cv::dnn Namespace Reference

This namespace is used for dnn module functionlaity. More...

Classes
class	_LayerStaticRegisterer
struct	_Range
class	AbsLayer
class	BaseConvolutionLayer
class	Blob
	This class provides methods for continuous n-dimensional CPU and GPU array processing. More...
struct	BlobShape
	Lightweight class for storing and processing a shape of blob (or anything else). More...
class	BNLLLayer
class	ConcatLayer
class	ConvolutionLayer
class	CropLayer
class	DeconvolutionLayer
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	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	MVNLayer
class	Net
	This class allows to create and manipulate comprehensive artificial neural networks. More...
class	PoolingLayer
class	PowerLayer
class	ReLULayer
class	ReshapeLayer
class	RNNLayer
	Classical recurrent layer. More...
class	SigmoidLayer
class	SliceLayer
class	SoftmaxLayer
class	SplitLayer
class	TanHLayer

Typedefs
typedef BlobShape	Shape

Functions
template<typename LayerClass >
Ptr< Layer >	_layerDynamicRegisterer (LayerParams &params)
BlobShape	computeShapeByReshapeMask (const BlobShape &srcShape, const BlobShape &maskShape, Range srcRange=Range::all())
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...
void	initModule ()
	Initialize dnn module and built-in layers. More...
std::ostream &	operator<< (std::ostream &s, cv::Range &r)
Net	readNetFromCaffe (const String &prototxt, const String &caffeModel=String())
	Reads a network model stored in Caffe model files. More...
Blob	readTorchBlob (const String &filename, bool isBinary=true)
	Loads blob which was serialized as torch.Tensor object of Torch7 framework. More...
template<typename Mat >
void	reshape (Mat &m, const BlobShape &shape)
template<typename Mat >
Mat	reshaped (const Mat &m, const BlobShape &shape)
template<typename Mat >
Mat	slice (const Mat &m, const _Range &r0)
template<typename Mat >
Mat	slice (const Mat &m, const _Range &r0, const _Range &r1)
template<typename Mat >
Mat	slice (const Mat &m, const _Range &r0, const _Range &r1, const _Range &r2)
template<typename Mat >
Mat	slice (const Mat &m, const _Range &r0, const _Range &r1, const _Range &r2, const _Range &r3)

Detailed Description

This namespace is used for dnn module functionlaity.

Typedef Documentation

Shape

typedef BlobShape cv::dnn::Shape

Function Documentation

_layerDynamicRegisterer()

template<typename LayerClass >

Ptr<Layer> cv::dnn::_layerDynamicRegisterer

(

LayerParams &

params

)

computeShapeByReshapeMask()

BlobShape cv::dnn::computeShapeByReshapeMask	(	const BlobShape &	srcShape,
		const BlobShape &	maskShape,
		Range	srcRange = Range::all()
	)

operator<<()

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

reshape()

template<typename Mat >

void cv::dnn::reshape	(	Mat &	m,
		const BlobShape &	shape
	)

reshaped()

template<typename Mat >

Mat cv::dnn::reshaped	(	const Mat &	m,
		const BlobShape &	shape
	)

slice() [1/4]

template<typename Mat >

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

slice() [2/4]

template<typename Mat >

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

slice() [3/4]

template<typename Mat >

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

slice() [4/4]

template<typename Mat >

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