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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_DNN_LAYERS_CONVOLUTION_LAYER_HPP__
#define __OPENCV_DNN_LAYERS_CONVOLUTION_LAYER_HPP__
#include "../precomp.hpp"
#include <opencv2/dnn/all_layers.hpp>
namespace cv
{
namespace dnn
{
class BaseConvolutionLayerImpl : public ConvolutionLayer
{
public:
BaseConvolutionLayerImpl();
virtual void allocate(const std::vector<Blob*> &inputs, std::vector<Blob> &outputs);
protected:
void init();
virtual void computeInpOutShape(const Blob &inpBlob) = 0;
bool is1x1() const;
int numOutput, group;
int inpH, inpW, inpCn;
int outH, outW, outCn;
int inpGroupCn, outGroupCn;
int ksize;
BlobShape colRowBlobShape;
bool bias;
bool tryUseOpenCL, useOpenCL;
Blob colRowBlob, biasOnesBlob;
};
//TODO: simultaneously convolution and bias addition for cache optimization
class ConvolutionLayerImpl : public BaseConvolutionLayerImpl
{
public:
virtual void forward(std::vector<Blob*> &inputs, std::vector<Blob> &outputs);
protected:
virtual void computeInpOutShape(const Blob &inpBlob);
template<typename XMat>
void forward_(std::vector<Blob*> &inputs, std::vector<Blob> &outputs);
void im2col(const Mat &srcImg, Mat &dstCol);
void im2row(const Mat &srcImg, Mat &dstRow);
void im2col(const UMat &srcImg, UMat &dstCol);
void im2row(const UMat &srcImg, UMat &dstCol);
};
class DeConvolutionLayerImpl : public BaseConvolutionLayerImpl
{
public:
virtual void forward(std::vector<Blob*> &inputs, std::vector<Blob> &outputs);
protected:
virtual void computeInpOutShape(const Blob &inpBlob);
template<typename XMat>
void forward_(std::vector<Blob*> &inputs, std::vector<Blob> &outputs);
void col2im(const Mat &colMat, Mat &dstImg);
void col2im(const UMat &colMat, UMat &dstImg);
};
//Importers
Ptr<Layer> createConvolutionLayerFromCaffe(LayerParams ¶ms);
Ptr<Layer> createDeconvolutionLayerFromCaffe(LayerParams ¶ms);
}
}
#endif