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411 lines
14 KiB
C++
411 lines
14 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// @Authors
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// Dachuan Zhao, dachuan@multicorewareinc.com
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// Yao Wang, bitwangyaoyao@gmail.com
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// Nathan, liujun@multicorewareinc.com
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other oclMaterials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "precomp.hpp"
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using namespace std;
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using namespace cv;
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using namespace cv::ocl;
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namespace cv
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{
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namespace ocl
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{
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///////////////////////////OpenCL kernel strings///////////////////////////
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extern const char *pyrlk;
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extern const char *pyrlk_no_image;
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extern const char *arithm_mul;
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}
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}
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struct dim3
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{
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unsigned int x, y, z;
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};
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struct float2
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{
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float x, y;
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};
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struct int2
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{
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int x, y;
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};
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namespace
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{
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void calcPatchSize(cv::Size winSize, int cn, dim3 &block, dim3 &patch, bool isDeviceArch11)
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{
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winSize.width *= cn;
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if (winSize.width > 32 && winSize.width > 2 * winSize.height)
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{
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block.x = isDeviceArch11 ? 16 : 32;
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block.y = 8;
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}
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else
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{
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block.x = 16;
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block.y = isDeviceArch11 ? 8 : 16;
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}
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patch.x = (winSize.width + block.x - 1) / block.x;
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patch.y = (winSize.height + block.y - 1) / block.y;
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block.z = patch.z = 1;
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}
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}
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static void multiply_cus(const oclMat &src1, oclMat &dst, float scalar)
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{
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if(!src1.clCxt->supportsFeature(Context::CL_DOUBLE) && src1.type() == CV_64F)
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{
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CV_Error(CV_GpuNotSupported, "Selected device don't support double\r\n");
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return;
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}
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CV_Assert(src1.cols == dst.cols &&
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src1.rows == dst.rows);
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CV_Assert(src1.type() == dst.type());
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CV_Assert(src1.depth() != CV_8S);
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Context *clCxt = src1.clCxt;
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size_t localThreads[3] = { 16, 16, 1 };
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size_t globalThreads[3] = { src1.cols,
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src1.rows,
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1
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};
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int dst_step1 = dst.cols * dst.elemSize();
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vector<pair<size_t , const void *> > args;
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args.push_back( make_pair( sizeof(cl_mem), (void *)&src1.data ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&src1.step ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&src1.offset ));
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args.push_back( make_pair( sizeof(cl_mem), (void *)&dst.data ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&dst.step ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&dst.offset ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&src1.rows ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&src1.cols ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&dst_step1 ));
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args.push_back( make_pair( sizeof(float), (float *)&scalar ));
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openCLExecuteKernel(clCxt, &arithm_mul, "arithm_muls", globalThreads, localThreads, args, -1, src1.depth());
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}
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static void lkSparse_run(oclMat &I, oclMat &J,
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const oclMat &prevPts, oclMat &nextPts, oclMat &status, oclMat& err, bool /*GET_MIN_EIGENVALS*/, int ptcount,
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int level, dim3 patch, Size winSize, int iters)
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{
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Context *clCxt = I.clCxt;
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int elemCntPerRow = I.step / I.elemSize();
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string kernelName = "lkSparse";
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bool isImageSupported = support_image2d();
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size_t localThreads[3] = { 8, isImageSupported ? 8 : 32, 1 };
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size_t globalThreads[3] = { 8 * ptcount, isImageSupported ? 8 : 32, 1};
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int cn = I.oclchannels();
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char calcErr;
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if (level == 0)
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{
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calcErr = 1;
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}
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else
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{
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calcErr = 0;
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}
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vector<pair<size_t , const void *> > args;
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cl_mem ITex = isImageSupported ? bindTexture(I) : (cl_mem)I.data;
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cl_mem JTex = isImageSupported ? bindTexture(J) : (cl_mem)J.data;
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args.push_back( make_pair( sizeof(cl_mem), (void *)&ITex ));
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args.push_back( make_pair( sizeof(cl_mem), (void *)&JTex ));
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args.push_back( make_pair( sizeof(cl_mem), (void *)&prevPts.data ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&prevPts.step ));
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args.push_back( make_pair( sizeof(cl_mem), (void *)&nextPts.data ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&nextPts.step ));
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args.push_back( make_pair( sizeof(cl_mem), (void *)&status.data ));
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args.push_back( make_pair( sizeof(cl_mem), (void *)&err.data ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&level ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&I.rows ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&I.cols ));
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if (!isImageSupported)
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args.push_back( make_pair( sizeof(cl_int), (void *)&elemCntPerRow ) );
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args.push_back( make_pair( sizeof(cl_int), (void *)&patch.x ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&patch.y ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&cn ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&winSize.width ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&winSize.height ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&iters ));
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args.push_back( make_pair( sizeof(cl_char), (void *)&calcErr ));
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bool is_cpu = queryDeviceInfo<IS_CPU_DEVICE, bool>();
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if (is_cpu)
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{
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openCLExecuteKernel(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth(), (char*)" -D CPU");
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releaseTexture(ITex);
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releaseTexture(JTex);
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}
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else
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{
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if(isImageSupported)
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{
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openCLExecuteKernel(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth());
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releaseTexture(ITex);
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releaseTexture(JTex);
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}
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else
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{
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openCLExecuteKernel(clCxt, &pyrlk_no_image, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth());
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}
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}
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}
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void cv::ocl::PyrLKOpticalFlow::sparse(const oclMat &prevImg, const oclMat &nextImg, const oclMat &prevPts, oclMat &nextPts, oclMat &status, oclMat *err)
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{
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if (prevPts.empty())
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{
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nextPts.release();
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status.release();
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if (err) err->release();
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return;
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}
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derivLambda = std::min(std::max(derivLambda, 0.0), 1.0);
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iters = std::min(std::max(iters, 0), 100);
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const int cn = prevImg.oclchannels();
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dim3 block, patch;
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calcPatchSize(winSize, cn, block, patch, isDeviceArch11_);
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CV_Assert(derivLambda >= 0);
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CV_Assert(maxLevel >= 0 && winSize.width > 2 && winSize.height > 2);
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CV_Assert(prevImg.size() == nextImg.size() && prevImg.type() == nextImg.type());
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CV_Assert(patch.x > 0 && patch.x < 6 && patch.y > 0 && patch.y < 6);
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CV_Assert(prevPts.rows == 1 && prevPts.type() == CV_32FC2);
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if (useInitialFlow)
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CV_Assert(nextPts.size() == prevPts.size() && nextPts.type() == CV_32FC2);
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else
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ensureSizeIsEnough(1, prevPts.cols, prevPts.type(), nextPts);
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oclMat temp1 = (useInitialFlow ? nextPts : prevPts).reshape(1);
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oclMat temp2 = nextPts.reshape(1);
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multiply_cus(temp1, temp2, 1.0f / (1 << maxLevel) / 2.0f);
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//::multiply(temp1, 1.0f / (1 << maxLevel) / 2.0f, temp2);
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ensureSizeIsEnough(1, prevPts.cols, CV_8UC1, status);
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status.setTo(Scalar::all(1));
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bool errMat = false;
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if (!err)
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{
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err = new oclMat(1, prevPts.cols, CV_32FC1);
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errMat = true;
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}
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else
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ensureSizeIsEnough(1, prevPts.cols, CV_32FC1, *err);
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// build the image pyramids.
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prevPyr_.resize(maxLevel + 1);
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nextPyr_.resize(maxLevel + 1);
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if (cn == 1 || cn == 4)
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{
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prevImg.convertTo(prevPyr_[0], CV_32F);
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nextImg.convertTo(nextPyr_[0], CV_32F);
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}
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for (int level = 1; level <= maxLevel; ++level)
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{
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pyrDown(prevPyr_[level - 1], prevPyr_[level]);
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pyrDown(nextPyr_[level - 1], nextPyr_[level]);
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}
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// dI/dx ~ Ix, dI/dy ~ Iy
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for (int level = maxLevel; level >= 0; level--)
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{
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lkSparse_run(prevPyr_[level], nextPyr_[level],
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prevPts, nextPts, status, *err, getMinEigenVals, prevPts.cols,
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level, patch, winSize, iters);
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}
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if(errMat)
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delete err;
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}
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static void lkDense_run(oclMat &I, oclMat &J, oclMat &u, oclMat &v,
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oclMat &prevU, oclMat &prevV, oclMat *err, Size winSize, int iters)
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{
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Context *clCxt = I.clCxt;
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bool isImageSupported = support_image2d();
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int elemCntPerRow = I.step / I.elemSize();
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string kernelName = "lkDense";
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size_t localThreads[3] = { 16, 16, 1 };
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size_t globalThreads[3] = { I.cols, I.rows, 1};
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bool calcErr;
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if (err)
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{
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calcErr = true;
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}
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else
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{
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calcErr = false;
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}
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cl_mem ITex;
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cl_mem JTex;
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if (isImageSupported)
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{
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ITex = bindTexture(I);
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JTex = bindTexture(J);
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}
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else
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{
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ITex = (cl_mem)I.data;
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JTex = (cl_mem)J.data;
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}
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vector<pair<size_t , const void *> > args;
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args.push_back( make_pair( sizeof(cl_mem), (void *)&ITex ));
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args.push_back( make_pair( sizeof(cl_mem), (void *)&JTex ));
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args.push_back( make_pair( sizeof(cl_mem), (void *)&u.data ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&u.step ));
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args.push_back( make_pair( sizeof(cl_mem), (void *)&v.data ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&v.step ));
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args.push_back( make_pair( sizeof(cl_mem), (void *)&prevU.data ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&prevU.step ));
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args.push_back( make_pair( sizeof(cl_mem), (void *)&prevV.data ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&prevV.step ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&I.rows ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&I.cols ));
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//args.push_back( make_pair( sizeof(cl_mem), (void *)&(*err).data ));
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//args.push_back( make_pair( sizeof(cl_int), (void *)&(*err).step ));
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if (!isImageSupported)
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{
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args.push_back( make_pair( sizeof(cl_int), (void *)&elemCntPerRow ) );
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}
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args.push_back( make_pair( sizeof(cl_int), (void *)&winSize.width ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&winSize.height ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&iters ));
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args.push_back( make_pair( sizeof(cl_char), (void *)&calcErr ));
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if (isImageSupported)
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{
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openCLExecuteKernel(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth());
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releaseTexture(ITex);
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releaseTexture(JTex);
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}
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else
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{
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openCLExecuteKernel(clCxt, &pyrlk_no_image, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth());
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}
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}
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void cv::ocl::PyrLKOpticalFlow::dense(const oclMat &prevImg, const oclMat &nextImg, oclMat &u, oclMat &v, oclMat *err)
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{
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CV_Assert(prevImg.type() == CV_8UC1);
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CV_Assert(prevImg.size() == nextImg.size() && prevImg.type() == nextImg.type());
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CV_Assert(maxLevel >= 0);
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CV_Assert(winSize.width > 2 && winSize.height > 2);
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if (err)
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err->create(prevImg.size(), CV_32FC1);
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prevPyr_.resize(maxLevel + 1);
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nextPyr_.resize(maxLevel + 1);
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prevPyr_[0] = prevImg;
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nextImg.convertTo(nextPyr_[0], CV_32F);
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for (int level = 1; level <= maxLevel; ++level)
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{
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pyrDown(prevPyr_[level - 1], prevPyr_[level]);
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pyrDown(nextPyr_[level - 1], nextPyr_[level]);
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}
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ensureSizeIsEnough(prevImg.size(), CV_32FC1, uPyr_[0]);
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ensureSizeIsEnough(prevImg.size(), CV_32FC1, vPyr_[0]);
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ensureSizeIsEnough(prevImg.size(), CV_32FC1, uPyr_[1]);
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ensureSizeIsEnough(prevImg.size(), CV_32FC1, vPyr_[1]);
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uPyr_[1].setTo(Scalar::all(0));
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vPyr_[1].setTo(Scalar::all(0));
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Size winSize2i(winSize.width, winSize.height);
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int idx = 0;
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for (int level = maxLevel; level >= 0; level--)
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{
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int idx2 = (idx + 1) & 1;
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lkDense_run(prevPyr_[level], nextPyr_[level], uPyr_[idx], vPyr_[idx], uPyr_[idx2], vPyr_[idx2],
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level == 0 ? err : 0, winSize2i, iters);
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if (level > 0)
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idx = idx2;
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}
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uPyr_[idx].copyTo(u);
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vPyr_[idx].copyTo(v);
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}
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