OpenCV  4.0.0-pre
Open Source Computer Vision
Classes | Namespaces | Typedefs | Enumerations | Functions
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,
  cv::dnn::DNN_BACKEND_INFERENCE_ENGINE,
  cv::dnn::DNN_BACKEND_OPENCV
}
 Enum of computation backends supported by layers. More...
 
enum  cv::dnn::Target {
  cv::dnn::DNN_TARGET_CPU,
  cv::dnn::DNN_TARGET_OPENCL,
  cv::dnn::DNN_TARGET_OPENCL_FP16,
  cv::dnn::DNN_TARGET_MYRIAD
}
 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...
 
void cv::dnn::blobFromImage (InputArray image, OutputArray blob, double scalefactor=1.0, const Size &size=Size(), const Scalar &mean=Scalar(), bool swapRB=true, bool crop=true)
 Creates 4-dimensional blob from image. More...
 
Mat cv::dnn::blobFromImages (InputArrayOfArrays 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::blobFromImages (InputArrayOfArrays images, OutputArray blob, 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. More...
 
void cv::dnn::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...
 
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...
 
void cv::dnn::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)
 
Net cv::dnn::readNet (const String &model, const String &config="", const String &framework="")
 Read deep learning network represented in one of the supported formats. More...
 
Net cv::dnn::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 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 std::vector< uchar > &bufferProto, const std::vector< uchar > &bufferModel=std::vector< uchar >())
 Reads a network model stored in Caffe model in memory. 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::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 cv::dnn::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 cv::dnn::readNetFromModelOptimizer (const String &xml, const String &bin)
 Load a network from Intel's Model Optimizer intermediate representation. 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 std::vector< uchar > &bufferModel, const std::vector< uchar > &bufferConfig=std::vector< uchar >())
 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...