/*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) 2010-2012, Multicoreware, Inc., all rights reserved. // Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // @Authors // Peng Xiao, pengxiao@multicorewareinc.com // // 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 oclMaterials 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*/ #include #include "precomp.hpp" using namespace cv; using namespace cv::ocl; //helper routines namespace cv { namespace ocl { ///////////////////////////OpenCL kernel strings/////////////////////////// extern const char *match_template; } } namespace cv { namespace ocl { void matchTemplate_SQDIFF( const oclMat &image, const oclMat &templ, oclMat &result, MatchTemplateBuf &buf); void matchTemplate_SQDIFF_NORMED( const oclMat &image, const oclMat &templ, oclMat &result, MatchTemplateBuf &buf); void convolve_32F( const oclMat &image, const oclMat &templ, oclMat &result, MatchTemplateBuf &buf); void matchTemplate_CCORR( const oclMat &image, const oclMat &templ, oclMat &result, MatchTemplateBuf &buf); void matchTemplate_CCORR_NORMED( const oclMat &image, const oclMat &templ, oclMat &result, MatchTemplateBuf &buf); void matchTemplate_CCOFF( const oclMat &image, const oclMat &templ, oclMat &result, MatchTemplateBuf &buf); void matchTemplate_CCOFF_NORMED( const oclMat &image, const oclMat &templ, oclMat &result, MatchTemplateBuf &buf); void matchTemplateNaive_SQDIFF( const oclMat &image, const oclMat &templ, oclMat &result, int cn); void matchTemplateNaive_CCORR( const oclMat &image, const oclMat &templ, oclMat &result, int cn); void extractFirstChannel_32F( const oclMat &image, oclMat &result); // Evaluates optimal template's area threshold. If // template's area is less than the threshold, we use naive match // template version, otherwise FFT-based (if available) static bool useNaive(int method, int depth, Size size) { #ifdef HAVE_CLAMDFFT if (method == TM_SQDIFF && (depth == CV_32F || !Context::getContext()->supportsFeature(Context::CL_DOUBLE))) { return true; } else if(method == TM_CCORR || (method == TM_SQDIFF && depth == CV_8U)) { return size.height < 18 && size.width < 18; } else return false; #else #define UNUSED(x) (void)(x); UNUSED(method) UNUSED(depth) UNUSED(size) #undef UNUSED return true; #endif } ////////////////////////////////////////////////////////////////////// // SQDIFF void matchTemplate_SQDIFF( const oclMat &image, const oclMat &templ, oclMat &result, MatchTemplateBuf & buf) { result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F); if (useNaive(TM_SQDIFF, image.depth(), templ.size())) { matchTemplateNaive_SQDIFF(image, templ, result, image.oclchannels()); return; } else { buf.image_sqsums.resize(1); // TODO, add double support for ocl::integral // use CPU integral temporarily Mat sums, sqsums; cv::integral(Mat(image.reshape(1)), sums, sqsums); buf.image_sqsums[0] = sqsums; unsigned long long templ_sqsum = (unsigned long long)sqrSum(templ.reshape(1))[0]; matchTemplate_CCORR(image, templ, result, buf); //port CUDA's matchTemplatePrepared_SQDIFF_8U Context *clCxt = image.clCxt; String kernelName = "matchTemplate_Prepared_SQDIFF"; std::vector< std::pair > args; args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sqsums[0].data)); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&result.data)); args.push_back( std::make_pair( sizeof(cl_ulong), (void *)&templ_sqsum)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.rows)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.cols)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.rows)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.cols)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sqsums[0].offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sqsums[0].step)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.step)); size_t globalThreads[3] = {result.cols, result.rows, 1}; size_t localThreads[3] = {16, 16, 1}; const char * build_opt = image.oclchannels() == 4 ? "-D CN4" : ""; openCLExecuteKernel(clCxt, &match_template, kernelName, globalThreads, localThreads, args, 1, CV_8U, build_opt); } } void matchTemplate_SQDIFF_NORMED( const oclMat &image, const oclMat &templ, oclMat &result, MatchTemplateBuf &buf) { matchTemplate_CCORR(image, templ, result, buf); buf.image_sums.resize(1); integral(image.reshape(1), buf.image_sums[0]); unsigned long long templ_sqsum = (unsigned long long)sqrSum(templ.reshape(1))[0]; Context *clCxt = image.clCxt; String kernelName = "matchTemplate_Prepared_SQDIFF_NORMED"; std::vector< std::pair > args; args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sums[0].data)); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&result.data)); args.push_back( std::make_pair( sizeof(cl_ulong), (void *)&templ_sqsum)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.rows)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.cols)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.rows)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.cols)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sums[0].offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sums[0].step)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.step)); size_t globalThreads[3] = {result.cols, result.rows, 1}; size_t localThreads[3] = {16, 16, 1}; openCLExecuteKernel(clCxt, &match_template, kernelName, globalThreads, localThreads, args, 1, CV_8U); } void matchTemplateNaive_SQDIFF( const oclMat &image, const oclMat &templ, oclMat &result, int) { CV_Assert((image.depth() == CV_8U && templ.depth() == CV_8U ) || ((image.depth() == CV_32F && templ.depth() == CV_32F) && result.depth() == CV_32F) ); CV_Assert(image.oclchannels() == templ.oclchannels() && (image.oclchannels() == 1 || image.oclchannels() == 4) && result.oclchannels() == 1); CV_Assert(result.rows == image.rows - templ.rows + 1 && result.cols == image.cols - templ.cols + 1); Context *clCxt = image.clCxt; String kernelName = "matchTemplate_Naive_SQDIFF"; std::vector< std::pair > args; args.push_back( std::make_pair( sizeof(cl_mem), (void *)&image.data)); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&templ.data)); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&result.data)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&image.rows)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&image.cols)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.rows)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.cols)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.rows)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.cols)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&image.offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&image.step)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.step)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.step)); size_t globalThreads[3] = {result.cols, result.rows, 1}; size_t localThreads[3] = {16, 16, 1}; openCLExecuteKernel(clCxt, &match_template, kernelName, globalThreads, localThreads, args, image.oclchannels(), image.depth()); } ////////////////////////////////////////////////////////////////////// // CCORR void convolve_32F( const oclMat &image, const oclMat &templ, oclMat &result, MatchTemplateBuf &buf) { ConvolveBuf convolve_buf; convolve_buf.user_block_size = buf.user_block_size; if (image.oclchannels() == 1) convolve(image, templ, result, true, convolve_buf); else { oclMat result_; convolve(image.reshape(1), templ.reshape(1), result_, true, convolve_buf); extractFirstChannel_32F(result_, result); } } void matchTemplate_CCORR( const oclMat &image, const oclMat &templ, oclMat &result, MatchTemplateBuf &buf) { result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F); if (useNaive(TM_CCORR, image.depth(), templ.size())) { matchTemplateNaive_CCORR(image, templ, result, image.oclchannels()); return; } else { if(image.depth() == CV_8U && templ.depth() == CV_8U) { image.convertTo(buf.imagef, CV_32F); templ.convertTo(buf.templf, CV_32F); convolve_32F(buf.imagef, buf.templf, result, buf); } else { convolve_32F(image, templ, result, buf); } } } void matchTemplate_CCORR_NORMED( const oclMat &image, const oclMat &templ, oclMat &result, MatchTemplateBuf &buf) { matchTemplate_CCORR(image, templ, result, buf); buf.image_sums.resize(1); buf.image_sqsums.resize(1); integral(image.reshape(1), buf.image_sums[0], buf.image_sqsums[0]); unsigned long long templ_sqsum = (unsigned long long)sqrSum(templ.reshape(1))[0]; Context *clCxt = image.clCxt; String kernelName = "normalizeKernel"; std::vector< std::pair > args; args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sqsums[0].data)); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&result.data)); args.push_back( std::make_pair( sizeof(cl_ulong), (void *)&templ_sqsum)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.rows)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.cols)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.rows)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.cols)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sqsums[0].offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sqsums[0].step)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.step)); size_t globalThreads[3] = {result.cols, result.rows, 1}; size_t localThreads[3] = {16, 16, 1}; openCLExecuteKernel(clCxt, &match_template, kernelName, globalThreads, localThreads, args, 1, CV_8U); } void matchTemplateNaive_CCORR( const oclMat &image, const oclMat &templ, oclMat &result, int) { CV_Assert((image.depth() == CV_8U && templ.depth() == CV_8U ) || ((image.depth() == CV_32F && templ.depth() == CV_32F) && result.depth() == CV_32F) ); CV_Assert(image.oclchannels() == templ.oclchannels() && (image.oclchannels() == 1 || image.oclchannels() == 4) && result.oclchannels() == 1); CV_Assert(result.rows == image.rows - templ.rows + 1 && result.cols == image.cols - templ.cols + 1); Context *clCxt = image.clCxt; String kernelName = "matchTemplate_Naive_CCORR"; std::vector< std::pair > args; args.push_back( std::make_pair( sizeof(cl_mem), (void *)&image.data)); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&templ.data)); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&result.data)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&image.rows)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&image.cols)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.rows)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.cols)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.rows)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.cols)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&image.offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&image.step)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.step)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.step)); size_t globalThreads[3] = {result.cols, result.rows, 1}; size_t localThreads[3] = {16, 16, 1}; openCLExecuteKernel(clCxt, &match_template, kernelName, globalThreads, localThreads, args, image.oclchannels(), image.depth()); } ////////////////////////////////////////////////////////////////////// // CCOFF void matchTemplate_CCOFF( const oclMat &image, const oclMat &templ, oclMat &result, MatchTemplateBuf &buf) { CV_Assert(image.depth() == CV_8U && templ.depth() == CV_8U); matchTemplate_CCORR(image, templ, result, buf); Context *clCxt = image.clCxt; String kernelName; kernelName = "matchTemplate_Prepared_CCOFF"; size_t globalThreads[3] = {result.cols, result.rows, 1}; size_t localThreads[3] = {16, 16, 1}; std::vector< std::pair > args; args.push_back( std::make_pair( sizeof(cl_mem), (void *)&result.data) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&image.rows) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&image.cols) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.rows) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.cols) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.rows) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.cols) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.step)); Vec4f templ_sum = Vec4f::all(0); // to be continued in the following section if(image.oclchannels() == 1) { buf.image_sums.resize(1); integral(image, buf.image_sums[0]); templ_sum[0] = (float)sum(templ)[0] / templ.size().area(); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sums[0].data) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sums[0].offset) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sums[0].step) ); args.push_back( std::make_pair( sizeof(cl_float), (void *)&templ_sum[0]) ); } else { split(image, buf.images); templ_sum = sum(templ) / templ.size().area(); buf.image_sums.resize(buf.images.size()); for(int i = 0; i < image.oclchannels(); i ++) { integral(buf.images[i], buf.image_sums[i]); } switch(image.oclchannels()) { case 4: args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sums[0].data) ); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sums[1].data) ); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sums[2].data) ); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sums[3].data) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sums[0].offset) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sums[0].step) ); args.push_back( std::make_pair( sizeof(cl_float), (void *)&templ_sum[0]) ); args.push_back( std::make_pair( sizeof(cl_float), (void *)&templ_sum[1]) ); args.push_back( std::make_pair( sizeof(cl_float), (void *)&templ_sum[2]) ); args.push_back( std::make_pair( sizeof(cl_float), (void *)&templ_sum[3]) ); break; default: CV_Error(CV_StsBadArg, "matchTemplate: unsupported number of channels"); break; } } openCLExecuteKernel(clCxt, &match_template, kernelName, globalThreads, localThreads, args, image.oclchannels(), image.depth()); } void matchTemplate_CCOFF_NORMED( const oclMat &image, const oclMat &templ, oclMat &result, MatchTemplateBuf &buf) { image.convertTo(buf.imagef, CV_32F); templ.convertTo(buf.templf, CV_32F); matchTemplate_CCORR(buf.imagef, buf.templf, result, buf); float scale = 1.f / templ.size().area(); Context *clCxt = image.clCxt; String kernelName; kernelName = "matchTemplate_Prepared_CCOFF_NORMED"; size_t globalThreads[3] = {result.cols, result.rows, 1}; size_t localThreads[3] = {16, 16, 1}; std::vector< std::pair > args; args.push_back( std::make_pair( sizeof(cl_mem), (void *)&result.data) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&image.rows) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&image.cols) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.rows) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&templ.cols) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.rows) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.cols) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.step)); args.push_back( std::make_pair( sizeof(cl_float), (void *)&scale) ); Vec4f templ_sum = Vec4f::all(0); Vec4f templ_sqsum = Vec4f::all(0); // to be continued in the following section if(image.oclchannels() == 1) { buf.image_sums.resize(1); buf.image_sqsums.resize(1); integral(image, buf.image_sums[0], buf.image_sqsums[0]); templ_sum[0] = (float)sum(templ)[0]; templ_sqsum[0] = sqrSum(templ)[0]; templ_sqsum[0] -= scale * templ_sum[0] * templ_sum[0]; templ_sum[0] *= scale; args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sums[0].data) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sums[0].offset) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sums[0].step) ); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sqsums[0].data) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sqsums[0].offset) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sqsums[0].step) ); args.push_back( std::make_pair( sizeof(cl_float), (void *)&templ_sum[0]) ); args.push_back( std::make_pair( sizeof(cl_float), (void *)&templ_sqsum[0]) ); } else { split(image, buf.images); templ_sum = sum(templ); templ_sqsum = sqrSum(templ); templ_sqsum -= scale * templ_sum * templ_sum; float templ_sqsum_sum = 0; for(int i = 0; i < image.oclchannels(); i ++) { templ_sqsum_sum += templ_sqsum[i] - scale * templ_sum[i] * templ_sum[i]; } templ_sum *= scale; buf.image_sums.resize(buf.images.size()); buf.image_sqsums.resize(buf.images.size()); for(int i = 0; i < image.oclchannels(); i ++) { integral(buf.images[i], buf.image_sums[i], buf.image_sqsums[i]); } switch(image.oclchannels()) { case 4: args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sums[0].data) ); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sums[1].data) ); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sums[2].data) ); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sums[3].data) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sums[0].offset) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sums[0].step) ); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sqsums[0].data) ); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sqsums[1].data) ); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sqsums[2].data) ); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&buf.image_sqsums[3].data) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sqsums[0].offset) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&buf.image_sqsums[0].step) ); args.push_back( std::make_pair( sizeof(cl_float), (void *)&templ_sum[0]) ); args.push_back( std::make_pair( sizeof(cl_float), (void *)&templ_sum[1]) ); args.push_back( std::make_pair( sizeof(cl_float), (void *)&templ_sum[2]) ); args.push_back( std::make_pair( sizeof(cl_float), (void *)&templ_sum[3]) ); args.push_back( std::make_pair( sizeof(cl_float), (void *)&templ_sqsum_sum) ); break; default: CV_Error(CV_StsBadArg, "matchTemplate: unsupported number of channels"); break; } } openCLExecuteKernel(clCxt, &match_template, kernelName, globalThreads, localThreads, args, image.oclchannels(), image.depth()); } void extractFirstChannel_32F(const oclMat &image, oclMat &result) { Context *clCxt = image.clCxt; String kernelName; kernelName = "extractFirstChannel"; size_t globalThreads[3] = {result.cols, result.rows, 1}; size_t localThreads[3] = {16, 16, 1}; std::vector< std::pair > args; args.push_back( std::make_pair( sizeof(cl_mem), (void *)&image.data) ); args.push_back( std::make_pair( sizeof(cl_mem), (void *)&result.data) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.rows) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.cols) ); args.push_back( std::make_pair( sizeof(cl_int), (void *)&image.offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.offset)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&image.step)); args.push_back( std::make_pair( sizeof(cl_int), (void *)&result.step)); openCLExecuteKernel(clCxt, &match_template, kernelName, globalThreads, localThreads, args, -1, -1); } }/*ocl*/ } /*cv*/ void cv::ocl::matchTemplate(const oclMat &image, const oclMat &templ, oclMat &result, int method) { MatchTemplateBuf buf; matchTemplate(image, templ, result, method, buf); } void cv::ocl::matchTemplate(const oclMat &image, const oclMat &templ, oclMat &result, int method, MatchTemplateBuf &buf) { CV_Assert(image.type() == templ.type()); CV_Assert(image.cols >= templ.cols && image.rows >= templ.rows); typedef void (*Caller)(const oclMat &, const oclMat &, oclMat &, MatchTemplateBuf &); const Caller callers[] = { ::matchTemplate_SQDIFF, ::matchTemplate_SQDIFF_NORMED, ::matchTemplate_CCORR, ::matchTemplate_CCORR_NORMED, ::matchTemplate_CCOFF, ::matchTemplate_CCOFF_NORMED }; Caller caller = callers[method]; CV_Assert(caller); caller(image, templ, result, buf); }