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https://github.com/opencv/opencv.git
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399 lines
11 KiB
C++
399 lines
11 KiB
C++
#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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IMPLEMENT_PARAM_CLASS(Levels, int)
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IMPLEMENT_PARAM_CLASS(Iters, int)
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GPU_PERF_TEST(PyrLKOpticalFlowSparse, cv::gpu::DeviceInfo, GraySource, Points, WinSize, Levels, Iters)
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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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int levels = GET_PARAM(4);
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int iters = GET_PARAM(5);
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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(),
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cv::Size(win_size, win_size), levels - 1,
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cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, iters, 0.01));
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declare.time(20.0);
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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(win_size, win_size), 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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}
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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(9), WinSize(13), WinSize(17), WinSize(21)),
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testing::Values(Levels(1), Levels(2), Levels(3)),
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testing::Values(Iters(1), Iters(10), Iters(30))));
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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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cv::calcOpticalFlowFarneback(frame0, frame1, flow, pyrScale, numLevels, winSize, numIters, polyN, polySigma, flags);
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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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// MOG
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IMPLEMENT_PARAM_CLASS(LearningRate, double)
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GPU_PERF_TEST(MOG, cv::gpu::DeviceInfo, std::string, Channels, LearningRate)
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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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int cn = GET_PARAM(2);
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double learningRate = GET_PARAM(3);
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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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cv::BackgroundSubtractorMOG mog;
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cv::Mat foreground;
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cap >> frame;
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ASSERT_FALSE(frame.empty());
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if (cn != 3)
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{
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cv::Mat temp;
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if (cn == 1)
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cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
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else
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cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
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cv::swap(temp, frame);
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}
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mog(frame, foreground, learningRate);
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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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if (cn != 3)
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{
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cv::Mat temp;
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if (cn == 1)
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cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
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else
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cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
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cv::swap(temp, frame);
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}
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startTimer(); next();
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mog(frame, foreground, learningRate);
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stopTimer();
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}
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}
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INSTANTIATE_TEST_CASE_P(Video, MOG, 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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testing::Values(Channels(1), Channels(3)/*, Channels(4)*/),
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testing::Values(LearningRate(0.0), LearningRate(0.01))));
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//////////////////////////////////////////////////////
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// MOG2
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GPU_PERF_TEST(MOG2_update, cv::gpu::DeviceInfo, std::string, Channels)
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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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int cn = GET_PARAM(2);
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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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cv::BackgroundSubtractorMOG2 mog2;
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cv::Mat foreground;
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cap >> frame;
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ASSERT_FALSE(frame.empty());
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if (cn != 3)
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{
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cv::Mat temp;
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if (cn == 1)
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cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
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else
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cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
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cv::swap(temp, frame);
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}
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mog2(frame, foreground);
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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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if (cn != 3)
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{
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cv::Mat temp;
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if (cn == 1)
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cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
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else
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cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
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cv::swap(temp, frame);
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}
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startTimer(); next();
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mog2(frame, foreground);
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stopTimer();
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}
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}
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INSTANTIATE_TEST_CASE_P(Video, MOG2_update, 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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testing::Values(Channels(1), Channels(3)/*, Channels(4)*/)));
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GPU_PERF_TEST(MOG2_getBackgroundImage, cv::gpu::DeviceInfo, std::string, Channels)
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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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int cn = GET_PARAM(2);
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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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cv::BackgroundSubtractorMOG2 mog2;
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cv::Mat foreground;
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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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if (cn != 3)
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{
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cv::Mat temp;
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if (cn == 1)
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cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
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else
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cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
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cv::swap(temp, frame);
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}
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mog2(frame, foreground);
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}
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cv::Mat background;
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mog2.getBackgroundImage(background);
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TEST_CYCLE()
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{
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mog2.getBackgroundImage(background);
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}
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}
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INSTANTIATE_TEST_CASE_P(Video, MOG2_getBackgroundImage, 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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testing::Values(/*Channels(1),*/ Channels(3)/*, Channels(4)*/)));
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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 = cv::tempfile(".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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