/* * By downloading, copying, installing or using the software you agree to this license. * If you do not agree to this license, do not download, install, * copy or use the software. * * * License Agreement * For Open Source Computer Vision Library * (3 - clause BSD License) * * Redistribution and use in source and binary forms, with or without modification, * are permitted provided that the following conditions are met : * * * Redistributions of source code must retain the above copyright notice, * this list of conditions and the following disclaimer. * * * Redistributions in binary form must reproduce the above copyright notice, * this list of conditions and the following disclaimer in the documentation * and / or other materials provided with the distribution. * * * Neither the names of the copyright holders nor the names of the contributors * may be used to endorse or promote products derived from this software * without specific prior written permission. * * This software is provided by the copyright holders and contributors "as is" and * any express or implied warranties, including, but not limited to, the implied * warranties of merchantability and fitness for a particular purpose are disclaimed. * In no event shall copyright holders or contributors be liable for any direct, * indirect, incidental, special, exemplary, or consequential damages * (including, but not limited to, procurement of substitute goods or services; * loss of use, data, or profits; or business interruption) however caused * and on any theory of liability, whether in contract, strict liability, * or tort(including negligence or otherwise) arising in any way out of * the use of this software, even if advised of the possibility of such damage. */ #include "perf_precomp.hpp" using std::tr1::tuple; using std::tr1::get; using namespace perf; using namespace testing; using namespace cv; using namespace cv::optflow; void MakeArtificialExample(Mat &dst_frame1, Mat &dst_frame2); typedef tuple<String, Size> DISParams; typedef TestBaseWithParam<DISParams> DenseOpticalFlow_DIS; PERF_TEST_P(DenseOpticalFlow_DIS, perf, Combine(Values("PRESET_ULTRAFAST", "PRESET_FAST", "PRESET_MEDIUM"), Values(szVGA, sz720p, sz1080p))) { DISParams params = GetParam(); // use strings to print preset names in the perf test results: String preset_string = get<0>(params); int preset = DISOpticalFlow::PRESET_FAST; if (preset_string == "PRESET_ULTRAFAST") preset = DISOpticalFlow::PRESET_ULTRAFAST; else if (preset_string == "PRESET_FAST") preset = DISOpticalFlow::PRESET_FAST; else if (preset_string == "PRESET_MEDIUM") preset = DISOpticalFlow::PRESET_MEDIUM; Size sz = get<1>(params); Mat frame1(sz, CV_8U); Mat frame2(sz, CV_8U); Mat flow; MakeArtificialExample(frame1, frame2); cv::setNumThreads(cv::getNumberOfCPUs()); TEST_CYCLE_N(10) { Ptr<DenseOpticalFlow> algo = createOptFlow_DIS(preset); algo->calc(frame1, frame2, flow); } SANITY_CHECK_NOTHING(); } void MakeArtificialExample(Mat &dst_frame1, Mat &dst_frame2) { int src_scale = 2; int OF_scale = 6; double sigma = dst_frame1.cols / 300; Mat tmp(Size(dst_frame1.cols / (int)pow(2, src_scale), dst_frame1.rows / (int)pow(2, src_scale)), CV_8U); randu(tmp, 0, 255); resize(tmp, dst_frame1, dst_frame1.size(), 0.0, 0.0, INTER_LINEAR); resize(tmp, dst_frame2, dst_frame2.size(), 0.0, 0.0, INTER_LINEAR); Mat displacement_field(Size(dst_frame1.cols / (int)pow(2, OF_scale), dst_frame1.rows / (int)pow(2, OF_scale)), CV_32FC2); randn(displacement_field, 0.0, sigma); resize(displacement_field, displacement_field, dst_frame2.size(), 0.0, 0.0, INTER_CUBIC); for (int i = 0; i < displacement_field.rows; i++) for (int j = 0; j < displacement_field.cols; j++) displacement_field.at<Vec2f>(i, j) += Vec2f((float)j, (float)i); remap(dst_frame2, dst_frame2, displacement_field, Mat(), INTER_LINEAR, BORDER_REPLICATE); }