/*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, Institute Of Software Chinese Academy Of Science, all rights reserved. // Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // @Authors // Jia Haipeng, jiahaipeng95@gmail.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 "precomp.hpp" #include using namespace cv; using namespace cv::ocl; using namespace std; using std::cout; using std::endl; //////////////////////////////////////////////////////////////////////// ///////////////// oclMat merge and split /////////////////////////////// //////////////////////////////////////////////////////////////////////// #if !defined (HAVE_OPENCL) namespace cv { namespace ocl { void cv::ocl::merge(const oclMat *src_mat, size_t count, oclMat &dst_mat) { throw_nogpu(); } void cv::ocl::merge(const vector &src_mat, oclMat &dst_mat) { throw_nogpu(); } void cv::ocl::split(const oclMat &src, oclMat *dst) { throw_nogpu(); } void cv::ocl::split(const oclMat &src, vector &dst) { throw_nogpu(); } } } #else /* !defined (HAVE_OPENCL) */ namespace cv { namespace ocl { ///////////////////////////OpenCL kernel strings/////////////////////////// extern const char *merge_mat; extern const char *split_mat; } } namespace cv { namespace ocl { namespace split_merge { /////////////////////////////////////////////////////////// ///////////////common///////////////////////////////////// ///////////////////////////////////////////////////////// inline int divUp(int total, int grain) { return (total + grain - 1) / grain; } //////////////////////////////////////////////////////////////////////////// ////////////////////merge////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////// void merge_vector_run_no_roi(const oclMat *mat_src, size_t n, oclMat &mat_dst) { Context *clCxt = mat_dst.clCxt; int channels = mat_dst.oclchannels(); int depth = mat_dst.depth(); string kernelName = "merge_vector"; int indexes[4][7] = {{0, 0, 0, 0, 0, 0, 0}, {4, 4, 2, 2, 1, 1, 1}, {4, 4, 2, 2 , 1, 1, 1}, {4, 4, 2, 2, 1, 1, 1} }; size_t index = indexes[channels - 1][mat_dst.depth()]; int cols = divUp(mat_dst.cols, index); size_t localThreads[3] = { 64, 4, 1 }; size_t globalThreads[3] = { divUp(cols, localThreads[0]) *localThreads[0], divUp(mat_dst.rows, localThreads[1]) *localThreads[1], 1 }; vector > args; args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst.rows)); args.push_back( make_pair( sizeof(cl_int), (void *)&cols)); args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_dst.data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst.step)); args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_src[0].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src[0].step)); args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_src[1].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src[1].step)); if(n >= 3) { args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_src[2].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src[2].step)); } if(n >= 4) { args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_src[3].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src[3].step)); } openCLExecuteKernel(clCxt, &merge_mat, kernelName, globalThreads, localThreads, args, channels, depth); } void merge_vector_run(const oclMat *mat_src, size_t n, oclMat &mat_dst) { if(mat_dst.clCxt -> impl -> double_support == 0 && mat_dst.type() == CV_64F) { CV_Error(CV_GpuNotSupported, "Selected device don't support double\r\n"); return; } Context *clCxt = mat_dst.clCxt; int channels = mat_dst.oclchannels(); int depth = mat_dst.depth(); string kernelName = "merge_vector"; int vector_lengths[4][7] = {{0, 0, 0, 0, 0, 0, 0}, {2, 2, 1, 1, 1, 1, 1}, {4, 4, 2, 2 , 1, 1, 1}, {1, 1, 1, 1, 1, 1, 1} }; size_t vector_length = vector_lengths[channels - 1][depth]; int offset_cols = (mat_dst.offset / mat_dst.elemSize()) & (vector_length - 1); int cols = divUp(mat_dst.cols + offset_cols, vector_length); size_t localThreads[3] = { 64, 4, 1 }; size_t globalThreads[3] = { divUp(cols, localThreads[0]) *localThreads[0], divUp(mat_dst.rows, localThreads[1]) *localThreads[1], 1 }; int dst_step1 = mat_dst.cols * mat_dst.elemSize(); vector > args; args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_dst.data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst.step)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst.offset)); args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_src[0].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src[0].step)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src[0].offset)); args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_src[1].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src[1].step)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src[1].offset)); if(channels == 4) { args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_src[2].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src[2].step)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src[2].offset)); // if channel == 3, then the matrix will convert to channel =4 //if(n == 3) // args.push_back( make_pair( sizeof(cl_int), (void *)&offset_cols)); if(n == 3) { args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_src[2].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src[2].step)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src[2].offset)); } else if( n == 4) { args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_src[3].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src[3].step)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src[3].offset)); } } args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst.rows)); args.push_back( make_pair( sizeof(cl_int), (void *)&cols)); args.push_back( make_pair( sizeof(cl_int), (void *)&dst_step1)); openCLExecuteKernel(clCxt, &merge_mat, kernelName, globalThreads, localThreads, args, channels, depth); } void merge(const oclMat *mat_src, size_t n, oclMat &mat_dst) { CV_Assert(mat_src); CV_Assert(n > 0); int depth = mat_src[0].depth(); Size size = mat_src[0].size(); int total_channels = 0; for(size_t i = 0; i < n; ++i) { CV_Assert(depth == mat_src[i].depth()); CV_Assert(size == mat_src[i].size()); total_channels += mat_src[i].oclchannels(); } CV_Assert(total_channels <= 4); if(total_channels == 1) { mat_src[0].copyTo(mat_dst); return; } mat_dst.create(size, CV_MAKETYPE(depth, total_channels)); merge_vector_run(mat_src, n, mat_dst); } //////////////////////////////////////////////////////////////////////////////////////////////////// //////////////////////////////////////split///////////////////////////////////////////////////////////// ////////////////////////////////////////////////////////////////////////////////////////////////// void split_vector_run_no_roi(const oclMat &mat_src, oclMat *mat_dst) { Context *clCxt = mat_src.clCxt; int channels = mat_src.oclchannels(); int depth = mat_src.depth(); string kernelName = "split_vector"; int indexes[4][7] = {{0, 0, 0, 0, 0, 0, 0}, {8, 8, 8, 8, 4, 4, 2}, {8, 8, 8, 8 , 4, 4, 4}, {4, 4, 2, 2, 1, 1, 1} }; size_t index = indexes[channels - 1][mat_dst[0].depth()]; int cols = divUp(mat_src.cols, index); size_t localThreads[3] = { 64, 4, 1 }; size_t globalThreads[3] = { divUp(cols, localThreads[0]) *localThreads[0], divUp(mat_src.rows, localThreads[1]) *localThreads[1], 1 }; vector > args; args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_src.data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src.step)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src.rows)); args.push_back( make_pair( sizeof(cl_int), (void *)&cols)); args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_dst[0].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst[0].step)); args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_dst[1].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst[1].step)); if(channels >= 3) { args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_dst[2].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst[2].step)); } if(channels >= 4) { args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_dst[3].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst[3].step)); } openCLExecuteKernel(clCxt, &split_mat, kernelName, globalThreads, localThreads, args, channels, depth); } void split_vector_run(const oclMat &mat_src, oclMat *mat_dst) { if(mat_src.clCxt -> impl -> double_support == 0 && mat_src.type() == CV_64F) { CV_Error(CV_GpuNotSupported, "Selected device don't support double\r\n"); return; } Context *clCxt = mat_src.clCxt; int channels = mat_src.oclchannels(); int depth = mat_src.depth(); string kernelName = "split_vector"; int vector_lengths[4][7] = {{0, 0, 0, 0, 0, 0, 0}, {4, 4, 2, 2, 1, 1, 1}, {4, 4, 2, 2 , 1, 1, 1}, {4, 4, 2, 2, 1, 1, 1} }; size_t vector_length = vector_lengths[channels - 1][mat_dst[0].depth()]; int max_offset_cols = 0; for(int i = 0; i < channels; i++) { int offset_cols = (mat_dst[i].offset / mat_dst[i].elemSize()) & (vector_length - 1); if(max_offset_cols < offset_cols) max_offset_cols = offset_cols; } int cols = vector_length == 1 ? divUp(mat_src.cols, vector_length) : divUp(mat_src.cols + max_offset_cols, vector_length); size_t localThreads[3] = { 64, 4, 1 }; size_t globalThreads[3] = { divUp(cols, localThreads[0]) *localThreads[0], divUp(mat_src.rows, localThreads[1]) *localThreads[1], 1 }; int dst_step1 = mat_dst[0].cols * mat_dst[0].elemSize(); vector > args; args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_src.data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src.step)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src.offset)); args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_dst[0].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst[0].step)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst[0].offset)); args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_dst[1].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst[1].step)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst[1].offset)); if(channels >= 3) { args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_dst[2].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst[2].step)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst[2].offset)); } if(channels >= 4) { args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_dst[3].data)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst[3].step)); args.push_back( make_pair( sizeof(cl_int), (void *)&mat_dst[3].offset)); } args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src.rows)); args.push_back( make_pair( sizeof(cl_int), (void *)&cols)); args.push_back( make_pair( sizeof(cl_int), (void *)&dst_step1)); openCLExecuteKernel(clCxt, &split_mat, kernelName, globalThreads, localThreads, args, channels, depth); } void split(const oclMat &mat_src, oclMat *mat_dst) { CV_Assert(mat_dst); int depth = mat_src.depth(); int num_channels = mat_src.oclchannels(); Size size = mat_src.size(); if(num_channels == 1) { mat_src.copyTo(mat_dst[0]); return; } int i; for(i = 0; i < num_channels; i++) mat_dst[i].create(size, CV_MAKETYPE(depth, 1)); split_vector_run(mat_src, mat_dst); } } } } void cv::ocl::merge(const oclMat *src, size_t n, oclMat &dst) { split_merge::merge(src, n, dst); } void cv::ocl::merge(const vector &src, oclMat &dst) { split_merge::merge(&src[0], src.size(), dst); } void cv::ocl::split(const oclMat &src, oclMat *dst) { split_merge::split(src, dst); } void cv::ocl::split(const oclMat &src, vector &dst) { dst.resize(src.oclchannels()); if(src.oclchannels() > 0) split_merge::split(src, &dst[0]); } #endif /* !defined (HAVE_OPENCL) */