dnn.hpp File Reference

#include <vector>
#include <opencv2/core.hpp>
#include <opencv2/dnn/dict.hpp>
#include <opencv2/dnn/layer.hpp>
#include <opencv2/dnn/dnn.inl.hpp>

Classes
class	cv::dnn::BackendNode
	Derivatives of this class encapsulates functions of certain backends. More...
class	cv::dnn::BackendWrapper
	Derivatives of this class wraps cv::Mat for different backends and targets. More...
class	cv::dnn::Layer
	This interface class allows to build new Layers - are building blocks of networks. More...
class	cv::dnn::LayerParams
	This class provides all data needed to initialize layer. More...
class	cv::dnn::Net
	This class allows to create and manipulate comprehensive artificial neural networks. More...

Namespaces
	cv
	cv::dnn

Typedefs
typedef std::vector< int >	cv::dnn::MatShape

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

Functions
Mat	cv::dnn::blobFromImage (InputArray image, double scalefactor=1.0, const Size &size=Size(), const Scalar &mean=Scalar(), bool swapRB=true, bool crop=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	cv::dnn::blobFromImages (const std::vector< Mat > &images, double scalefactor=1.0, Size size=Size(), const Scalar &mean=Scalar(), bool swapRB=true, bool crop=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...
void	cv::dnn::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...
Net	cv::dnn::readNetFromCaffe (const String &prototxt, const String &caffeModel=String())
	Reads a network model stored in Caffe framework's format. More...
Net	cv::dnn::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	cv::dnn::readNetFromDarknet (const String &cfgFile, const String &darknetModel=String())
	Reads a network model stored in Darknet model files. More...
Net	cv::dnn::readNetFromTensorflow (const String &model, const String &config=String())
	Reads a network model stored in TensorFlow framework's format. More...
Net	cv::dnn::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	cv::dnn::readNetFromTorch (const String &model, bool isBinary=true)
	Reads a network model stored in Torch7 framework's format. More...
Mat	cv::dnn::readTorchBlob (const String &filename, bool isBinary=true)
	Loads blob which was serialized as torch.Tensor object of Torch7 framework. More...
void	cv::dnn::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...