/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "perf_precomp.hpp" using namespace std; using namespace testing; using namespace perf; typedef pair pair_string; DEF_PARAM_TEST_1(ImagePair, pair_string); ////////////////////////////////////////////////////// // BroxOpticalFlow PERF_TEST_P(ImagePair, BroxOpticalFlow, Values(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png"))) { declare.time(300); cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE); ASSERT_FALSE(frame0.empty()); cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE); ASSERT_FALSE(frame1.empty()); frame0.convertTo(frame0, CV_32FC1, 1.0 / 255.0); frame1.convertTo(frame1, CV_32FC1, 1.0 / 255.0); if (PERF_RUN_CUDA()) { const cv::cuda::GpuMat d_frame0(frame0); const cv::cuda::GpuMat d_frame1(frame1); cv::cuda::GpuMat flow; cv::Ptr d_alg = cv::cuda::BroxOpticalFlow::create(0.197 /*alpha*/, 50.0 /*gamma*/, 0.8 /*scale_factor*/, 10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/); TEST_CYCLE() d_alg->calc(d_frame0, d_frame1, flow); cv::cuda::GpuMat flows[2]; cv::cuda::split(flow, flows); cv::cuda::GpuMat u = flows[0]; cv::cuda::GpuMat v = flows[1]; CUDA_SANITY_CHECK(u, 1e-1); CUDA_SANITY_CHECK(v, 1e-1); } else { FAIL_NO_CPU(); } } ////////////////////////////////////////////////////// // PyrLKOpticalFlowSparse DEF_PARAM_TEST(ImagePair_Gray_NPts_WinSz_Levels_Iters, pair_string, bool, int, int, int, int); PERF_TEST_P(ImagePair_Gray_NPts_WinSz_Levels_Iters, PyrLKOpticalFlowSparse, Combine(Values(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")), Bool(), Values(8000), Values(21), Values(1, 3), Values(1, 30))) { declare.time(20.0); const pair_string imagePair = GET_PARAM(0); const bool useGray = GET_PARAM(1); const int points = GET_PARAM(2); const int winSize = GET_PARAM(3); const int levels = GET_PARAM(4); const int iters = GET_PARAM(5); cv::Mat frame0 = readImage(imagePair.first, useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR); ASSERT_FALSE(frame0.empty()); cv::Mat frame1 = readImage(imagePair.second, useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR); ASSERT_FALSE(frame1.empty()); cv::Mat gray_frame; if (useGray) gray_frame = frame0; else cv::cvtColor(frame0, gray_frame, cv::COLOR_BGR2GRAY); cv::Mat pts; cv::goodFeaturesToTrack(gray_frame, pts, points, 0.01, 0.0); frame0.convertTo(frame0, CV_32F); frame1.convertTo(frame1, CV_32F); if(!useGray) { cv::cvtColor(frame0, frame0, cv::COLOR_BGR2BGRA); cv::cvtColor(frame1, frame1, cv::COLOR_BGR2BGRA); } if (PERF_RUN_CUDA()) { const cv::cuda::GpuMat d_pts(pts.reshape(2, 1)); cv::Ptr d_pyrLK = cv::cuda::SparsePyrLKOpticalFlow::create(cv::Size(winSize, winSize), levels - 1, iters); const cv::cuda::GpuMat d_frame0(frame0); const cv::cuda::GpuMat d_frame1(frame1); cv::cuda::GpuMat nextPts; cv::cuda::GpuMat status; TEST_CYCLE() d_pyrLK->calc(d_frame0, d_frame1, d_pts, nextPts, status); CUDA_SANITY_CHECK(nextPts); CUDA_SANITY_CHECK(status); } else { cv::Mat nextPts; cv::Mat status; TEST_CYCLE() { cv::calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, cv::noArray(), cv::Size(winSize, winSize), levels - 1, cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, iters, 0.01)); } CPU_SANITY_CHECK(nextPts); CPU_SANITY_CHECK(status); } } ////////////////////////////////////////////////////// // PyrLKOpticalFlowDense DEF_PARAM_TEST(ImagePair_WinSz_Levels_Iters, pair_string, int, int, int); PERF_TEST_P(ImagePair_WinSz_Levels_Iters, PyrLKOpticalFlowDense, Combine(Values(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")), Values(3, 5, 7, 9, 13, 17, 21), Values(1, 3), Values(1, 10))) { declare.time(30); const pair_string imagePair = GET_PARAM(0); const int winSize = GET_PARAM(1); const int levels = GET_PARAM(2); const int iters = GET_PARAM(3); const cv::Mat frame0 = readImage(imagePair.first, cv::IMREAD_GRAYSCALE); ASSERT_FALSE(frame0.empty()); const cv::Mat frame1 = readImage(imagePair.second, cv::IMREAD_GRAYSCALE); ASSERT_FALSE(frame1.empty()); if (PERF_RUN_CUDA()) { const cv::cuda::GpuMat d_frame0(frame0); const cv::cuda::GpuMat d_frame1(frame1); cv::cuda::GpuMat flow; cv::Ptr d_pyrLK = cv::cuda::DensePyrLKOpticalFlow::create(cv::Size(winSize, winSize), levels - 1, iters); TEST_CYCLE() d_pyrLK->calc(d_frame0, d_frame1, flow); cv::cuda::GpuMat flows[2]; cv::cuda::split(flow, flows); cv::cuda::GpuMat u = flows[0]; cv::cuda::GpuMat v = flows[1]; // Sanity test fails on Maxwell and CUDA 7.0 SANITY_CHECK_NOTHING(); } else { FAIL_NO_CPU(); } } ////////////////////////////////////////////////////// // FarnebackOpticalFlow PERF_TEST_P(ImagePair, FarnebackOpticalFlow, Values(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png"))) { declare.time(10); const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE); ASSERT_FALSE(frame0.empty()); const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE); ASSERT_FALSE(frame1.empty()); const int numLevels = 5; const double pyrScale = 0.5; const int winSize = 13; const int numIters = 10; const int polyN = 5; const double polySigma = 1.1; const int flags = 0; if (PERF_RUN_CUDA()) { const cv::cuda::GpuMat d_frame0(frame0); const cv::cuda::GpuMat d_frame1(frame1); cv::cuda::GpuMat flow; cv::Ptr d_farneback = cv::cuda::FarnebackOpticalFlow::create(numLevels, pyrScale, false, winSize, numIters, polyN, polySigma, flags); TEST_CYCLE() d_farneback->calc(d_frame0, d_frame1, flow); cv::cuda::GpuMat flows[2]; cv::cuda::split(flow, flows); cv::cuda::GpuMat u = flows[0]; cv::cuda::GpuMat v = flows[1]; CUDA_SANITY_CHECK(u, 1e-4); CUDA_SANITY_CHECK(v, 1e-4); } else { cv::Mat flow; TEST_CYCLE() cv::calcOpticalFlowFarneback(frame0, frame1, flow, pyrScale, numLevels, winSize, numIters, polyN, polySigma, flags); CPU_SANITY_CHECK(flow); } } ////////////////////////////////////////////////////// // OpticalFlowDual_TVL1 PERF_TEST_P(ImagePair, OpticalFlowDual_TVL1, Values(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png"))) { declare.time(20); const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE); ASSERT_FALSE(frame0.empty()); const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE); ASSERT_FALSE(frame1.empty()); if (PERF_RUN_CUDA()) { const cv::cuda::GpuMat d_frame0(frame0); const cv::cuda::GpuMat d_frame1(frame1); cv::cuda::GpuMat flow; cv::Ptr d_alg = cv::cuda::OpticalFlowDual_TVL1::create(); TEST_CYCLE() d_alg->calc(d_frame0, d_frame1, flow); cv::cuda::GpuMat flows[2]; cv::cuda::split(flow, flows); cv::cuda::GpuMat u = flows[0]; cv::cuda::GpuMat v = flows[1]; CUDA_SANITY_CHECK(u, 1e-1); CUDA_SANITY_CHECK(v, 1e-1); } else { cv::Mat flow; cv::Ptr alg = cv::createOptFlow_DualTVL1(); alg->setMedianFiltering(1); alg->setInnerIterations(1); alg->setOuterIterations(300); TEST_CYCLE() alg->calc(frame0, frame1, flow); CPU_SANITY_CHECK(flow); } }