9c2272d520
Conflicts: .gitignore CMakeLists.txt doc/CMakeLists.txt modules/calib3d/src/stereosgbm.cpp modules/core/include/opencv2/core/mat.hpp modules/highgui/src/cap_openni.cpp modules/ml/include/opencv2/ml/ml.hpp modules/objdetect/src/hog.cpp modules/ocl/perf/perf_color.cpp modules/ocl/src/arithm.cpp modules/ocl/src/filtering.cpp modules/ocl/src/imgproc.cpp modules/ocl/src/optical_flow_farneback.cpp platforms/scripts/camera_build.conf platforms/scripts/cmake_android_all_cameras.py samples/cpp/Qt_sample/main.cpp samples/cpp/tutorial_code/introduction/windows_visual_studio_Opencv/Test.cpp
543 lines
19 KiB
C++
543 lines
19 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// @Authors
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// Sen Liu, swjtuls1987@126.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 materials 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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#include "opencv2/video/tracking.hpp"
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using namespace cv;
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using namespace cv::ocl;
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#define MIN_SIZE 32
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namespace cv {
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namespace ocl {
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namespace optflow_farneback
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{
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oclMat g;
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oclMat xg;
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oclMat xxg;
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oclMat gKer;
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float ig[4];
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inline void setGaussianBlurKernel(const float *c_gKer, int ksizeHalf)
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{
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cv::Mat t_gKer(1, ksizeHalf + 1, CV_32FC1, const_cast<float *>(c_gKer));
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gKer.upload(t_gKer);
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}
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static void gaussianBlurOcl(const oclMat &src, int ksizeHalf, oclMat &dst)
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{
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String kernelName("gaussianBlur");
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#ifdef ANDROID
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size_t localThreads[3] = { 128, 1, 1 };
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#else
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size_t localThreads[3] = { 256, 1, 1 };
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#endif
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size_t globalThreads[3] = { src.cols, src.rows, 1 };
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int smem_size = (localThreads[0] + 2*ksizeHalf) * sizeof(float);
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CV_Assert(dst.size() == src.size());
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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 *)&dst.data));
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args.push_back(std::make_pair(sizeof(cl_mem), (void *)&src.data));
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args.push_back(std::make_pair(sizeof(cl_mem), (void *)&gKer.data));
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args.push_back(std::make_pair(smem_size, (void *)NULL));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&dst.rows));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&dst.cols));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&dst.step));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&src.step));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&ksizeHalf));
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openCLExecuteKernel(Context::getContext(), &optical_flow_farneback, kernelName,
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globalThreads, localThreads, args, -1, -1);
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}
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static void polynomialExpansionOcl(const oclMat &src, int polyN, oclMat &dst)
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{
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String kernelName("polynomialExpansion");
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#ifdef ANDROID
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size_t localThreads[3] = { 128, 1, 1 };
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#else
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size_t localThreads[3] = { 256, 1, 1 };
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#endif
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size_t globalThreads[3] = { divUp(src.cols, localThreads[0] - 2*polyN) * localThreads[0], src.rows, 1 };
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int smem_size = 3 * localThreads[0] * sizeof(float);
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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 *)&dst.data));
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args.push_back(std::make_pair(sizeof(cl_mem), (void *)&src.data));
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args.push_back(std::make_pair(sizeof(cl_mem), (void *)&g.data));
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args.push_back(std::make_pair(sizeof(cl_mem), (void *)&xg.data));
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args.push_back(std::make_pair(sizeof(cl_mem), (void *)&xxg.data));
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args.push_back(std::make_pair(smem_size, (void *)NULL));
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args.push_back(std::make_pair(sizeof(cl_float4), (void *)&ig));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&src.rows));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&src.cols));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&dst.step));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&src.step));
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char opt [128];
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sprintf(opt, "-D polyN=%d", polyN);
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openCLExecuteKernel(Context::getContext(), &optical_flow_farneback, kernelName,
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globalThreads, localThreads, args, -1, -1, opt);
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}
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static void updateMatricesOcl(const oclMat &flowx, const oclMat &flowy, const oclMat &R0, const oclMat &R1, oclMat &M)
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{
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String kernelName("updateMatrices");
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#ifdef ANDROID
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size_t localThreads[3] = { 32, 4, 1 };
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#else
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size_t localThreads[3] = { 32, 8, 1 };
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#endif
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size_t globalThreads[3] = { flowx.cols, flowx.rows, 1 };
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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 *)&M.data));
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args.push_back(std::make_pair(sizeof(cl_mem), (void *)&flowx.data));
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args.push_back(std::make_pair(sizeof(cl_mem), (void *)&flowy.data));
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args.push_back(std::make_pair(sizeof(cl_mem), (void *)&R0.data));
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args.push_back(std::make_pair(sizeof(cl_mem), (void *)&R1.data));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&flowx.rows));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&flowx.cols));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&M.step));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&flowx.step));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&flowy.step));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&R0.step));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&R1.step));
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openCLExecuteKernel(Context::getContext(), &optical_flow_farneback, kernelName,
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globalThreads, localThreads, args, -1, -1);
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}
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static void boxFilter5Ocl(const oclMat &src, int ksizeHalf, oclMat &dst)
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{
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String kernelName("boxFilter5");
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int height = src.rows / 5;
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#ifdef ANDROID
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size_t localThreads[3] = { 128, 1, 1 };
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#else
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size_t localThreads[3] = { 256, 1, 1 };
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#endif
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size_t globalThreads[3] = { src.cols, height, 1 };
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int smem_size = (localThreads[0] + 2*ksizeHalf) * 5 * sizeof(float);
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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 *)&dst.data));
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args.push_back(std::make_pair(sizeof(cl_mem), (void *)&src.data));
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args.push_back(std::make_pair(smem_size, (void *)NULL));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&height));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&src.cols));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&dst.step));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&src.step));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&ksizeHalf));
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openCLExecuteKernel(Context::getContext(), &optical_flow_farneback, kernelName,
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globalThreads, localThreads, args, -1, -1);
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}
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static void updateFlowOcl(const oclMat &M, oclMat &flowx, oclMat &flowy)
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{
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String kernelName("updateFlow");
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int cols = divUp(flowx.cols, 4);
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#ifdef ANDROID
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size_t localThreads[3] = { 32, 4, 1 };
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#else
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size_t localThreads[3] = { 32, 8, 1 };
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#endif
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size_t globalThreads[3] = { cols, flowx.rows, 1 };
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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 *)&flowx.data));
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args.push_back(std::make_pair(sizeof(cl_mem), (void *)&flowy.data));
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args.push_back(std::make_pair(sizeof(cl_mem), (void *)&M.data));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&flowx.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 *)&flowx.step));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&flowy.step));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&M.step));
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openCLExecuteKernel(Context::getContext(), &optical_flow_farneback, kernelName,
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globalThreads, localThreads, args, -1, -1);
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}
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static void gaussianBlur5Ocl(const oclMat &src, int ksizeHalf, oclMat &dst)
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{
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String kernelName("gaussianBlur5");
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int height = src.rows / 5;
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#ifdef ANDROID
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size_t localThreads[3] = { 128, 1, 1 };
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#else
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size_t localThreads[3] = { 256, 1, 1 };
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#endif
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size_t globalThreads[3] = { src.cols, height, 1 };
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int smem_size = (localThreads[0] + 2*ksizeHalf) * 5 * sizeof(float);
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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 *)&dst.data));
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args.push_back(std::make_pair(sizeof(cl_mem), (void *)&src.data));
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args.push_back(std::make_pair(sizeof(cl_mem), (void *)&gKer.data));
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args.push_back(std::make_pair(smem_size, (void *)NULL));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&height));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&src.cols));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&dst.step));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&src.step));
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args.push_back(std::make_pair(sizeof(cl_int), (void *)&ksizeHalf));
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openCLExecuteKernel(Context::getContext(), &optical_flow_farneback, kernelName,
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globalThreads, localThreads, args, -1, -1);
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}
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}
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}
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} // namespace cv { namespace ocl { namespace optflow_farneback
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static oclMat allocMatFromBuf(int rows, int cols, int type, oclMat &mat)
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{
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if (!mat.empty() && mat.type() == type && mat.rows >= rows && mat.cols >= cols)
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return mat(Rect(0, 0, cols, rows));
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return mat = oclMat(rows, cols, type);
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}
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cv::ocl::FarnebackOpticalFlow::FarnebackOpticalFlow()
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{
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numLevels = 5;
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pyrScale = 0.5;
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fastPyramids = false;
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winSize = 13;
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numIters = 10;
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polyN = 5;
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polySigma = 1.1;
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flags = 0;
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}
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void cv::ocl::FarnebackOpticalFlow::releaseMemory()
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{
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frames_[0].release();
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frames_[1].release();
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pyrLevel_[0].release();
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pyrLevel_[1].release();
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M_.release();
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bufM_.release();
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R_[0].release();
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R_[1].release();
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blurredFrame_[0].release();
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blurredFrame_[1].release();
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pyramid0_.clear();
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pyramid1_.clear();
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}
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void cv::ocl::FarnebackOpticalFlow::prepareGaussian(
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int n, double sigma, float *g, float *xg, float *xxg,
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double &ig11, double &ig03, double &ig33, double &ig55)
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{
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double s = 0.;
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for (int x = -n; x <= n; x++)
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{
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g[x] = (float)std::exp(-x*x/(2*sigma*sigma));
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s += g[x];
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}
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s = 1./s;
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for (int x = -n; x <= n; x++)
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{
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g[x] = (float)(g[x]*s);
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xg[x] = (float)(x*g[x]);
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xxg[x] = (float)(x*x*g[x]);
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}
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Mat_<double> G(6, 6);
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G.setTo(0);
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for (int y = -n; y <= n; y++)
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{
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for (int x = -n; x <= n; x++)
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{
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G(0,0) += g[y]*g[x];
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G(1,1) += g[y]*g[x]*x*x;
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G(3,3) += g[y]*g[x]*x*x*x*x;
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G(5,5) += g[y]*g[x]*x*x*y*y;
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}
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}
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//G[0][0] = 1.;
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G(2,2) = G(0,3) = G(0,4) = G(3,0) = G(4,0) = G(1,1);
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G(4,4) = G(3,3);
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G(3,4) = G(4,3) = G(5,5);
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// invG:
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// [ x e e ]
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// [ y ]
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// [ y ]
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// [ e z ]
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// [ e z ]
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// [ u ]
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Mat_<double> invG = G.inv(DECOMP_CHOLESKY);
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ig11 = invG(1,1);
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ig03 = invG(0,3);
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ig33 = invG(3,3);
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ig55 = invG(5,5);
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}
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void cv::ocl::FarnebackOpticalFlow::setPolynomialExpansionConsts(int n, double sigma)
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{
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std::vector<float> buf(n*6 + 3);
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float* g = &buf[0] + n;
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float* xg = g + n*2 + 1;
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float* xxg = xg + n*2 + 1;
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if (sigma < FLT_EPSILON)
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sigma = n*0.3;
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double ig11, ig03, ig33, ig55;
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prepareGaussian(n, sigma, g, xg, xxg, ig11, ig03, ig33, ig55);
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cv::Mat t_g(1, n + 1, CV_32FC1, g);
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cv::Mat t_xg(1, n + 1, CV_32FC1, xg);
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cv::Mat t_xxg(1, n + 1, CV_32FC1, xxg);
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optflow_farneback::g.upload(t_g);
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optflow_farneback::xg.upload(t_xg);
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optflow_farneback::xxg.upload(t_xxg);
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optflow_farneback::ig[0] = static_cast<float>(ig11);
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optflow_farneback::ig[1] = static_cast<float>(ig03);
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optflow_farneback::ig[2] = static_cast<float>(ig33);
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optflow_farneback::ig[3] = static_cast<float>(ig55);
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}
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void cv::ocl::FarnebackOpticalFlow::updateFlow_boxFilter(
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const oclMat& R0, const oclMat& R1, oclMat& flowx, oclMat &flowy,
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oclMat& M, oclMat &bufM, int blockSize, bool updateMatrices)
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{
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optflow_farneback::boxFilter5Ocl(M, blockSize/2, bufM);
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swap(M, bufM);
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optflow_farneback::updateFlowOcl(M, flowx, flowy);
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if (updateMatrices)
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optflow_farneback::updateMatricesOcl(flowx, flowy, R0, R1, M);
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}
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void cv::ocl::FarnebackOpticalFlow::updateFlow_gaussianBlur(
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const oclMat& R0, const oclMat& R1, oclMat& flowx, oclMat& flowy,
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oclMat& M, oclMat &bufM, int blockSize, bool updateMatrices)
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{
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optflow_farneback::gaussianBlur5Ocl(M, blockSize/2, bufM);
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swap(M, bufM);
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optflow_farneback::updateFlowOcl(M, flowx, flowy);
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if (updateMatrices)
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optflow_farneback::updateMatricesOcl(flowx, flowy, R0, R1, M);
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}
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void cv::ocl::FarnebackOpticalFlow::operator ()(
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const oclMat &frame0, const oclMat &frame1, oclMat &flowx, oclMat &flowy)
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{
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CV_Assert(frame0.channels() == 1 && frame1.channels() == 1);
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CV_Assert(frame0.size() == frame1.size());
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CV_Assert(polyN == 5 || polyN == 7);
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CV_Assert(!fastPyramids || std::abs(pyrScale - 0.5) < 1e-6);
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Size size = frame0.size();
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oclMat prevFlowX, prevFlowY, curFlowX, curFlowY;
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flowx.create(size, CV_32F);
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flowy.create(size, CV_32F);
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oclMat flowx0 = flowx;
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oclMat flowy0 = flowy;
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// Crop unnecessary levels
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double scale = 1;
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int numLevelsCropped = 0;
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for (; numLevelsCropped < numLevels; numLevelsCropped++)
|
|
{
|
|
scale *= pyrScale;
|
|
if (size.width*scale < MIN_SIZE || size.height*scale < MIN_SIZE)
|
|
break;
|
|
}
|
|
|
|
frame0.convertTo(frames_[0], CV_32F);
|
|
frame1.convertTo(frames_[1], CV_32F);
|
|
|
|
if (fastPyramids)
|
|
{
|
|
// Build Gaussian pyramids using pyrDown()
|
|
pyramid0_.resize(numLevelsCropped + 1);
|
|
pyramid1_.resize(numLevelsCropped + 1);
|
|
pyramid0_[0] = frames_[0];
|
|
pyramid1_[0] = frames_[1];
|
|
for (int i = 1; i <= numLevelsCropped; ++i)
|
|
{
|
|
pyrDown(pyramid0_[i - 1], pyramid0_[i]);
|
|
pyrDown(pyramid1_[i - 1], pyramid1_[i]);
|
|
}
|
|
}
|
|
|
|
setPolynomialExpansionConsts(polyN, polySigma);
|
|
|
|
for (int k = numLevelsCropped; k >= 0; k--)
|
|
{
|
|
scale = 1;
|
|
for (int i = 0; i < k; i++)
|
|
scale *= pyrScale;
|
|
|
|
double sigma = (1./scale - 1) * 0.5;
|
|
int smoothSize = cvRound(sigma*5) | 1;
|
|
smoothSize = std::max(smoothSize, 3);
|
|
|
|
int width = cvRound(size.width*scale);
|
|
int height = cvRound(size.height*scale);
|
|
|
|
if (fastPyramids)
|
|
{
|
|
width = pyramid0_[k].cols;
|
|
height = pyramid0_[k].rows;
|
|
}
|
|
|
|
if (k > 0)
|
|
{
|
|
curFlowX.create(height, width, CV_32F);
|
|
curFlowY.create(height, width, CV_32F);
|
|
}
|
|
else
|
|
{
|
|
curFlowX = flowx0;
|
|
curFlowY = flowy0;
|
|
}
|
|
|
|
if (!prevFlowX.data)
|
|
{
|
|
if (flags & cv::OPTFLOW_USE_INITIAL_FLOW)
|
|
{
|
|
resize(flowx0, curFlowX, Size(width, height), 0, 0, INTER_LINEAR);
|
|
resize(flowy0, curFlowY, Size(width, height), 0, 0, INTER_LINEAR);
|
|
multiply(scale, curFlowX, curFlowX);
|
|
multiply(scale, curFlowY, curFlowY);
|
|
}
|
|
else
|
|
{
|
|
curFlowX.setTo(0);
|
|
curFlowY.setTo(0);
|
|
}
|
|
}
|
|
else
|
|
{
|
|
resize(prevFlowX, curFlowX, Size(width, height), 0, 0, INTER_LINEAR);
|
|
resize(prevFlowY, curFlowY, Size(width, height), 0, 0, INTER_LINEAR);
|
|
multiply(1./pyrScale, curFlowX, curFlowX);
|
|
multiply(1./pyrScale, curFlowY, curFlowY);
|
|
}
|
|
|
|
oclMat M = allocMatFromBuf(5*height, width, CV_32F, M_);
|
|
oclMat bufM = allocMatFromBuf(5*height, width, CV_32F, bufM_);
|
|
oclMat R[2] =
|
|
{
|
|
allocMatFromBuf(5*height, width, CV_32F, R_[0]),
|
|
allocMatFromBuf(5*height, width, CV_32F, R_[1])
|
|
};
|
|
|
|
if (fastPyramids)
|
|
{
|
|
optflow_farneback::polynomialExpansionOcl(pyramid0_[k], polyN, R[0]);
|
|
optflow_farneback::polynomialExpansionOcl(pyramid1_[k], polyN, R[1]);
|
|
}
|
|
else
|
|
{
|
|
oclMat blurredFrame[2] =
|
|
{
|
|
allocMatFromBuf(size.height, size.width, CV_32F, blurredFrame_[0]),
|
|
allocMatFromBuf(size.height, size.width, CV_32F, blurredFrame_[1])
|
|
};
|
|
oclMat pyrLevel[2] =
|
|
{
|
|
allocMatFromBuf(height, width, CV_32F, pyrLevel_[0]),
|
|
allocMatFromBuf(height, width, CV_32F, pyrLevel_[1])
|
|
};
|
|
|
|
Mat g = getGaussianKernel(smoothSize, sigma, CV_32F);
|
|
optflow_farneback::setGaussianBlurKernel(g.ptr<float>(smoothSize/2), smoothSize/2);
|
|
|
|
for (int i = 0; i < 2; i++)
|
|
{
|
|
optflow_farneback::gaussianBlurOcl(frames_[i], smoothSize/2, blurredFrame[i]);
|
|
resize(blurredFrame[i], pyrLevel[i], Size(width, height), INTER_LINEAR);
|
|
optflow_farneback::polynomialExpansionOcl(pyrLevel[i], polyN, R[i]);
|
|
}
|
|
}
|
|
|
|
optflow_farneback::updateMatricesOcl(curFlowX, curFlowY, R[0], R[1], M);
|
|
|
|
if (flags & OPTFLOW_FARNEBACK_GAUSSIAN)
|
|
{
|
|
Mat g = getGaussianKernel(winSize, winSize/2*0.3f, CV_32F);
|
|
optflow_farneback::setGaussianBlurKernel(g.ptr<float>(winSize/2), winSize/2);
|
|
}
|
|
for (int i = 0; i < numIters; i++)
|
|
{
|
|
if (flags & OPTFLOW_FARNEBACK_GAUSSIAN)
|
|
updateFlow_gaussianBlur(R[0], R[1], curFlowX, curFlowY, M, bufM, winSize, i < numIters-1);
|
|
else
|
|
updateFlow_boxFilter(R[0], R[1], curFlowX, curFlowY, M, bufM, winSize, i < numIters-1);
|
|
}
|
|
|
|
prevFlowX = curFlowX;
|
|
prevFlowY = curFlowY;
|
|
}
|
|
|
|
flowx = curFlowX;
|
|
flowy = curFlowY;
|
|
}
|