OpenCV  3.2.0
Open Source Computer Vision
Classes
Partial List of Implemented Layers

Classes

class  cv::dnn::AbsLayer
 
class  cv::dnn::BaseConvolutionLayer
 
class  cv::dnn::BNLLLayer
 
class  cv::dnn::ConcatLayer
 
class  cv::dnn::ConvolutionLayer
 
class  cv::dnn::CropLayer
 
class  cv::dnn::DeconvolutionLayer
 
class  cv::dnn::EltwiseLayer
 
class  cv::dnn::InnerProductLayer
 
class  cv::dnn::LRNLayer
 
class  cv::dnn::LSTMLayer
 LSTM recurrent layer. More...
 
class  cv::dnn::MVNLayer
 
class  cv::dnn::PoolingLayer
 
class  cv::dnn::PowerLayer
 
class  cv::dnn::ReLULayer
 
class  cv::dnn::ReshapeLayer
 
class  cv::dnn::RNNLayer
 Classical recurrent layer. More...
 
class  cv::dnn::SigmoidLayer
 
class  cv::dnn::SliceLayer
 
class  cv::dnn::SoftmaxLayer
 
class  cv::dnn::SplitLayer
 
class  cv::dnn::TanHLayer
 

Detailed Description

This subsection of dnn module contains information about bult-in layers and their descriptions.

Classes listed here, in fact, provides C++ API for creating intances of bult-in layers. In addition to this way of layers instantiation, there is a more common factory API (see Utilities for New Layers Registration), it allows to create layers dynamically (by name) and register new ones. You can use both API, but factory API is less convinient for native C++ programming and basically designed for use inside importers (see Importer, createCaffeImporter(), createTorchImporter()).

Bult-in layers partially reproduce functionality of corresponding Caffe and Torch7 layers. In partuclar, the following layers and Caffe Importer were tested to reproduce Caffe functionality: