662 lines
29 KiB
C++
662 lines
29 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, 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 <vector>
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using namespace cv;
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using namespace cv::ocl;
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using namespace std;
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////////////////////////////////////////////////////////////////////////
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///////////////// stereoBP /////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////
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#if !defined (HAVE_OPENCL)
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namespace cv
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{
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namespace ocl
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{
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void cv::ocl::StereoBeliefPropagation::estimateRecommendedParams(int, int, int &, int &, int &)
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{
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throw_nogpu();
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}
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cv::ocl::StereoBeliefPropagation::StereoBeliefPropagation(int, int, int, int)
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{
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throw_nogpu();
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}
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cv::ocl::StereoBeliefPropagation::StereoBeliefPropagation(int, int, int, float, float, float, float, int)
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{
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throw_nogpu();
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}
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void cv::ocl::StereoBeliefPropagation::operator()(const oclMat &, const oclMat &, oclMat &)
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{
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throw_nogpu();
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}
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void cv::ocl::StereoBeliefPropagation::operator()(const oclMat &, oclMat &)
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{
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throw_nogpu();
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}
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}
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}
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#else /* !defined (HAVE_OPENCL) */
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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 *stereobp;
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}
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}
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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 stereoBP
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{
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//////////////////////////////////////////////////////////////////////////
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//////////////////////////////common////////////////////////////////////
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////////////////////////////////////////////////////////////////////////
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typedef struct
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{
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int cndisp;
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float cmax_data_term;
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float cdata_weight;
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float cmax_disc_term;
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float cdisc_single_jump;
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} con_struct_t;
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cl_mem cl_con_struct = NULL;
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void load_constants(Context *clCxt, int ndisp, float max_data_term, float data_weight,
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float max_disc_term, float disc_single_jump)
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{
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con_struct_t *con_struct = new con_struct_t;
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con_struct -> cndisp = ndisp;
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con_struct -> cmax_data_term = max_data_term;
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con_struct -> cdata_weight = data_weight;
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con_struct -> cmax_disc_term = max_data_term;
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con_struct -> cdisc_single_jump = disc_single_jump;
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cl_con_struct = load_constant(clCxt->impl->clContext, clCxt->impl->clCmdQueue, (void *)con_struct,
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sizeof(con_struct_t));
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delete con_struct;
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}
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void release_constants()
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{
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openCLFree(cl_con_struct);
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}
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static inline int divUp(int total, int grain)
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{
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return (total + grain - 1) / grain;
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}
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/////////////////////////////////////////////////////////////////////////////
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///////////////////////////comp data////////////////////////////////////////
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/////////////////////////////////////////////////////////////////////////
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void comp_data_call(const oclMat &left, const oclMat &right, oclMat &data, int disp, float cmax_data_term, float cdata_weight)
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{
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Context *clCxt = left.clCxt;
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int channels = left.channels();
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int data_type = data.type();
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string kernelName = "comp_data_";
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stringstream idxStr;
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if(data_type == CV_16S)
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idxStr << "0";
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else
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idxStr << "1";
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kernelName += idxStr.str();
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cl_kernel kernel = openCLGetKernelFromSource(clCxt, &stereobp, kernelName);
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size_t blockSize = 32;
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size_t localThreads[] = {32, 8};
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size_t globalThreads[] = {divUp(left.cols, localThreads[0]) * localThreads[0],
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divUp(left.rows, localThreads[1]) * localThreads[1]
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};
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openCLVerifyKernel(clCxt, kernel, &blockSize, globalThreads, localThreads);
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openCLSafeCall(clSetKernelArg(kernel, 0, sizeof(cl_mem), (void *)&left.data));
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openCLSafeCall(clSetKernelArg(kernel, 1, sizeof(cl_int), (void *)&left.rows));
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openCLSafeCall(clSetKernelArg(kernel, 2, sizeof(cl_int), (void *)&left.cols));
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openCLSafeCall(clSetKernelArg(kernel, 3, sizeof(cl_int), (void *)&left.step));
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openCLSafeCall(clSetKernelArg(kernel, 4, sizeof(cl_mem), (void *)&right.data));
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openCLSafeCall(clSetKernelArg(kernel, 5, sizeof(cl_int), (void *)&right.step));
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openCLSafeCall(clSetKernelArg(kernel, 6, sizeof(cl_mem), (void *)&data.data));
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openCLSafeCall(clSetKernelArg(kernel, 7, sizeof(cl_int), (void *)&data.cols));
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openCLSafeCall(clSetKernelArg(kernel, 8, sizeof(cl_int), (void *)&data.step));
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openCLSafeCall(clSetKernelArg(kernel, 9, sizeof(cl_mem), (void *)&cl_con_struct));
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//openCLSafeCall(clSetKernelArg(kernel,12,sizeof(cl_int),(void*)&disp));
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//openCLSafeCall(clSetKernelArg(kernel,13,sizeof(cl_float),(void*)&cmax_data_term));
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//openCLSafeCall(clSetKernelArg(kernel,14,sizeof(cl_float),(void*)&cdata_weight));
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openCLSafeCall(clSetKernelArg(kernel, 10, sizeof(cl_int), (void *)&channels));
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openCLSafeCall(clEnqueueNDRangeKernel(clCxt->impl->clCmdQueue, kernel, 2, NULL,
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globalThreads, localThreads, 0, NULL, NULL));
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clFinish(clCxt->impl->clCmdQueue);
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openCLSafeCall(clReleaseKernel(kernel));
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}
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///////////////////////////////////////////////////////////////////////////////////
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/////////////////////////data set down////////////////////////////////////////////
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/////////////////////////////////////////////////////////////////////////////////
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void data_step_down_call(int dst_cols, int dst_rows, int src_rows,
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const oclMat &src, oclMat &dst, int disp)
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{
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Context *clCxt = src.clCxt;
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int data_type = src.type();
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string kernelName = "data_step_down_";
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stringstream idxStr;
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if(data_type == CV_16S)
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idxStr << "0";
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else
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idxStr << "1";
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kernelName += idxStr.str();
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cl_kernel kernel = openCLGetKernelFromSource(clCxt, &stereobp, kernelName);
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size_t blockSize = 32;
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size_t localThreads[] = {32, 8};
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size_t globalThreads[] = {divUp(dst_cols, localThreads[0]) * localThreads[0],
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divUp(dst_rows, localThreads[1]) * localThreads[1]
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};
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openCLVerifyKernel(clCxt, kernel, &blockSize, globalThreads, localThreads);
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openCLSafeCall(clSetKernelArg(kernel, 0, sizeof(cl_mem), (void *)&src.data));
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openCLSafeCall(clSetKernelArg(kernel, 1, sizeof(cl_int), (void *)&src_rows));
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openCLSafeCall(clSetKernelArg(kernel, 2, sizeof(cl_int), (void *)&src.cols));
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openCLSafeCall(clSetKernelArg(kernel, 3, sizeof(cl_mem), (void *)&dst.data));
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openCLSafeCall(clSetKernelArg(kernel, 4, sizeof(cl_int), (void *)&dst_rows));
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openCLSafeCall(clSetKernelArg(kernel, 5, sizeof(cl_int), (void *)&dst_cols));
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openCLSafeCall(clSetKernelArg(kernel, 6, sizeof(cl_int), (void *)&dst.cols));
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openCLSafeCall(clSetKernelArg(kernel, 7, sizeof(cl_int), (void *)&disp));
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openCLSafeCall(clEnqueueNDRangeKernel(clCxt->impl->clCmdQueue, kernel, 2, NULL,
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globalThreads, localThreads, 0, NULL, NULL));
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clFinish(clCxt->impl->clCmdQueue);
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openCLSafeCall(clReleaseKernel(kernel));
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}
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/////////////////////////////////////////////////////////////////////////////////
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///////////////////////////live up message////////////////////////////////////////
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/////////////////////////////////////////////////////////////////////////////////
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void level_up_message_call(int dst_idx, int dst_cols, int dst_rows, int src_rows,
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oclMat &src, oclMat &dst, int ndisp)
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{
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Context *clCxt = src.clCxt;
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int data_type = src.type();
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string kernelName = "level_up_message_";
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stringstream idxStr;
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if(data_type == CV_16S)
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idxStr << "0";
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else
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idxStr << "1";
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kernelName += idxStr.str();
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cl_kernel kernel = openCLGetKernelFromSource(clCxt, &stereobp, kernelName);
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size_t blockSize = 32;
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size_t localThreads[] = {32, 8};
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size_t globalThreads[] = {divUp(dst_cols, localThreads[0]) * localThreads[0],
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divUp(dst_rows, localThreads[1]) * localThreads[1]
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};
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openCLVerifyKernel(clCxt, kernel, &blockSize, globalThreads, localThreads);
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openCLSafeCall(clSetKernelArg(kernel, 0, sizeof(cl_mem), (void *)&src.data));
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openCLSafeCall(clSetKernelArg(kernel, 1, sizeof(cl_int), (void *)&src_rows));
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openCLSafeCall(clSetKernelArg(kernel, 2, sizeof(cl_int), (void *)&src.step));
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openCLSafeCall(clSetKernelArg(kernel, 3, sizeof(cl_mem), (void *)&dst.data));
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openCLSafeCall(clSetKernelArg(kernel, 4, sizeof(cl_int), (void *)&dst_rows));
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openCLSafeCall(clSetKernelArg(kernel, 5, sizeof(cl_int), (void *)&dst_cols));
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openCLSafeCall(clSetKernelArg(kernel, 6, sizeof(cl_int), (void *)&dst.step));
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openCLSafeCall(clSetKernelArg(kernel, 7, sizeof(cl_int), (void *)&ndisp));
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openCLSafeCall(clEnqueueNDRangeKernel(clCxt->impl->clCmdQueue, kernel, 2, NULL,
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globalThreads, localThreads, 0, NULL, NULL));
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clFinish(clCxt->impl->clCmdQueue);
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openCLSafeCall(clReleaseKernel(kernel));
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}
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void level_up_messages_calls(int dst_idx, int dst_cols, int dst_rows, int src_rows,
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oclMat *mus, oclMat *mds, oclMat *mls, oclMat *mrs,
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int ndisp)
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{
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int src_idx = (dst_idx + 1) & 1;
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level_up_message_call(dst_idx, dst_cols, dst_rows, src_rows,
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mus[src_idx], mus[dst_idx], ndisp);
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level_up_message_call(dst_idx, dst_cols, dst_rows, src_rows,
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mds[src_idx], mds[dst_idx], ndisp);
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level_up_message_call(dst_idx, dst_cols, dst_rows, src_rows,
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mls[src_idx], mls[dst_idx], ndisp);
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level_up_message_call(dst_idx, dst_cols, dst_rows, src_rows,
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mrs[src_idx], mrs[dst_idx], ndisp);
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}
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//////////////////////////////////////////////////////////////////////////////////
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//////////////////////////////cals_all_iterations_call///////////////////////////
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/////////////////////////////////////////////////////////////////////////////////
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void calc_all_iterations_call(int cols, int rows, oclMat &u, oclMat &d,
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oclMat &l, oclMat &r, oclMat &data,
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int t, int cndisp, float cmax_disc_term,
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float cdisc_single_jump)
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{
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Context *clCxt = l.clCxt;
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int data_type = u.type();
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string kernelName = "one_iteration_";
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stringstream idxStr;
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if(data_type == CV_16S)
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idxStr << "0";
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else
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idxStr << "1";
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kernelName += idxStr.str();
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cl_kernel kernel = openCLGetKernelFromSource(clCxt, &stereobp, kernelName);
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size_t blockSize = 32;
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size_t localThreads[] = {32, 8};
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size_t globalThreads[] = {divUp(cols, (localThreads[0] << 1)) * (localThreads[0] << 1),
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divUp(rows, localThreads[1]) * localThreads[1]
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};
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openCLVerifyKernel(clCxt, kernel, &blockSize, globalThreads, localThreads);
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openCLSafeCall(clSetKernelArg(kernel, 0, sizeof(cl_mem), (void *)&u.data));
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openCLSafeCall(clSetKernelArg(kernel, 1, sizeof(cl_int), (void *)&u.step));
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openCLSafeCall(clSetKernelArg(kernel, 2, sizeof(cl_int), (void *)&u.cols));
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openCLSafeCall(clSetKernelArg(kernel, 3, sizeof(cl_mem), (void *)&data.data));
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openCLSafeCall(clSetKernelArg(kernel, 4, sizeof(cl_int), (void *)&data.step));
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openCLSafeCall(clSetKernelArg(kernel, 5, sizeof(cl_int), (void *)&data.cols));
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openCLSafeCall(clSetKernelArg(kernel, 6, sizeof(cl_mem), (void *)&d.data));
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openCLSafeCall(clSetKernelArg(kernel, 7, sizeof(cl_mem), (void *)&l.data));
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openCLSafeCall(clSetKernelArg(kernel, 8, sizeof(cl_mem), (void *)&r.data));
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openCLSafeCall(clSetKernelArg(kernel, 9, sizeof(cl_int), (void *)&t));
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openCLSafeCall(clSetKernelArg(kernel, 10, sizeof(cl_int), (void *)&cols));
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openCLSafeCall(clSetKernelArg(kernel, 11, sizeof(cl_int), (void *)&rows));
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openCLSafeCall(clSetKernelArg(kernel, 12, sizeof(cl_int), (void *)&cndisp));
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openCLSafeCall(clSetKernelArg(kernel, 13, sizeof(cl_float), (void *)&cmax_disc_term));
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openCLSafeCall(clSetKernelArg(kernel, 14, sizeof(cl_float), (void *)&cdisc_single_jump));
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openCLSafeCall(clEnqueueNDRangeKernel(clCxt->impl->clCmdQueue, kernel, 2, NULL,
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globalThreads, localThreads, 0, NULL, NULL));
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clFinish(clCxt->impl->clCmdQueue);
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openCLSafeCall(clReleaseKernel(kernel));
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}
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void calc_all_iterations_calls(int cols, int rows, int iters, oclMat &u,
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oclMat &d, oclMat &l, oclMat &r,
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oclMat &data, int cndisp, float cmax_disc_term,
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float cdisc_single_jump)
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{
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for(int t = 0; t < iters; ++t)
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calc_all_iterations_call(cols, rows, u, d, l, r, data, t, cndisp,
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cmax_disc_term, cdisc_single_jump);
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}
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///////////////////////////////////////////////////////////////////////////////
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///////////////////////output///////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////
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void output_call(const oclMat &u, const oclMat &d, const oclMat l, const oclMat &r,
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const oclMat &data, oclMat &disp, int ndisp)
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{
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Context *clCxt = u.clCxt;
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int data_type = u.type();
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string kernelName = "output_";
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stringstream idxStr;
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if(data_type == CV_16S)
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idxStr << "0";
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else
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idxStr << "1";
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kernelName += idxStr.str();
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cl_kernel kernel = openCLGetKernelFromSource(clCxt, &stereobp, kernelName);
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size_t blockSize = 32;
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size_t localThreads[] = {32, 8};
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size_t globalThreads[] = {divUp(disp.cols, localThreads[0]) * localThreads[0],
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divUp(disp.rows, localThreads[1]) * localThreads[1]
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};
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openCLVerifyKernel(clCxt, kernel, &blockSize, globalThreads, localThreads);
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openCLSafeCall(clSetKernelArg(kernel, 0, sizeof(cl_mem), (void *)&u.data));
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openCLSafeCall(clSetKernelArg(kernel, 1, sizeof(cl_int), (void *)&u.step));
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openCLSafeCall(clSetKernelArg(kernel, 2, sizeof(cl_int), (void *)&u.cols));
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openCLSafeCall(clSetKernelArg(kernel, 3, sizeof(cl_mem), (void *)&d.data));
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openCLSafeCall(clSetKernelArg(kernel, 4, sizeof(cl_mem), (void *)&l.data));
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openCLSafeCall(clSetKernelArg(kernel, 5, sizeof(cl_mem), (void *)&r.data));
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openCLSafeCall(clSetKernelArg(kernel, 6, sizeof(cl_mem), (void *)&data.data));
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openCLSafeCall(clSetKernelArg(kernel, 7, sizeof(cl_mem), (void *)&disp.data));
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openCLSafeCall(clSetKernelArg(kernel, 8, sizeof(cl_int), (void *)&disp.rows));
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openCLSafeCall(clSetKernelArg(kernel, 9, sizeof(cl_int), (void *)&disp.cols));
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openCLSafeCall(clSetKernelArg(kernel, 10, sizeof(cl_int), (void *)&disp.step));
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openCLSafeCall(clSetKernelArg(kernel, 11, sizeof(cl_int), (void *)&ndisp));
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openCLSafeCall(clEnqueueNDRangeKernel(clCxt->impl->clCmdQueue, kernel, 2, NULL,
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globalThreads, localThreads, 0, NULL, NULL));
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clFinish(clCxt->impl->clCmdQueue);
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openCLSafeCall(clReleaseKernel(kernel));
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}
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}
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}
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}
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namespace
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{
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const float DEFAULT_MAX_DATA_TERM = 10.0f;
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const float DEFAULT_DATA_WEIGHT = 0.07f;
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const float DEFAULT_MAX_DISC_TERM = 1.7f;
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const float DEFAULT_DISC_SINGLE_JUMP = 1.0f;
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template<typename T>
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void print_gpu_mat(const oclMat &mat)
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{
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T *data_1 = new T[mat.rows * mat.cols * mat.channels()];
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Context *clCxt = mat.clCxt;
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int status = clEnqueueReadBuffer(clCxt -> impl-> clCmdQueue, (cl_mem)mat.data, CL_TRUE, 0,
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mat.rows * mat.cols * mat.channels() * sizeof(T), data_1, 0, NULL, NULL);
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if(status != CL_SUCCESS)
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cout << "error " << status << endl;
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cout << ".........................................................." << endl;
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cout << "elemSize() " << mat.elemSize() << endl;
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cout << "elemSize() " << mat.elemSize1() << endl;
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cout << "channels: " << mat.channels() << endl;
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cout << "rows: " << mat.rows << endl;
|
|
cout << "cols: " << mat.cols << endl;
|
|
|
|
for(int i = 0; i < 30; i++)
|
|
{
|
|
for(int j = 0; j < 30; j++)
|
|
{
|
|
cout << (int)data_1[i * mat.cols * mat.channels() + j] << " ";
|
|
}
|
|
cout << endl;
|
|
}
|
|
}
|
|
}
|
|
|
|
void cv::ocl::StereoBeliefPropagation::estimateRecommendedParams(int width, int height, int &ndisp, int &iters, int &levels)
|
|
{
|
|
ndisp = width / 4;
|
|
if ((ndisp & 1) != 0)
|
|
ndisp++;
|
|
|
|
int mm = ::max(width, height);
|
|
iters = mm / 100 + 2;
|
|
|
|
levels = (int)(::log(static_cast<double>(mm)) + 1) * 4 / 5;
|
|
if (levels == 0) levels++;
|
|
}
|
|
|
|
cv::ocl::StereoBeliefPropagation::StereoBeliefPropagation(int ndisp_, int iters_, int levels_, int msg_type_)
|
|
: ndisp(ndisp_), iters(iters_), levels(levels_),
|
|
max_data_term(DEFAULT_MAX_DATA_TERM), data_weight(DEFAULT_DATA_WEIGHT),
|
|
max_disc_term(DEFAULT_MAX_DISC_TERM), disc_single_jump(DEFAULT_DISC_SINGLE_JUMP),
|
|
msg_type(msg_type_), datas(levels_)
|
|
{
|
|
}
|
|
|
|
cv::ocl::StereoBeliefPropagation::StereoBeliefPropagation(int ndisp_, int iters_, int levels_, float max_data_term_, float data_weight_, float max_disc_term_, float disc_single_jump_, int msg_type_)
|
|
: ndisp(ndisp_), iters(iters_), levels(levels_),
|
|
max_data_term(max_data_term_), data_weight(data_weight_),
|
|
max_disc_term(max_disc_term_), disc_single_jump(disc_single_jump_),
|
|
msg_type(msg_type_), datas(levels_)
|
|
{
|
|
}
|
|
|
|
namespace
|
|
{
|
|
class StereoBeliefPropagationImpl
|
|
{
|
|
public:
|
|
StereoBeliefPropagationImpl(StereoBeliefPropagation &rthis_,
|
|
oclMat &u_, oclMat &d_, oclMat &l_, oclMat &r_,
|
|
oclMat &u2_, oclMat &d2_, oclMat &l2_, oclMat &r2_,
|
|
vector<oclMat>& datas_, oclMat &out_)
|
|
: rthis(rthis_), u(u_), d(d_), l(l_), r(r_), u2(u2_), d2(d2_), l2(l2_), r2(r2_), datas(datas_), out(out_),
|
|
zero(Scalar::all(0)), scale(rthis_.msg_type == CV_32F ? 1.0f : 10.0f)
|
|
{
|
|
CV_Assert(0 < rthis.ndisp && 0 < rthis.iters && 0 < rthis.levels);
|
|
CV_Assert(rthis.msg_type == CV_32F || rthis.msg_type == CV_16S);
|
|
CV_Assert(rthis.msg_type == CV_32F || (1 << (rthis.levels - 1)) * scale * rthis.max_data_term < numeric_limits<short>::max());
|
|
}
|
|
|
|
void operator()(const oclMat &left, const oclMat &right, oclMat &disp)
|
|
{
|
|
CV_Assert(left.size() == right.size() && left.type() == right.type());
|
|
CV_Assert(left.type() == CV_8UC1 || left.type() == CV_8UC3 || left.type() == CV_8UC4);
|
|
|
|
rows = left.rows;
|
|
cols = left.cols;
|
|
|
|
int divisor = (int)pow(2.f, rthis.levels - 1.0f);
|
|
int lowest_cols = cols / divisor;
|
|
int lowest_rows = rows / divisor;
|
|
const int min_image_dim_size = 2;
|
|
CV_Assert(min(lowest_cols, lowest_rows) > min_image_dim_size);
|
|
|
|
init();
|
|
|
|
datas[0].create(rows * rthis.ndisp, cols, rthis.msg_type);
|
|
datas[0].setTo(Scalar_<short>::all(0));
|
|
|
|
cv::ocl::stereoBP::comp_data_call(left, right, datas[0], rthis.ndisp, rthis.max_data_term, scale * rthis.data_weight);
|
|
|
|
calcBP(disp);
|
|
}
|
|
|
|
void operator()(const oclMat &data, oclMat &disp)
|
|
{
|
|
CV_Assert((data.type() == rthis.msg_type) && (data.rows % rthis.ndisp == 0));
|
|
|
|
rows = data.rows / rthis.ndisp;
|
|
cols = data.cols;
|
|
|
|
int divisor = (int)pow(2.f, rthis.levels - 1.0f);
|
|
int lowest_cols = cols / divisor;
|
|
int lowest_rows = rows / divisor;
|
|
const int min_image_dim_size = 2;
|
|
CV_Assert(min(lowest_cols, lowest_rows) > min_image_dim_size);
|
|
|
|
init();
|
|
|
|
datas[0] = data;
|
|
|
|
calcBP(disp);
|
|
}
|
|
private:
|
|
void init()
|
|
{
|
|
u.create(rows * rthis.ndisp, cols, rthis.msg_type);
|
|
d.create(rows * rthis.ndisp, cols, rthis.msg_type);
|
|
l.create(rows * rthis.ndisp, cols, rthis.msg_type);
|
|
r.create(rows * rthis.ndisp, cols, rthis.msg_type);
|
|
|
|
if (rthis.levels & 1)
|
|
{
|
|
//can clear less area
|
|
u = zero;
|
|
d = zero;
|
|
l = zero;
|
|
r = zero;
|
|
}
|
|
|
|
if (rthis.levels > 1)
|
|
{
|
|
int less_rows = (rows + 1) / 2;
|
|
int less_cols = (cols + 1) / 2;
|
|
|
|
u2.create(less_rows * rthis.ndisp, less_cols, rthis.msg_type);
|
|
d2.create(less_rows * rthis.ndisp, less_cols, rthis.msg_type);
|
|
l2.create(less_rows * rthis.ndisp, less_cols, rthis.msg_type);
|
|
r2.create(less_rows * rthis.ndisp, less_cols, rthis.msg_type);
|
|
|
|
if ((rthis.levels & 1) == 0)
|
|
{
|
|
u2 = zero;
|
|
d2 = zero;
|
|
l2 = zero;
|
|
r2 = zero;
|
|
}
|
|
}
|
|
|
|
cv::ocl::stereoBP::load_constants(u.clCxt, rthis.ndisp, rthis.max_data_term, scale * rthis.data_weight,
|
|
scale * rthis.max_disc_term, scale * rthis.disc_single_jump);
|
|
|
|
datas.resize(rthis.levels);
|
|
|
|
cols_all.resize(rthis.levels);
|
|
rows_all.resize(rthis.levels);
|
|
|
|
cols_all[0] = cols;
|
|
rows_all[0] = rows;
|
|
}
|
|
|
|
void calcBP(oclMat &disp)
|
|
{
|
|
using namespace cv::ocl::stereoBP;
|
|
|
|
for (int i = 1; i < rthis.levels; ++i)
|
|
{
|
|
cols_all[i] = (cols_all[i-1] + 1) / 2;
|
|
rows_all[i] = (rows_all[i-1] + 1) / 2;
|
|
|
|
datas[i].create(rows_all[i] * rthis.ndisp, cols_all[i], rthis.msg_type);
|
|
datas[i].setTo(Scalar_<short>::all(0));
|
|
|
|
data_step_down_call(cols_all[i], rows_all[i], rows_all[i-1],
|
|
datas[i-1], datas[i], rthis.ndisp);
|
|
}
|
|
|
|
oclMat mus[] = {u, u2};
|
|
oclMat mds[] = {d, d2};
|
|
oclMat mrs[] = {r, r2};
|
|
oclMat mls[] = {l, l2};
|
|
|
|
int mem_idx = (rthis.levels & 1) ? 0 : 1;
|
|
|
|
for (int i = rthis.levels - 1; i >= 0; --i)
|
|
{
|
|
// for lower level we have already computed messages by setting to zero
|
|
if (i != rthis.levels - 1)
|
|
level_up_messages_calls(mem_idx, cols_all[i], rows_all[i], rows_all[i+1],
|
|
mus, mds, mls, mrs, rthis.ndisp);
|
|
|
|
calc_all_iterations_calls(cols_all[i], rows_all[i], rthis.iters, mus[mem_idx],
|
|
mds[mem_idx], mls[mem_idx], mrs[mem_idx], datas[i],
|
|
rthis.ndisp, scale * rthis.max_disc_term,
|
|
scale * rthis.disc_single_jump);
|
|
|
|
mem_idx = (mem_idx + 1) & 1;
|
|
}
|
|
|
|
if (disp.empty())
|
|
disp.create(rows, cols, CV_16S);
|
|
|
|
out = ((disp.type() == CV_16S) ? disp : (out.create(rows, cols, CV_16S), out));
|
|
out = zero;
|
|
|
|
output_call(u, d, l, r, datas.front(), out, rthis.ndisp);
|
|
|
|
|
|
if (disp.type() != CV_16S)
|
|
out.convertTo(disp, disp.type());
|
|
|
|
release_constants();
|
|
}
|
|
|
|
StereoBeliefPropagation &rthis;
|
|
|
|
oclMat &u;
|
|
oclMat &d;
|
|
oclMat &l;
|
|
oclMat &r;
|
|
|
|
oclMat &u2;
|
|
oclMat &d2;
|
|
oclMat &l2;
|
|
oclMat &r2;
|
|
|
|
vector<oclMat>& datas;
|
|
oclMat &out;
|
|
|
|
const Scalar zero;
|
|
const float scale;
|
|
|
|
int rows, cols;
|
|
|
|
vector<int> cols_all, rows_all;
|
|
};
|
|
}
|
|
|
|
void cv::ocl::StereoBeliefPropagation::operator()(const oclMat &left, const oclMat &right, oclMat &disp)
|
|
{
|
|
::StereoBeliefPropagationImpl impl(*this, u, d, l, r, u2, d2, l2, r2, datas, out);
|
|
impl(left, right, disp);
|
|
}
|
|
|
|
void cv::ocl::StereoBeliefPropagation::operator()(const oclMat &data, oclMat &disp)
|
|
{
|
|
::StereoBeliefPropagationImpl impl(*this, u, d, l, r, u2, d2, l2, r2, datas, out);
|
|
impl(data, disp);
|
|
}
|
|
#endif /* !defined (HAVE_OPENCL) */
|