable methods for crate::dnn::ReLU6Layer
ReLU6LayerTraitConst
Constant methods for crate::dnn::ReLU6Layer
ReLULayerTrait
Mutable methods for crate::dnn::ReLULayer
ReLULayerTraitConst
Constant methods for crate::dnn::ReLULayer
ReciprocalLayerTrait
Mutable methods for crate::dnn::ReciprocalLayer
ReciprocalLayerTraitConst
Constant methods for crate::dnn::ReciprocalLayer
ReduceLayerTrait
Mutable methods for crate::dnn::ReduceLayer
ReduceLayerTraitConst
Constant methods for crate::dnn::ReduceLayer
RegionLayerTrait
Mutable methods for crate::dnn::RegionLayer
RegionLayerTraitConst
Constant methods for crate::dnn::RegionLayer
ReorgLayerTrait
Mutable methods for crate::dnn::ReorgLayer
ReorgLayerTraitConst
Constant methods for crate::dnn::ReorgLayer
RequantizeLayerTrait
Mutable methods for crate::dnn::RequantizeLayer
RequantizeLayerTraitConst
Constant methods for crate::dnn::RequantizeLayer
ReshapeLayerTrait
Mutable methods for crate::dnn::ReshapeLayer
ReshapeLayerTraitConst
Constant methods for crate::dnn::ReshapeLayer
ResizeLayerTrait
Mutable methods for crate::dnn::ResizeLayer
ResizeLayerTraitConst
Constant methods for crate::dnn::ResizeLayer
RoundLayerTrait
Mutable methods for crate::dnn::RoundLayer
RoundLayerTraitConst
Constant methods for crate::dnn::RoundLayer
ScaleLayerInt8Trait
Mutable methods for crate::dnn::ScaleLayerInt8
ScaleLayerInt8TraitConst
Constant methods for crate::dnn::ScaleLayerInt8
ScaleLayerTrait
Mutable methods for crate::dnn::ScaleLayer
ScaleLayerTraitConst
Constant methods for crate::dnn::ScaleLayer
ScatterLayerTrait
Mutable methods for crate::dnn::ScatterLayer
ScatterLayerTraitConst
Constant methods for crate::dnn::ScatterLayer
ScatterNDLayerTrait
Mutable methods for crate::dnn::ScatterNDLayer
ScatterNDLayerTraitConst
Constant methods for crate::dnn::ScatterNDLayer
SegmentationModelTrait
Mutable methods for crate::dnn::SegmentationModel
SegmentationModelTraitConst
Constant methods for crate::dnn::SegmentationModel
SeluLayerTrait
Mutable methods for crate::dnn::SeluLayer
SeluLayerTraitConst
Constant methods for crate::dnn::SeluLayer
ShiftLayerInt8Trait
Mutable methods for crate::dnn::ShiftLayerInt8
ShiftLayerInt8TraitConst
Constant methods for crate::dnn::ShiftLayerInt8
ShiftLayerTrait
Mutable methods for crate::dnn::ShiftLayer
ShiftLayerTraitConst
Constant methods for crate::dnn::ShiftLayer
ShrinkLayerTrait
Mutable methods for crate::dnn::ShrinkLayer
ShrinkLayerTraitConst
Constant methods for crate::dnn::ShrinkLayer
ShuffleChannelLayerTrait
Mutable methods for crate::dnn::ShuffleChannelLayer
ShuffleChannelLayerTraitConst
Constant methods for crate::dnn::ShuffleChannelLayer
SigmoidLayerTrait
Mutable methods for crate::dnn::SigmoidLayer
SigmoidLayerTraitConst
Constant methods for crate::dnn::SigmoidLayer
SignLayerTrait
Mutable methods for crate::dnn::SignLayer
SignLayerTraitConst
Constant methods for crate::dnn::SignLayer
SinLayerTrait
Mutable methods for crate::dnn::SinLayer
SinLayerTraitConst
Constant methods for crate::dnn::SinLayer
SinhLayerTrait
Mutable methods for crate::dnn::SinhLayer
SinhLayerTraitConst
Constant methods for crate::dnn::SinhLayer
SliceLayerTrait
Mutable methods for crate::dnn::SliceLayer
SliceLayerTraitConst
Constant methods for crate::dnn::SliceLayer
SoftmaxLayerInt8Trait
Mutable methods for crate::dnn::SoftmaxLayerInt8
SoftmaxLayerInt8TraitConst
Constant methods for crate::dnn::SoftmaxLayerInt8
SoftmaxLayerTrait
Mutable methods for crate::dnn::SoftmaxLayer
SoftmaxLayerTraitConst
Constant methods for crate::dnn::SoftmaxLayer
SoftplusLayerTrait
Mutable methods for crate::dnn::SoftplusLayer
SoftplusLayerTraitConst
Constant methods for crate::dnn::SoftplusLayer
SoftsignLayerTrait
Mutable methods for crate::dnn::SoftsignLayer
SoftsignLayerTraitConst
Constant methods for crate::dnn::SoftsignLayer
SpaceToDepthLayerTrait
Mutable methods for crate::dnn::SpaceToDepthLayer
SpaceToDepthLayerTraitConst
Constant methods for crate::dnn::SpaceToDepthLayer
SplitLayerTrait
Mutable methods for crate::dnn::SplitLayer
SplitLayerTraitConst
Constant methods for crate::dnn::SplitLayer
SqrtLayerTrait
Mutable methods for crate::dnn::SqrtLayer
SqrtLayerTraitConst
Constant methods for crate::dnn::SqrtLayer
SwishLayerTrait
Mutable methods for crate::dnn::SwishLayer
SwishLayerTraitConst
Constant methods for crate::dnn::SwishLayer
TanHLayerTrait
Mutable methods for crate::dnn::TanHLayer
TanHLayerTraitConst
Constant methods for crate::dnn::TanHLayer
TanLayerTrait
Mutable methods for crate::dnn::TanLayer
TanLayerTraitConst
Constant methods for crate::dnn::TanLayer
TextDetectionModelTrait
Mutable methods for crate::dnn::TextDetectionModel
TextDetectionModelTraitConst
Constant methods for crate::dnn::TextDetectionModel
TextDetectionModel_DBTrait
Mutable methods for crate::dnn::TextDetectionModel_DB
TextDetectionModel_DBTraitConst
Constant methods for crate::dnn::TextDetectionModel_DB
TextDetectionModel_EASTTrait
Mutable methods for crate::dnn::TextDetectionModel_EAST
TextDetectionModel_EASTTraitConst
Constant methods for crate::dnn::TextDetectionModel_EAST
TextRecognitionModelTrait
Mutable methods for crate::dnn::TextRecognitionModel
TextRecognitionModelTraitConst
Constant methods for crate::dnn::TextRecognitionModel
ThresholdedReluLayerTrait
Mutable methods for crate::dnn::ThresholdedReluLayer
ThresholdedReluLayerTraitConst
Constant methods for crate::dnn::ThresholdedReluLayer
TileLayerTrait
Mutable methods for crate::dnn::TileLayer
TileLayerTraitConst
Constant methods for crate::dnn::TileLayer
TopKLayerTrait
Mutable methods for crate::dnn::TopKLayer
TopKLayerTraitConst
Constant methods for crate::dnn::TopKLayer
_RangeTrait
Mutable methods for crate::dnn::_Range
_RangeTraitConst
Constant methods for crate::dnn::_Range

Functions§

blob_from_image
Creates 4-dimensional blob from image. Optionally resizes and crops @p image from center, subtract @p mean values, scales values by @p scalefactor, swap Blue and Red channels.
blob_from_image_def
Creates 4-dimensional blob from image. Optionally resizes and crops @p image from center, subtract @p mean values, scales values by @p scalefactor, swap Blue and Red channels.
blob_from_image_to
Creates 4-dimensional blob from image. @details This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
blob_from_image_to_def
Creates 4-dimensional blob from image. @details This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
blob_from_image_with_params
Creates 4-dimensional blob from image with given params.
blob_from_image_with_params_1
Creates 4-dimensional blob from image with given params.
blob_from_image_with_params_1_def
@overload
blob_from_image_with_params_def
Creates 4-dimensional blob from image with given params.
blob_from_images
Creates 4-dimensional blob from series of images. Optionally resizes and crops @p images from center, subtract @p mean values, scales values by @p scalefactor, swap Blue and Red channels.
blob_from_images_def
Creates 4-dimensional blob from series of images. Optionally resizes and crops @p images from center, subtract @p mean values, scales values by @p scalefactor, swap Blue and Red channels.
blob_from_images_to
Creates 4-dimensional blob from series of images. @details This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
blob_from_images_to_def
Creates 4-dimensional blob from series of images. @details This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
blob_from_images_with_params
Creates 4-dimensional blob from series of images with given params.
blob_from_images_with_params_1
Creates 4-dimensional blob from series of images with given params.
blob_from_images_with_params_1_def
@overload
blob_from_images_with_params_def
Creates 4-dimensional blob from series of images with given params.
concat
enable_model_diagnostics
Enables detailed logging of the DNN model loading with CV DNN API.
get_available_backends
get_available_targets
get_inference_engine_backend_type
Returns Inference Engine internal backend API.
get_inference_engine_cpu_type
Returns Inference Engine CPU type.
get_inference_engine_vpu_type
Returns Inference Engine VPU type.
get_plane
images_from_blob
Parse a 4D blob and output the images it contains as 2D arrays through a simpler data structure (std::vectorcv::Mat).
nms_boxes
Performs non maximum suppression given boxes and corresponding scores.
nms_boxes_batched
Performs batched non maximum suppression on given boxes and corresponding scores across different classes.
nms_boxes_batched_1
C++ default parameters
nms_boxes_batched_1_def
Note
nms_boxes_batched_def
Performs batched non maximum suppression on given boxes and corresponding scores across different classes.
nms_boxes_def
Performs non maximum suppression given boxes and corresponding scores.
nms_boxes_f64
C++ default parameters
nms_boxes_f64_def
Note
nms_boxes_rotated
C++ default parameters
nms_boxes_rotated_def
Note
read_net
Read deep learning network represented in one of the supported formats.
read_net_1
Read deep learning network represented in one of the supported formats. @details This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
read_net_1_def
Read deep learning network represented in one of the supported formats. @details This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
read_net_def
Read deep learning network represented in one of the supported formats.
read_net_from_caffe
Reads a network model stored in Caffe framework’s format.
read_net_from_caffe_buffer
Reads a network model stored in Caffe model in memory.
read_net_from_caffe_buffer_def
Reads a network model stored in Caffe model in memory.
read_net_from_caffe_def
Reads a network model stored in Caffe framework’s format.
read_net_from_caffe_str
Reads a network model stored in Caffe model in memory. @details This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
read_net_from_caffe_str_def
Reads a network model stored in Caffe model in memory. @details This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
read_net_from_darknet
Reads a network model stored in Darknet model files.
read_net_from_darknet_buffer
Reads a network model stored in Darknet model files.
read_net_from_darknet_buffer_def
Reads a network model stored in Darknet model files.
read_net_from_darknet_def
Reads a network model stored in Darknet model files.
read_net_from_darknet_str
Reads a network model stored in Darknet model files.
read_net_from_darknet_str_def
Reads a network model stored in Darknet model files.
read_net_from_model_optimizer
Load a network from Intel’s Model Optimizer intermediate representation.
read_net_from_model_optimizer_1
Load a network from Intel’s Model Optimizer intermediate representation.
read_net_from_model_optimizer_2
Load a network from Intel’s Model Optimizer intermediate representation.
read_net_from_model_optimizer_def
Load a network from Intel’s Model Optimizer intermediate representation.
read_net_from_onnx
Reads a network model ONNX.
read_net_from_onnx_buffer
Reads a network model from ONNX in-memory buffer.
read_net_from_onnx_str
Reads a network model from ONNX in-memory buffer.
read_net_from_tensorflow
Reads a network model stored in TensorFlow framework’s format.
read_net_from_tensorflow_buffer
Reads a network model stored in TensorFlow framework’s format.
read_net_from_tensorflow_buffer_def
Reads a network model stored in TensorFlow framework’s format.
read_net_from_tensorflow_def
Reads a network model stored in TensorFlow framework’s format.
read_net_from_tensorflow_str
Reads a network model stored in TensorFlow framework’s format. @details This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
read_net_from_tensorflow_str_def
Reads a network model stored in TensorFlow framework’s format. @details This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
read_net_from_tf_lite
Reads a network model stored in TFLite framework’s format.
read_net_from_tf_lite_1
Reads a network model stored in TFLite framework’s format.
read_net_from_tf_lite_2
Reads a network model stored in TFLite framework’s format. @details This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
read_net_from_torch
Reads a network model stored in Torch7 framework’s format.
read_net_from_torch_def
Reads a network model stored in Torch7 framework’s format.
read_tensor_from_onnx
Creates blob from .pb file.
read_torch_blob
Loads blob which was serialized as torch.Tensor object of Torch7 framework. @warning This function has the same limitations as readNetFromTorch().
read_torch_blob_def
Loads blob which was serialized as torch.Tensor object of Torch7 framework. @warning This function has the same limitations as readNetFromTorch().
release_hddl_plugin
Release a HDDL plugin.
reset_myriad_device
Release a Myriad device (binded by OpenCV).
set_inference_engine_backend_type
Specify Inference Engine internal backend API.
shape
shape_1
shape_2
shape_3
shape_4
C++ default parameters
shape_4_def
Note
shrink_caffe_model
Convert all weights of Caffe network to half precision floating point.
shrink_caffe_model_def
Convert all weights of Caffe network to half precision floating point.
slice
slice_1
slice_2
slice_3
soft_nms_boxes
Performs soft non maximum suppression given boxes and corresponding scores. Reference: https://arxiv.org/abs/1704.04503
soft_nms_boxes_def
Performs soft non maximum suppression given boxes and corresponding scores. Reference: https://arxiv.org/abs/1704.04503
total
C++ default parameters
total_1
C++ default parameters
total_1_def
Note
total_def
Note
write_text_graph
Create a text representation for a binary network stored in protocol buffer format.

Type Aliases§

LayerFactory_Constructor
Each Layer class must provide this function to the factory
MatShape
Net_LayerIdDeprecated
Container for strings and integers.