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Open Source Computer Vision Library
https://opencv.org/
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222 lines
5.8 KiB
222 lines
5.8 KiB
#include "perf_cpu_precomp.hpp" |
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#ifdef HAVE_CUDA |
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////////////////////////////////////////////////////// |
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// GoodFeaturesToTrack |
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IMPLEMENT_PARAM_CLASS(MinDistance, double) |
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GPU_PERF_TEST(GoodFeaturesToTrack, cv::gpu::DeviceInfo, MinDistance) |
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{ |
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double minDistance = GET_PARAM(1); |
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cv::Mat image = readImage("gpu/perf/aloe.jpg", cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(image.empty()); |
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cv::Mat corners; |
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cv::goodFeaturesToTrack(image, corners, 8000, 0.01, minDistance); |
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TEST_CYCLE() |
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{ |
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cv::goodFeaturesToTrack(image, corners, 8000, 0.01, minDistance); |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(Video, GoodFeaturesToTrack, testing::Combine( |
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ALL_DEVICES, |
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testing::Values(MinDistance(0.0), MinDistance(3.0)))); |
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////////////////////////////////////////////////////// |
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// PyrLKOpticalFlowSparse |
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IMPLEMENT_PARAM_CLASS(GraySource, bool) |
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IMPLEMENT_PARAM_CLASS(Points, int) |
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IMPLEMENT_PARAM_CLASS(WinSize, int) |
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GPU_PERF_TEST(PyrLKOpticalFlowSparse, cv::gpu::DeviceInfo, GraySource, Points, WinSize) |
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{ |
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bool useGray = GET_PARAM(1); |
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int points = GET_PARAM(2); |
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int win_size = GET_PARAM(3); |
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cv::Mat frame0 = readImage("gpu/opticalflow/frame0.png", useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR); |
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ASSERT_FALSE(frame0.empty()); |
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cv::Mat frame1 = readImage("gpu/opticalflow/frame1.png", 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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cv::Mat nextPts; |
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cv::Mat status; |
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cv::calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, cv::noArray(), cv::Size(win_size, win_size)); |
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TEST_CYCLE() |
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{ |
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cv::calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, cv::noArray(), cv::Size(win_size, win_size)); |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(Video, PyrLKOpticalFlowSparse, testing::Combine( |
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ALL_DEVICES, |
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testing::Values(GraySource(true), GraySource(false)), |
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testing::Values(Points(1000), Points(2000), Points(4000), Points(8000)), |
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testing::Values(WinSize(17), WinSize(21)))); |
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////////////////////////////////////////////////////// |
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// FarnebackOpticalFlowTest |
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GPU_PERF_TEST_1(FarnebackOpticalFlowTest, cv::gpu::DeviceInfo) |
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{ |
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cv::Mat frame0 = readImage("gpu/opticalflow/frame0.png", cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(frame0.empty()); |
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cv::Mat frame1 = readImage("gpu/opticalflow/frame1.png", cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(frame1.empty()); |
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cv::Mat flow; |
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int numLevels = 5; |
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double pyrScale = 0.5; |
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int winSize = 13; |
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int numIters = 10; |
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int polyN = 5; |
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double polySigma = 1.1; |
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int flags = 0; |
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cv::calcOpticalFlowFarneback(frame0, frame1, flow, pyrScale, numLevels, winSize, numIters, polyN, polySigma, flags); |
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declare.time(10); |
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TEST_CYCLE() |
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{ |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(Video, FarnebackOpticalFlowTest, ALL_DEVICES); |
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////////////////////////////////////////////////////// |
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// FGDStatModel |
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namespace cv |
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{ |
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template<> void Ptr<CvBGStatModel>::delete_obj() |
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{ |
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cvReleaseBGStatModel(&obj); |
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} |
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} |
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GPU_PERF_TEST(FGDStatModel, cv::gpu::DeviceInfo, std::string) |
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{ |
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std::string inputFile = perf::TestBase::getDataPath(std::string("gpu/video/") + GET_PARAM(1)); |
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cv::VideoCapture cap(inputFile); |
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ASSERT_TRUE(cap.isOpened()); |
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cv::Mat frame; |
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cap >> frame; |
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ASSERT_FALSE(frame.empty()); |
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IplImage ipl_frame = frame; |
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cv::Ptr<CvBGStatModel> model(cvCreateFGDStatModel(&ipl_frame)); |
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declare.time(60); |
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for (int i = 0; i < 10; ++i) |
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{ |
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cap >> frame; |
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ASSERT_FALSE(frame.empty()); |
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ipl_frame = frame; |
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startTimer(); |
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next(); |
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cvUpdateBGStatModel(&ipl_frame, model); |
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stopTimer(); |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(Video, FGDStatModel, testing::Combine( |
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ALL_DEVICES, |
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testing::Values(std::string("768x576.avi"), std::string("1920x1080.avi")))); |
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////////////////////////////////////////////////////// |
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// VideoWriter |
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#ifdef WIN32 |
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GPU_PERF_TEST(VideoWriter, cv::gpu::DeviceInfo, std::string) |
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{ |
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const double FPS = 25.0; |
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std::string inputFile = perf::TestBase::getDataPath(std::string("gpu/video/") + GET_PARAM(1)); |
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std::string outputFile = inputFile.substr(0, inputFile.find('.')) + "_test.avi"; |
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cv::VideoCapture reader(inputFile); |
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ASSERT_TRUE( reader.isOpened() ); |
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cv::VideoWriter writer; |
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cv::Mat frame; |
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declare.time(30); |
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for (int i = 0; i < 10; ++i) |
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{ |
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reader >> frame; |
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ASSERT_FALSE(frame.empty()); |
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if (!writer.isOpened()) |
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writer.open(outputFile, CV_FOURCC('X', 'V', 'I', 'D'), FPS, frame.size()); |
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startTimer(); next(); |
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writer.write(frame); |
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stopTimer(); |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(Video, VideoWriter, testing::Combine( |
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ALL_DEVICES, |
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testing::Values(std::string("768x576.avi"), std::string("1920x1080.avi")))); |
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#endif // WIN32 |
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////////////////////////////////////////////////////// |
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// VideoReader |
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GPU_PERF_TEST(VideoReader, cv::gpu::DeviceInfo, std::string) |
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{ |
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std::string inputFile = perf::TestBase::getDataPath(std::string("gpu/video/") + GET_PARAM(1)); |
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cv::VideoCapture reader(inputFile); |
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ASSERT_TRUE( reader.isOpened() ); |
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cv::Mat frame; |
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reader >> frame; |
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declare.time(20); |
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TEST_CYCLE_N(10) |
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{ |
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reader >> frame; |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(Video, VideoReader, testing::Combine( |
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ALL_DEVICES, |
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testing::Values(std::string("768x576.avi"), std::string("1920x1080.avi")))); |
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#endif
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