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Open Source Computer Vision Library
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321 lines
10 KiB
321 lines
10 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) 2000-2008, Intel Corporation, all rights reserved. |
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// Copyright (C) 2009, Willow Garage 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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// 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 "perf_precomp.hpp" |
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using namespace std; |
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using namespace testing; |
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using namespace perf; |
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typedef pair<string, string> pair_string; |
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DEF_PARAM_TEST_1(ImagePair, pair_string); |
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////////////////////////////////////////////////////// |
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// BroxOpticalFlow |
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PERF_TEST_P(ImagePair, BroxOpticalFlow, |
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Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png"))) |
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{ |
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declare.time(300); |
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cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(frame0.empty()); |
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cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(frame1.empty()); |
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frame0.convertTo(frame0, CV_32FC1, 1.0 / 255.0); |
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frame1.convertTo(frame1, CV_32FC1, 1.0 / 255.0); |
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if (PERF_RUN_CUDA()) |
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{ |
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const cv::cuda::GpuMat d_frame0(frame0); |
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const cv::cuda::GpuMat d_frame1(frame1); |
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cv::cuda::GpuMat flow; |
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cv::Ptr<cv::cuda::BroxOpticalFlow> d_alg = |
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cv::cuda::BroxOpticalFlow::create(0.197 /*alpha*/, 50.0 /*gamma*/, 0.8 /*scale_factor*/, |
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10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/); |
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TEST_CYCLE() d_alg->calc(d_frame0, d_frame1, flow); |
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cv::cuda::GpuMat flows[2]; |
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cv::cuda::split(flow, flows); |
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cv::cuda::GpuMat u = flows[0]; |
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cv::cuda::GpuMat v = flows[1]; |
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CUDA_SANITY_CHECK(u, 1e-1); |
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CUDA_SANITY_CHECK(v, 1e-1); |
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} |
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else |
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{ |
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FAIL_NO_CPU(); |
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} |
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} |
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////////////////////////////////////////////////////// |
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// PyrLKOpticalFlowSparse |
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DEF_PARAM_TEST(ImagePair_Gray_NPts_WinSz_Levels_Iters, pair_string, bool, int, int, int, int); |
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PERF_TEST_P(ImagePair_Gray_NPts_WinSz_Levels_Iters, PyrLKOpticalFlowSparse, |
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Combine(Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")), |
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Bool(), |
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Values(8000), |
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Values(21), |
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Values(1, 3), |
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Values(1, 30))) |
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{ |
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declare.time(20.0); |
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const pair_string imagePair = GET_PARAM(0); |
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const bool useGray = GET_PARAM(1); |
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const int points = GET_PARAM(2); |
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const int winSize = GET_PARAM(3); |
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const int levels = GET_PARAM(4); |
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const int iters = GET_PARAM(5); |
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const cv::Mat frame0 = readImage(imagePair.first, useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR); |
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ASSERT_FALSE(frame0.empty()); |
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const cv::Mat frame1 = readImage(imagePair.second, useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR); |
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ASSERT_FALSE(frame1.empty()); |
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cv::Mat gray_frame; |
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if (useGray) |
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gray_frame = frame0; |
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else |
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cv::cvtColor(frame0, gray_frame, cv::COLOR_BGR2GRAY); |
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cv::Mat pts; |
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cv::goodFeaturesToTrack(gray_frame, pts, points, 0.01, 0.0); |
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if (PERF_RUN_CUDA()) |
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{ |
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const cv::cuda::GpuMat d_pts(pts.reshape(2, 1)); |
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cv::Ptr<cv::cuda::SparsePyrLKOpticalFlow> d_pyrLK = |
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cv::cuda::SparsePyrLKOpticalFlow::create(cv::Size(winSize, winSize), |
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levels - 1, |
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iters); |
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const cv::cuda::GpuMat d_frame0(frame0); |
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const cv::cuda::GpuMat d_frame1(frame1); |
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cv::cuda::GpuMat nextPts; |
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cv::cuda::GpuMat status; |
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TEST_CYCLE() d_pyrLK->calc(d_frame0, d_frame1, d_pts, nextPts, status); |
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CUDA_SANITY_CHECK(nextPts); |
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CUDA_SANITY_CHECK(status); |
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} |
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else |
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{ |
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cv::Mat nextPts; |
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cv::Mat status; |
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TEST_CYCLE() |
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{ |
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cv::calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, cv::noArray(), |
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cv::Size(winSize, winSize), levels - 1, |
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cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, iters, 0.01)); |
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} |
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CPU_SANITY_CHECK(nextPts); |
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CPU_SANITY_CHECK(status); |
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} |
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} |
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////////////////////////////////////////////////////// |
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// PyrLKOpticalFlowDense |
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DEF_PARAM_TEST(ImagePair_WinSz_Levels_Iters, pair_string, int, int, int); |
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PERF_TEST_P(ImagePair_WinSz_Levels_Iters, PyrLKOpticalFlowDense, |
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Combine(Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")), |
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Values(3, 5, 7, 9, 13, 17, 21), |
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Values(1, 3), |
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Values(1, 10))) |
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{ |
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declare.time(30); |
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const pair_string imagePair = GET_PARAM(0); |
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const int winSize = GET_PARAM(1); |
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const int levels = GET_PARAM(2); |
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const int iters = GET_PARAM(3); |
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const cv::Mat frame0 = readImage(imagePair.first, cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(frame0.empty()); |
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const cv::Mat frame1 = readImage(imagePair.second, cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(frame1.empty()); |
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if (PERF_RUN_CUDA()) |
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{ |
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const cv::cuda::GpuMat d_frame0(frame0); |
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const cv::cuda::GpuMat d_frame1(frame1); |
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cv::cuda::GpuMat flow; |
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cv::Ptr<cv::cuda::DensePyrLKOpticalFlow> d_pyrLK = |
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cv::cuda::DensePyrLKOpticalFlow::create(cv::Size(winSize, winSize), |
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levels - 1, |
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iters); |
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TEST_CYCLE() d_pyrLK->calc(d_frame0, d_frame1, flow); |
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cv::cuda::GpuMat flows[2]; |
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cv::cuda::split(flow, flows); |
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cv::cuda::GpuMat u = flows[0]; |
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cv::cuda::GpuMat v = flows[1]; |
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// Sanity test fails on Maxwell and CUDA 7.0 |
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SANITY_CHECK_NOTHING(); |
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} |
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else |
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{ |
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FAIL_NO_CPU(); |
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} |
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} |
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////////////////////////////////////////////////////// |
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// FarnebackOpticalFlow |
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PERF_TEST_P(ImagePair, FarnebackOpticalFlow, |
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Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png"))) |
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{ |
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declare.time(10); |
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const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(frame0.empty()); |
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const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(frame1.empty()); |
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const int numLevels = 5; |
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const double pyrScale = 0.5; |
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const int winSize = 13; |
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const int numIters = 10; |
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const int polyN = 5; |
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const double polySigma = 1.1; |
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const int flags = 0; |
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if (PERF_RUN_CUDA()) |
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{ |
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const cv::cuda::GpuMat d_frame0(frame0); |
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const cv::cuda::GpuMat d_frame1(frame1); |
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cv::cuda::GpuMat flow; |
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cv::Ptr<cv::cuda::FarnebackOpticalFlow> d_farneback = |
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cv::cuda::FarnebackOpticalFlow::create(numLevels, pyrScale, false, winSize, |
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numIters, polyN, polySigma, flags); |
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TEST_CYCLE() d_farneback->calc(d_frame0, d_frame1, flow); |
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cv::cuda::GpuMat flows[2]; |
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cv::cuda::split(flow, flows); |
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cv::cuda::GpuMat u = flows[0]; |
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cv::cuda::GpuMat v = flows[1]; |
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CUDA_SANITY_CHECK(u, 1e-4); |
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CUDA_SANITY_CHECK(v, 1e-4); |
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} |
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else |
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{ |
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cv::Mat flow; |
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TEST_CYCLE() cv::calcOpticalFlowFarneback(frame0, frame1, flow, pyrScale, numLevels, winSize, numIters, polyN, polySigma, flags); |
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CPU_SANITY_CHECK(flow); |
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} |
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} |
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////////////////////////////////////////////////////// |
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// OpticalFlowDual_TVL1 |
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PERF_TEST_P(ImagePair, OpticalFlowDual_TVL1, |
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Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png"))) |
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{ |
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declare.time(20); |
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const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(frame0.empty()); |
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const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(frame1.empty()); |
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if (PERF_RUN_CUDA()) |
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{ |
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const cv::cuda::GpuMat d_frame0(frame0); |
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const cv::cuda::GpuMat d_frame1(frame1); |
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cv::cuda::GpuMat flow; |
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cv::Ptr<cv::cuda::OpticalFlowDual_TVL1> d_alg = |
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cv::cuda::OpticalFlowDual_TVL1::create(); |
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TEST_CYCLE() d_alg->calc(d_frame0, d_frame1, flow); |
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cv::cuda::GpuMat flows[2]; |
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cv::cuda::split(flow, flows); |
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cv::cuda::GpuMat u = flows[0]; |
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cv::cuda::GpuMat v = flows[1]; |
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CUDA_SANITY_CHECK(u, 1e-1); |
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CUDA_SANITY_CHECK(v, 1e-1); |
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} |
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else |
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{ |
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cv::Mat flow; |
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cv::Ptr<cv::DualTVL1OpticalFlow> alg = cv::createOptFlow_DualTVL1(); |
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alg->setMedianFiltering(1); |
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alg->setInnerIterations(1); |
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alg->setOuterIterations(300); |
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TEST_CYCLE() alg->calc(frame0, frame1, flow); |
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CPU_SANITY_CHECK(flow); |
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} |
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}
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