Namespaces
	accessor

	details

Classes
struct	_Range

class	AbsLayer

class	AccumLayer

class	AcoshLayer

class	AcosLayer

class	ActivationLayer

class	ActivationLayerInt8

class	ArgLayer
	ArgMax/ArgMin layer. More...

class	AsinhLayer

class	AsinLayer

class	AtanhLayer

class	AtanLayer

class	BackendNode
	Derivatives of this class encapsulates functions of certain backends. More...

class	BackendWrapper
	Derivatives of this class wraps cv::Mat for different backends and targets. More...

class	BaseConvolutionLayer

class	BatchNormLayer

class	BatchNormLayerInt8

class	BlankLayer

class	BNLLLayer

class	CeilLayer

class	CeluLayer

class	ChannelsPReLULayer

class	ClassificationModel
	This class represents high-level API for classification models. More...

class	CompareLayer

class	ConcatLayer

class	ConstLayer

class	ConvolutionLayer

class	ConvolutionLayerInt8

class	CorrelationLayer

class	CoshLayer

class	CosLayer

class	CropAndResizeLayer

class	CropLayer

class	CumSumLayer

class	DataAugmentationLayer

class	DeconvolutionLayer

class	DequantizeLayer

class	DetectionModel
	This class represents high-level API for object detection networks. More...

class	DetectionOutputLayer
	Detection output layer. More...

class	Dict
	This class implements name-value dictionary, values are instances of DictValue. More...

struct	DictValue
	This struct stores the scalar value (or array) of one of the following type: double, cv::String or int64. More...

class	EltwiseLayer
	Element wise operation on inputs. More...

class	EltwiseLayerInt8

class	ELULayer

class	ErfLayer

class	ExpLayer

class	FlattenLayer

class	FloorLayer

class	FlowWarpLayer

class	GatherLayer
	Gather layer. More...

class	GRULayer
	GRU recurrent one-layer. More...

class	HardSigmoidLayer

class	HardSwishLayer

class	InnerProductLayer

class	InnerProductLayerInt8

class	InterpLayer
	Bilinear resize layer from https://github.com/cdmh/deeplab-public-ver2. More...

class	KeypointsModel
	This class represents high-level API for keypoints models. More...

class	Layer
	This interface class allows to build new Layers - are building blocks of networks. More...

class	LayerFactory
	Layer factory allows to create instances of registered layers. More...

class	LayerParams
	This class provides all data needed to initialize layer. More...

class	LogLayer

class	LRNLayer

class	LSTMLayer
	LSTM recurrent layer. More...

class	MaxUnpoolLayer

class	MishLayer

class	Model
	This class is presented high-level API for neural networks. More...

class	MVNLayer

class	NaryEltwiseLayer

class	Net
	This class allows to create and manipulate comprehensive artificial neural networks. More...

class	NormalizeBBoxLayer
	\( L_p \) - normalization layer. More...

class	NotLayer

class	PaddingLayer
	Adds extra values for specific axes. More...

class	PermuteLayer

class	PoolingLayer

class	PoolingLayerInt8

class	PowerLayer

class	PriorBoxLayer

class	ProposalLayer

class	QuantizeLayer

class	ReciprocalLayer

class	ReduceLayer

class	ReduceLayerInt8

class	RegionLayer

class	ReLU6Layer

class	ReLULayer

class	ReorgLayer

class	RequantizeLayer

class	ReshapeLayer

class	ResizeLayer
	Resize input 4-dimensional blob by nearest neighbor or bilinear strategy. More...

class	RNNLayer
	Classical recurrent layer. More...

class	RoundLayer

class	ScaleLayer

class	ScaleLayerInt8

class	ScatterLayer

class	ScatterNDLayer

class	SegmentationModel
	This class represents high-level API for segmentation models. More...

class	SeluLayer

class	ShiftLayer

class	ShiftLayerInt8

class	ShrinkLayer

class	ShuffleChannelLayer

class	SigmoidLayer

class	SignLayer

class	SinhLayer

class	SinLayer

class	SliceLayer

class	SoftmaxLayer

class	SoftmaxLayerInt8

class	SoftplusLayer

class	SoftsignLayer

class	SplitLayer

class	SqrtLayer

class	SwishLayer

class	TanHLayer

class	TanLayer

class	TextDetectionModel
	Base class for text detection networks. More...

class	TextDetectionModel_DB
	This class represents high-level API for text detection DL networks compatible with DB model. More...

class	TextDetectionModel_EAST
	This class represents high-level API for text detection DL networks compatible with EAST model. More...

class	TextRecognitionModel
	This class represents high-level API for text recognition networks. More...

class	ThresholdedReluLayer

class	TileLayer

Typedefs
typedef std::map< std::string, std::vector< LayerFactory::Constructor > >	LayerFactory_Impl

typedef std::vector< int >	MatShape

Enumerations
enum	Backend { DNN_BACKEND_DEFAULT = 0, DNN_BACKEND_HALIDE, DNN_BACKEND_INFERENCE_ENGINE, DNN_BACKEND_OPENCV, DNN_BACKEND_VKCOM, DNN_BACKEND_CUDA, DNN_BACKEND_WEBNN, DNN_BACKEND_TIMVX, DNN_BACKEND_CANN }
	Enum of computation backends supported by layers. More...

enum	SoftNMSMethod { SoftNMSMethod::SOFTNMS_LINEAR = 1, SoftNMSMethod::SOFTNMS_GAUSSIAN = 2 }
	Enum of Soft NMS methods. More...

enum	Target { DNN_TARGET_CPU = 0, DNN_TARGET_OPENCL, DNN_TARGET_OPENCL_FP16, DNN_TARGET_MYRIAD, DNN_TARGET_VULKAN, DNN_TARGET_FPGA, DNN_TARGET_CUDA, DNN_TARGET_CUDA_FP16, DNN_TARGET_HDDL, DNN_TARGET_NPU }
	Enum of target devices for computations. More...

Functions
Mat	blobFromImage (InputArray image, double scalefactor=1.0, const Size &size=Size(), const Scalar &mean=Scalar(), bool swapRB=false, bool crop=false, int ddepth=CV_32F)
	Creates 4-dimensional blob from image. Optionally resizes and crops `image` from center, subtract `mean` values, scales values by `scalefactor`, swap Blue and Red channels. More...

void	blobFromImage (InputArray image, OutputArray blob, double scalefactor=1.0, const Size &size=Size(), const Scalar &mean=Scalar(), bool swapRB=false, bool crop=false, int ddepth=CV_32F)
	Creates 4-dimensional blob from image. More...

Mat	blobFromImages (InputArrayOfArrays images, double scalefactor=1.0, Size size=Size(), const Scalar &mean=Scalar(), bool swapRB=false, bool crop=false, int ddepth=CV_32F)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops `images` from center, subtract `mean` values, scales values by `scalefactor`, swap Blue and Red channels. More...

void	blobFromImages (InputArrayOfArrays images, OutputArray blob, double scalefactor=1.0, Size size=Size(), const Scalar &mean=Scalar(), bool swapRB=false, bool crop=false, int ddepth=CV_32F)
	Creates 4-dimensional blob from series of images. More...

static MatShape	concat (const MatShape &a, const MatShape &b)

void	enableModelDiagnostics (bool isDiagnosticsMode)
	Enables detailed logging of the DNN model loading with CV DNN API. More...

std::vector< std::pair< Backend, Target > >	getAvailableBackends ()

std::vector< Target >	getAvailableTargets (dnn::Backend be)

cv::String	getInferenceEngineBackendType ()
	Returns Inference Engine internal backend API. More...

cv::String	getInferenceEngineCPUType ()
	Returns Inference Engine CPU type. More...

cv::String	getInferenceEngineVPUType ()
	Returns Inference Engine VPU type. More...

LayerFactory_Impl &	getLayerFactoryImpl ()

Mutex &	getLayerFactoryMutex ()
	Get the mutex guarding LayerFactory_Impl, see getLayerFactoryImpl() function. More...

static Mat	getPlane (const Mat &m, int n, int cn)

void	imagesFromBlob (const cv::Mat &blob_, OutputArrayOfArrays images_)
	Parse a 4D blob and output the images it contains as 2D arrays through a simpler data structure (std::vector<cv::Mat>). More...

static bool	isAllOnes (const MatShape &inputShape, int startPos, int endPos)

void	NMSBoxes (const std::vector< Rect > &bboxes, const std::vector< float > &scores, const float score_threshold, const float nms_threshold, std::vector< int > &indices, const float eta=1.f, const int top_k=0)
	Performs non maximum suppression given boxes and corresponding scores. More...

void	NMSBoxes (const std::vector< Rect2d > &bboxes, const std::vector< float > &scores, const float score_threshold, const float nms_threshold, std::vector< int > &indices, const float eta=1.f, const int top_k=0)

void	NMSBoxes (const std::vector< RotatedRect > &bboxes, const std::vector< float > &scores, const float score_threshold, const float nms_threshold, std::vector< int > &indices, const float eta=1.f, const int top_k=0)

void	NMSBoxesBatched (const std::vector< Rect > &bboxes, const std::vector< float > &scores, const std::vector< int > &class_ids, const float score_threshold, const float nms_threshold, std::vector< int > &indices, const float eta=1.f, const int top_k=0)
	Performs batched non maximum suppression on given boxes and corresponding scores across different classes. More...

void	NMSBoxesBatched (const std::vector< Rect2d > &bboxes, const std::vector< float > &scores, const std::vector< int > &class_ids, const float score_threshold, const float nms_threshold, std::vector< int > &indices, const float eta=1.f, const int top_k=0)

static int	normalize_axis (int axis, int dims)
	Converts axis from `[-dims; dims)` (similar to Python's slice notation) to `[0; dims)` range. More...

static int	normalize_axis (int axis, const MatShape &shape)

static Range	normalize_axis_range (const Range &r, int axisSize)

template<typename _Tp >
static std::ostream &	operator<< (std::ostream &out, const std::vector< _Tp > &shape)

template<typename _Tp >
static void	print (const std::vector< _Tp > &shape, const String &name="")

Net	readNet (const String &model, const String &config="", const String &framework="")
	Read deep learning network represented in one of the supported formats. More...

Net	readNet (const String &framework, const std::vector< uchar > &bufferModel, const std::vector< uchar > &bufferConfig=std::vector< uchar >())
	Read deep learning network represented in one of the supported formats. More...

Net	readNetFromCaffe (const String &prototxt, const String &caffeModel=String())
	Reads a network model stored in Caffe framework's format. More...

Net	readNetFromCaffe (const std::vector< uchar > &bufferProto, const std::vector< uchar > &bufferModel=std::vector< uchar >())
	Reads a network model stored in Caffe model in memory. More...

Net	readNetFromCaffe (const char bufferProto, size_t lenProto, const char bufferModel=NULL, size_t lenModel=0)
	Reads a network model stored in Caffe model in memory. More...

Net	readNetFromDarknet (const String &cfgFile, const String &darknetModel=String())
	Reads a network model stored in Darknet model files. More...

Net	readNetFromDarknet (const std::vector< uchar > &bufferCfg, const std::vector< uchar > &bufferModel=std::vector< uchar >())
	Reads a network model stored in Darknet model files. More...

Net	readNetFromDarknet (const char bufferCfg, size_t lenCfg, const char bufferModel=NULL, size_t lenModel=0)
	Reads a network model stored in Darknet model files. More...

Net	readNetFromModelOptimizer (const String &xml, const String &bin)
	Load a network from Intel's Model Optimizer intermediate representation. More...

Net	readNetFromModelOptimizer (const std::vector< uchar > &bufferModelConfig, const std::vector< uchar > &bufferWeights)
	Load a network from Intel's Model Optimizer intermediate representation. More...

Net	readNetFromModelOptimizer (const uchar bufferModelConfigPtr, size_t bufferModelConfigSize, const uchar bufferWeightsPtr, size_t bufferWeightsSize)
	Load a network from Intel's Model Optimizer intermediate representation. More...

Net	readNetFromONNX (const String &onnxFile)
	Reads a network model ONNX. More...

Net	readNetFromONNX (const char *buffer, size_t sizeBuffer)
	Reads a network model from ONNX in-memory buffer. More...

Net	readNetFromONNX (const std::vector< uchar > &buffer)
	Reads a network model from ONNX in-memory buffer. More...

Net	readNetFromTensorflow (const String &model, const String &config=String())
	Reads a network model stored in TensorFlow framework's format. More...

Net	readNetFromTensorflow (const std::vector< uchar > &bufferModel, const std::vector< uchar > &bufferConfig=std::vector< uchar >())
	Reads a network model stored in TensorFlow framework's format. More...

Net	readNetFromTensorflow (const char bufferModel, size_t lenModel, const char bufferConfig=NULL, size_t lenConfig=0)
	Reads a network model stored in TensorFlow framework's format. More...

Net	readNetFromTorch (const String &model, bool isBinary=true, bool evaluate=true)
	Reads a network model stored in Torch7 framework's format. More...

Mat	readTensorFromONNX (const String &path)
	Creates blob from .pb file. More...

Mat	readTorchBlob (const String &filename, bool isBinary=true)
	Loads blob which was serialized as torch.Tensor object of Torch7 framework. More...

void	releaseHDDLPlugin ()
	Release a HDDL plugin. More...

void	resetMyriadDevice ()
	Release a Myriad device (binded by OpenCV). More...

cv::String	setInferenceEngineBackendType (const cv::String &newBackendType)
	Specify Inference Engine internal backend API. More...

static MatShape	shape (const int *dims, const int n)

static MatShape	shape (const Mat &mat)

static MatShape	shape (const MatSize &sz)

static MatShape	shape (const UMat &mat)

static MatShape	shape (int a0, int a1=-1, int a2=-1, int a3=-1)

void	shrinkCaffeModel (const String &src, const String &dst, const std::vector< String > &layersTypes=std::vector< String >())
	Convert all weights of Caffe network to half precision floating point. More...

void	skipModelImport (bool skip)
	Skip model import after diagnostic run in readNet() functions. More...

static Mat	slice (const Mat &m, const _Range &r0)

static Mat	slice (const Mat &m, const _Range &r0, const _Range &r1)

static Mat	slice (const Mat &m, const _Range &r0, const _Range &r1, const _Range &r2)

static Mat	slice (const Mat &m, const _Range &r0, const _Range &r1, const _Range &r2, const _Range &r3)

void	softNMSBoxes (const std::vector< Rect > &bboxes, const std::vector< float > &scores, std::vector< float > &updated_scores, const float score_threshold, const float nms_threshold, std::vector< int > &indices, size_t top_k=0, const float sigma=0.5, SoftNMSMethod method=SoftNMSMethod::SOFTNMS_GAUSSIAN)
	Performs soft non maximum suppression given boxes and corresponding scores. Reference: https://arxiv.org/abs/1704.04503. More...

template<typename _Tp >
static std::string	toString (const std::vector< _Tp > &shape, const String &name="")

static int	total (const MatShape &shape, int start=-1, int end=-1)

static int	total (const Mat &mat, int start=-1, int end=-1)

void	writeTextGraph (const String &model, const String &output)
	Create a text representation for a binary network stored in protocol buffer format. More...

Function Documentation

◆ concat()

static MatShape cv::dnn::concat	(	const MatShape &	a,
		const MatShape &	b
	)

inlinestatic

◆ getInferenceEngineBackendType()

cv::String cv::dnn::getInferenceEngineBackendType ( )

Returns Inference Engine internal backend API.

See values of CV_DNN_BACKEND_INFERENCE_ENGINE_* macros.

OPENCV_DNN_BACKEND_INFERENCE_ENGINE_TYPE runtime parameter (environment variable) is ignored since 4.6.0.

Deprecated:

◆ getInferenceEngineCPUType()

cv::String cv::dnn::getInferenceEngineCPUType ( )

Returns Inference Engine CPU type.

Specify OpenVINO plugin: CPU or ARM.

◆ getInferenceEngineVPUType()

cv::String cv::dnn::getInferenceEngineVPUType ( )

Returns Inference Engine VPU type.

See values of CV_DNN_INFERENCE_ENGINE_VPU_TYPE_* macros.

◆ getPlane()

static Mat cv::dnn::getPlane	(	const Mat &	m,
		int	n,
		int	cn
	)

inlinestatic

◆ isAllOnes()

static bool cv::dnn::isAllOnes	(	const MatShape &	inputShape,
		int	startPos,
		int	endPos
	)

inlinestatic

◆ normalize_axis() [1/2]

static int cv::dnn::normalize_axis	(	int	axis,
		int	dims
	)

inlinestatic

Converts axis from [-dims; dims) (similar to Python's slice notation) to [0; dims) range.

◆ normalize_axis() [2/2]

static int cv::dnn::normalize_axis	(	int	axis,
		const MatShape &	shape
	)

inlinestatic

◆ normalize_axis_range()

static Range cv::dnn::normalize_axis_range	(	const Range &	r,
		int	axisSize
	)

inlinestatic

◆ operator<<()

template<typename _Tp >

static std::ostream& cv::dnn::operator<<	(	std::ostream &	out,
		const std::vector< _Tp > &	shape
	)

inlinestatic

◆ print()

template<typename _Tp >

static void cv::dnn::print	(	const std::vector< _Tp > &	shape,
		const String &	name = `""`
	)

inlinestatic

◆ releaseHDDLPlugin()

void cv::dnn::releaseHDDLPlugin ( )

Release a HDDL plugin.

◆ resetMyriadDevice()

void cv::dnn::resetMyriadDevice ( )

Release a Myriad device (binded by OpenCV).

Single Myriad device cannot be shared across multiple processes which uses Inference Engine's Myriad plugin.

◆ setInferenceEngineBackendType()

cv::String cv::dnn::setInferenceEngineBackendType ( const cv::String & newBackendType )

Specify Inference Engine internal backend API.

See values of CV_DNN_BACKEND_INFERENCE_ENGINE_* macros.

Returns: previous value of internal backend API

Deprecated:

◆ shape() [1/5]

static MatShape cv::dnn::shape	(	const int *	dims,
		const int	n
	)

inlinestatic

◆ shape() [2/5]

static MatShape cv::dnn::shape ( const Mat & mat )

inlinestatic

◆ shape() [3/5]

static MatShape cv::dnn::shape ( const MatSize & sz )

inlinestatic

◆ shape() [4/5]

static MatShape cv::dnn::shape ( const UMat & mat )

inlinestatic

◆ shape() [5/5]

static MatShape cv::dnn::shape	(	int	a0,
		int	a1 = `-1`,
		int	a2 = `-1`,
		int	a3 = `-1`
	)

inlinestatic

◆ skipModelImport()

void cv::dnn::skipModelImport ( bool skip )

Skip model import after diagnostic run in readNet() functions.

Parameters

[in] skip Indicates whether to skip the import.

This is an internal OpenCV function not intended for users.

◆ slice() [1/4]

static Mat cv::dnn::slice	(	const Mat &	m,
		const _Range &	r0
	)

inlinestatic

◆ slice() [2/4]

static Mat cv::dnn::slice	(	const Mat &	m,
		const _Range &	r0,
		const _Range &	r1
	)

inlinestatic

◆ slice() [3/4]

static Mat cv::dnn::slice	(	const Mat &	m,
		const _Range &	r0,
		const _Range &	r1,
		const _Range &	r2
	)

inlinestatic

◆ slice() [4/4]

static Mat cv::dnn::slice	(	const Mat &	m,
		const _Range &	r0,
		const _Range &	r1,
		const _Range &	r2,
		const _Range &	r3
	)

inlinestatic

◆ toString()

template<typename _Tp >

static std::string cv::dnn::toString	(	const std::vector< _Tp > &	shape,
		const String &	name = `""`
	)

inlinestatic

◆ total() [1/2]

static int cv::dnn::total	(	const MatShape &	shape,
		int	start = `-1`,
		int	end = `-1`
	)

inlinestatic

◆ total() [2/2]

static int cv::dnn::total	(	const Mat &	mat,
		int	start = `-1`,
		int	end = `-1`
	)

inlinestatic

Namespaces

Classes

Typedefs

Enumerations

Functions

Function Documentation

◆ concat()

◆ getInferenceEngineBackendType()

◆ getInferenceEngineCPUType()

◆ getInferenceEngineVPUType()

◆ getPlane()

◆ isAllOnes()

◆ normalize_axis() [1/2]

◆ normalize_axis() [2/2]

◆ normalize_axis_range()

◆ operator<<()

◆ print()

◆ releaseHDDLPlugin()

◆ resetMyriadDevice()

◆ setInferenceEngineBackendType()

◆ shape() [1/5]

◆ shape() [2/5]

◆ shape() [3/5]

◆ shape() [4/5]

◆ shape() [5/5]

◆ skipModelImport()

◆ slice() [1/4]

◆ slice() [2/4]

◆ slice() [3/4]

◆ slice() [4/4]

◆ toString()

◆ total() [1/2]

◆ total() [2/2]