Open Source Computer Vision Library
https://opencv.org/
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261 lines
11 KiB
261 lines
11 KiB
/*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, Institute Of Software Chinese Academy Of Science, 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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// Jia Haipeng, jiahaipeng95@gmail.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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#include "opencl_kernels.hpp" |
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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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namespace split_merge |
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{ |
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static void merge_vector_run(const oclMat *mat_src, size_t n, oclMat &mat_dst) |
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{ |
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if(!mat_dst.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && mat_dst.type() == CV_64F) |
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{ |
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CV_Error(Error::GpuNotSupported, "Selected device don't support double\r\n"); |
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return; |
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} |
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Context *clCxt = mat_dst.clCxt; |
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int channels = mat_dst.oclchannels(); |
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int depth = mat_dst.depth(); |
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String kernelName = "merge_vector"; |
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int vector_lengths[4][7] = {{0, 0, 0, 0, 0, 0, 0}, |
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{2, 2, 1, 1, 1, 1, 1}, |
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{4, 4, 2, 2 , 1, 1, 1}, |
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{1, 1, 1, 1, 1, 1, 1} |
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}; |
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size_t vector_length = vector_lengths[channels - 1][depth]; |
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int offset_cols = (mat_dst.offset / mat_dst.elemSize()) & (vector_length - 1); |
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int cols = divUp(mat_dst.cols + offset_cols, vector_length); |
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size_t localThreads[3] = { 64, 4, 1 }; |
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size_t globalThreads[3] = { cols, mat_dst.rows, 1 }; |
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int dst_step1 = mat_dst.cols * mat_dst.elemSize(); |
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std::vector<std::pair<size_t , const void *> > args; |
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&mat_dst.data)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_dst.step)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_dst.offset)); |
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&mat_src[0].data)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_src[0].step)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_src[0].offset)); |
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&mat_src[1].data)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_src[1].step)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_src[1].offset)); |
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if(channels == 4) |
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{ |
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&mat_src[2].data)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_src[2].step)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_src[2].offset)); |
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if(n == 3) |
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{ |
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&mat_src[2].data)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_src[2].step)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_src[2].offset)); |
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} |
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else if( n == 4) |
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{ |
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&mat_src[3].data)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_src[3].step)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_src[3].offset)); |
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} |
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} |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_dst.rows)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&cols)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&dst_step1)); |
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openCLExecuteKernel(clCxt, &merge_mat, kernelName, globalThreads, localThreads, args, channels, depth); |
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} |
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static void merge(const oclMat *mat_src, size_t n, oclMat &mat_dst) |
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{ |
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CV_Assert(mat_src); |
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CV_Assert(n > 0); |
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int depth = mat_src[0].depth(); |
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Size size = mat_src[0].size(); |
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int total_channels = 0; |
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for(size_t i = 0; i < n; ++i) |
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{ |
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CV_Assert(depth == mat_src[i].depth()); |
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CV_Assert(size == mat_src[i].size()); |
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total_channels += mat_src[i].oclchannels(); |
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} |
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CV_Assert(total_channels <= 4); |
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if(total_channels == 1) |
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{ |
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mat_src[0].copyTo(mat_dst); |
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return; |
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} |
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mat_dst.create(size, CV_MAKETYPE(depth, total_channels)); |
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merge_vector_run(mat_src, n, mat_dst); |
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} |
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static void split_vector_run(const oclMat &mat_src, oclMat *mat_dst) |
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{ |
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if(!mat_src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && mat_src.type() == CV_64F) |
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{ |
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CV_Error(Error::GpuNotSupported, "Selected device don't support double\r\n"); |
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return; |
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} |
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Context *clCxt = mat_src.clCxt; |
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int channels = mat_src.oclchannels(); |
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int depth = mat_src.depth(); |
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String kernelName = "split_vector"; |
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int vector_lengths[4][7] = {{0, 0, 0, 0, 0, 0, 0}, |
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{4, 4, 2, 2, 1, 1, 1}, |
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{4, 4, 2, 2 , 1, 1, 1}, |
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{4, 4, 2, 2, 1, 1, 1} |
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}; |
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size_t vector_length = vector_lengths[channels - 1][mat_dst[0].depth()]; |
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int max_offset_cols = 0; |
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for(int i = 0; i < channels; i++) |
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{ |
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int offset_cols = (mat_dst[i].offset / mat_dst[i].elemSize()) & (vector_length - 1); |
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if(max_offset_cols < offset_cols) |
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max_offset_cols = offset_cols; |
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} |
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int cols = vector_length == 1 ? divUp(mat_src.cols, vector_length) |
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: divUp(mat_src.cols + max_offset_cols, vector_length); |
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size_t localThreads[3] = { 64, 4, 1 }; |
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size_t globalThreads[3] = { cols, mat_src.rows, 1 }; |
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int dst_step1 = mat_dst[0].cols * mat_dst[0].elemSize(); |
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std::vector<std::pair<size_t , const void *> > args; |
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&mat_src.data)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_src.step)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_src.offset)); |
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&mat_dst[0].data)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_dst[0].step)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_dst[0].offset)); |
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&mat_dst[1].data)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_dst[1].step)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_dst[1].offset)); |
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if(channels >= 3) |
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{ |
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&mat_dst[2].data)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_dst[2].step)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_dst[2].offset)); |
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} |
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if(channels >= 4) |
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{ |
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&mat_dst[3].data)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_dst[3].step)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_dst[3].offset)); |
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} |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&mat_src.rows)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&cols)); |
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&dst_step1)); |
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openCLExecuteKernel(clCxt, &split_mat, kernelName, globalThreads, localThreads, args, channels, depth); |
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} |
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static void split(const oclMat &mat_src, oclMat *mat_dst) |
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{ |
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CV_Assert(mat_dst); |
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int depth = mat_src.depth(); |
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int num_channels = mat_src.oclchannels(); |
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Size size = mat_src.size(); |
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if(num_channels == 1) |
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{ |
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mat_src.copyTo(mat_dst[0]); |
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return; |
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} |
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int i; |
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for(i = 0; i < num_channels; i++) |
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mat_dst[i].create(size, CV_MAKETYPE(depth, 1)); |
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split_vector_run(mat_src, mat_dst); |
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} |
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} |
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} |
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} |
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void cv::ocl::merge(const oclMat *src, size_t n, oclMat &dst) |
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{ |
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split_merge::merge(src, n, dst); |
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} |
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void cv::ocl::merge(const std::vector<oclMat> &src, oclMat &dst) |
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{ |
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split_merge::merge(&src[0], src.size(), dst); |
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} |
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void cv::ocl::split(const oclMat &src, oclMat *dst) |
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{ |
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split_merge::split(src, dst); |
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} |
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void cv::ocl::split(const oclMat &src, std::vector<oclMat> &dst) |
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{ |
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dst.resize(src.oclchannels()); |
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if(src.oclchannels() > 0) |
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split_merge::split(src, &dst[0]); |
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}
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