cv::dnn Namespace Reference

Namespaces
	details

Classes
struct	_Range
class	AbsLayer
class	ActivationLayer
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	BlankLayer
class	BNLLLayer
class	ChannelsPReLULayer
class	ConcatLayer
class	ConvolutionLayer
class	CropLayer
class	DeconvolutionLayer
class	DetectionOutputLayer
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
class	ELULayer
class	FlattenLayer
class	Importer
	Small interface class for loading trained serialized models of different dnn-frameworks. More...
class	InnerProductLayer
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	LRNLayer
class	LSTMLayer
	LSTM recurrent layer. More...
class	MaxUnpoolLayer
class	MVNLayer
class	Net
	This class allows to create and manipulate comprehensive artificial neural networks. More...
class	NormalizeBBoxLayer
class	PaddingLayer
class	PermuteLayer
class	PoolingLayer
class	PowerLayer
class	PriorBoxLayer
class	ReLULayer
class	ReshapeLayer
class	RNNLayer
	Classical recurrent layer. More...
class	ScaleLayer
class	ShiftLayer
class	SigmoidLayer
class	SliceLayer
class	SoftmaxLayer
class	SplitLayer
class	TanHLayer

Typedefs
typedef std::vector< int >	MatShape

Enumerations
enum	Backend {   DNN_BACKEND_DEFAULT,   DNN_BACKEND_HALIDE }
	Enum of computation backends supported by layers. More...
enum	Target {   DNN_TARGET_CPU,   DNN_TARGET_OPENCL }
	Enum of target devices for computations. More...

Functions
Mat	blobFromImage (const Mat &image, double scalefactor=1.0, const Size &size=Size(), const Scalar &mean=Scalar(), bool swapRB=true)
	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...
Mat	blobFromImages (const std::vector< Mat > &images, double scalefactor=1.0, Size size=Size(), const Scalar &mean=Scalar(), bool swapRB=true)
	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...
int	clamp (int ax, int dims)
int	clamp (int ax, const MatShape &shape)
static MatShape	concat (const MatShape &a, const MatShape &b)
Ptr< Importer >	createCaffeImporter (const String &prototxt, const String &caffeModel=String())
	Creates the importer of Caffe framework network. More...
Ptr< Importer >	createTensorflowImporter (const String &model)
	Creates the importer of TensorFlow framework network. More...
Ptr< Importer >	createTorchImporter (const String &filename, bool isBinary=true)
	Creates the importer of Torch7 framework network. More...
static Mat	getPlane (const Mat &m, int n, int cn)
CV__DNN_EXPERIMENTAL_NS_BEGIN std::ostream &	operator<< (std::ostream &s, cv::Range &r)
void	print (const MatShape &shape, const String &name="")
Net	readNetFromCaffe (const String &prototxt, const String &caffeModel=String())
	Reads a network model stored in Caffe model files. More...
Net	readNetFromTensorflow (const String &model)
	Reads a network model stored in Tensorflow model file. More...
Net	readNetFromTorch (const String &model, bool isBinary=true)
	Reads a network model stored in Torch model file. More...
Mat	readTorchBlob (const String &filename, bool isBinary=true)
	Loads blob which was serialized as torch.Tensor object of Torch7 framework. More...
static MatShape	shape (const int *dims, const int n=4)
static MatShape	shape (const Mat &mat)
static MatShape	shape (int a0, int a1=-1, int a2=-1, int a3=-1)
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)
static int	total (const MatShape &shape, int start=-1, int end=-1)

Function Documentation

clamp() [1/2]

int cv::dnn::clamp ( int  ax, int  dims  )

inline

clamp() [2/2]

int cv::dnn::clamp ( int  ax, const MatShape &  shape  )

inline

concat()

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

inlinestatic

getPlane()

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

inlinestatic

operator<<()

CV__DNN_EXPERIMENTAL_NS_BEGIN std::ostream& cv::dnn::operator<< ( std::ostream &  s, cv::Range &  r  )

inline

print()

void cv::dnn::print ( const MatShape &  shape, const String &  name = ""  )

inline

shape() [1/3]

static MatShape cv::dnn::shape ( const int *  dims, const int  n = 4  )

inlinestatic

shape() [2/3]

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

inlinestatic

shape() [3/3]

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

inlinestatic

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

total()

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

inlinestatic