658 lines
18 KiB
C++
658 lines
18 KiB
C++
#include "perf_precomp.hpp"
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#ifdef HAVE_CUDA
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//////////////////////////////////////////////////////
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// BroxOpticalFlow
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GPU_PERF_TEST_1(BroxOpticalFlow, cv::gpu::DeviceInfo)
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{
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cv::gpu::DeviceInfo devInfo = GetParam();
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cv::gpu::setDevice(devInfo.deviceID());
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cv::Mat frame0_host = readImage("gpu/opticalflow/frame0.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame0_host.empty());
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cv::Mat frame1_host = readImage("gpu/opticalflow/frame1.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1_host.empty());
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frame0_host.convertTo(frame0_host, CV_32FC1, 1.0 / 255.0);
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frame1_host.convertTo(frame1_host, CV_32FC1, 1.0 / 255.0);
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cv::gpu::GpuMat frame0(frame0_host);
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cv::gpu::GpuMat frame1(frame1_host);
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cv::gpu::GpuMat u;
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cv::gpu::GpuMat v;
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cv::gpu::BroxOpticalFlow d_flow(0.197f /*alpha*/, 50.0f /*gamma*/, 0.8f /*scale_factor*/,
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10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/);
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d_flow(frame0, frame1, u, v);
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declare.time(10);
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TEST_CYCLE()
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{
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d_flow(frame0, frame1, u, v);
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}
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}
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INSTANTIATE_TEST_CASE_P(Video, BroxOpticalFlow, ALL_DEVICES);
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//////////////////////////////////////////////////////
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// InterpolateFrames
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GPU_PERF_TEST_1(InterpolateFrames, cv::gpu::DeviceInfo)
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{
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cv::gpu::DeviceInfo devInfo = GetParam();
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cv::gpu::setDevice(devInfo.deviceID());
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cv::Mat frame0_host = readImage("gpu/perf/aloe.jpg", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame0_host.empty());
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cv::Mat frame1_host = readImage("gpu/perf/aloeR.jpg", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1_host.empty());
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frame0_host.convertTo(frame0_host, CV_32FC1, 1.0 / 255.0);
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frame1_host.convertTo(frame1_host, CV_32FC1, 1.0 / 255.0);
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cv::gpu::GpuMat frame0(frame0_host);
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cv::gpu::GpuMat frame1(frame1_host);
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cv::gpu::GpuMat fu, fv;
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cv::gpu::GpuMat bu, bv;
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cv::gpu::BroxOpticalFlow d_flow(0.197f /*alpha*/, 50.0f /*gamma*/, 0.8f /*scale_factor*/,
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10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/);
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d_flow(frame0, frame1, fu, fv);
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d_flow(frame1, frame0, bu, bv);
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cv::gpu::GpuMat newFrame;
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cv::gpu::GpuMat buf;
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cv::gpu::interpolateFrames(frame0, frame1, fu, fv, bu, bv, 0.5f, newFrame, buf);
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TEST_CYCLE()
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{
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cv::gpu::interpolateFrames(frame0, frame1, fu, fv, bu, bv, 0.5f, newFrame, buf);
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}
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}
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INSTANTIATE_TEST_CASE_P(Video, InterpolateFrames, ALL_DEVICES);
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//////////////////////////////////////////////////////
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// CreateOpticalFlowNeedleMap
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GPU_PERF_TEST_1(CreateOpticalFlowNeedleMap, cv::gpu::DeviceInfo)
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{
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cv::gpu::DeviceInfo devInfo = GetParam();
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cv::gpu::setDevice(devInfo.deviceID());
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cv::Mat frame0_host = readImage("gpu/perf/aloe.jpg", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame0_host.empty());
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cv::Mat frame1_host = readImage("gpu/perf/aloeR.jpg", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1_host.empty());
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frame0_host.convertTo(frame0_host, CV_32FC1, 1.0 / 255.0);
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frame1_host.convertTo(frame1_host, CV_32FC1, 1.0 / 255.0);
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cv::gpu::GpuMat frame0(frame0_host);
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cv::gpu::GpuMat frame1(frame1_host);
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cv::gpu::GpuMat u, v;
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cv::gpu::BroxOpticalFlow d_flow(0.197f /*alpha*/, 50.0f /*gamma*/, 0.8f /*scale_factor*/,
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10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/);
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d_flow(frame0, frame1, u, v);
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cv::gpu::GpuMat vertex, colors;
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cv::gpu::createOpticalFlowNeedleMap(u, v, vertex, colors);
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TEST_CYCLE()
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{
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cv::gpu::createOpticalFlowNeedleMap(u, v, vertex, colors);
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}
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}
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INSTANTIATE_TEST_CASE_P(Video, CreateOpticalFlowNeedleMap, ALL_DEVICES);
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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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cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
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cv::gpu::setDevice(devInfo.deviceID());
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double minDistance = GET_PARAM(1);
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cv::Mat image_host = readImage("gpu/perf/aloe.jpg", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(image_host.empty());
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cv::gpu::GoodFeaturesToTrackDetector_GPU detector(8000, 0.01, minDistance);
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cv::gpu::GpuMat image(image_host);
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cv::gpu::GpuMat pts;
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detector(image, pts);
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TEST_CYCLE()
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{
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detector(image, pts);
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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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cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
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cv::gpu::setDevice(devInfo.deviceID());
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bool useGray = GET_PARAM(1);
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int points = GET_PARAM(2);
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int winSize = 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_host = readImage("gpu/opticalflow/frame0.png", useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
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ASSERT_FALSE(frame0_host.empty());
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cv::Mat frame1_host = readImage("gpu/opticalflow/frame1.png", useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
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ASSERT_FALSE(frame1_host.empty());
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cv::Mat gray_frame;
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if (useGray)
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gray_frame = frame0_host;
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else
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cv::cvtColor(frame0_host, gray_frame, cv::COLOR_BGR2GRAY);
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cv::gpu::GpuMat pts;
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cv::gpu::GoodFeaturesToTrackDetector_GPU detector(points, 0.01, 0.0);
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detector(cv::gpu::GpuMat(gray_frame), pts);
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cv::gpu::PyrLKOpticalFlow pyrLK;
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pyrLK.winSize = cv::Size(winSize, winSize);
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pyrLK.maxLevel = levels - 1;
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pyrLK.iters = iters;
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cv::gpu::GpuMat frame0(frame0_host);
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cv::gpu::GpuMat frame1(frame1_host);
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cv::gpu::GpuMat nextPts;
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cv::gpu::GpuMat status;
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pyrLK.sparse(frame0, frame1, pts, nextPts, status);
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TEST_CYCLE()
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{
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pyrLK.sparse(frame0, frame1, pts, nextPts, status);
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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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// PyrLKOpticalFlowDense
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GPU_PERF_TEST(PyrLKOpticalFlowDense, cv::gpu::DeviceInfo, WinSize, Levels, Iters)
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{
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cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
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cv::gpu::setDevice(devInfo.deviceID());
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int winSize = GET_PARAM(1);
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int levels = GET_PARAM(2);
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int iters = GET_PARAM(3);
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cv::Mat frame0_host = readImage("gpu/opticalflow/frame0.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame0_host.empty());
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cv::Mat frame1_host = readImage("gpu/opticalflow/frame1.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1_host.empty());
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cv::gpu::GpuMat frame0(frame0_host);
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cv::gpu::GpuMat frame1(frame1_host);
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cv::gpu::GpuMat u;
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cv::gpu::GpuMat v;
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cv::gpu::PyrLKOpticalFlow pyrLK;
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pyrLK.winSize = cv::Size(winSize, winSize);
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pyrLK.maxLevel = levels - 1;
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pyrLK.iters = iters;
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pyrLK.dense(frame0, frame1, u, v);
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declare.time(30);
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TEST_CYCLE()
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{
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pyrLK.dense(frame0, frame1, u, v);
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}
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}
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INSTANTIATE_TEST_CASE_P(Video, PyrLKOpticalFlowDense, testing::Combine(
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ALL_DEVICES,
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testing::Values(WinSize(3), WinSize(5), WinSize(7), 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))));
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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::gpu::DeviceInfo devInfo = GetParam();
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cv::gpu::setDevice(devInfo.deviceID());
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cv::Mat frame0_host = readImage("gpu/opticalflow/frame0.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame0_host.empty());
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cv::Mat frame1_host = readImage("gpu/opticalflow/frame1.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1_host.empty());
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cv::gpu::GpuMat frame0(frame0_host);
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cv::gpu::GpuMat frame1(frame1_host);
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cv::gpu::GpuMat u;
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cv::gpu::GpuMat v;
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cv::gpu::FarnebackOpticalFlow farneback;
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farneback(frame0, frame1, u, v);
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declare.time(10);
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TEST_CYCLE()
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{
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farneback(frame0, frame1, u, v);
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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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GPU_PERF_TEST(FGDStatModel, cv::gpu::DeviceInfo, std::string)
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{
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cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
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cv::gpu::setDevice(devInfo.deviceID());
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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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cv::gpu::GpuMat d_frame(frame);
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cv::gpu::FGDStatModel d_model(4);
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d_model.create(d_frame);
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declare.time(10);
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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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d_frame.upload(frame);
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startTimer(); next();
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d_model.update(d_frame);
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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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cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
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cv::gpu::setDevice(devInfo.deviceID());
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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::gpu::GpuMat d_frame;
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cv::gpu::MOG_GPU mog;
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cv::gpu::GpuMat 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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d_frame.upload(frame);
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mog(d_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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d_frame.upload(frame);
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startTimer(); next();
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mog(d_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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cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
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cv::gpu::setDevice(devInfo.deviceID());
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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::gpu::GpuMat d_frame;
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cv::gpu::MOG2_GPU mog2;
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cv::gpu::GpuMat 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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d_frame.upload(frame);
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mog2(d_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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d_frame.upload(frame);
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startTimer(); next();
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mog2(d_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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cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
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cv::gpu::setDevice(devInfo.deviceID());
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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::gpu::GpuMat d_frame;
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cv::gpu::MOG2_GPU mog2;
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cv::gpu::GpuMat 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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d_frame.upload(frame);
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mog2(d_frame, foreground);
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}
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cv::gpu::GpuMat background;
|
|
mog2.getBackgroundImage(background);
|
|
|
|
TEST_CYCLE()
|
|
{
|
|
mog2.getBackgroundImage(background);
|
|
}
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Video, MOG2_getBackgroundImage, testing::Combine(
|
|
ALL_DEVICES,
|
|
testing::Values(std::string("768x576.avi"), std::string("1920x1080.avi")),
|
|
testing::Values(Channels(1), Channels(3), Channels(4))));
|
|
|
|
//////////////////////////////////////////////////////
|
|
// VIBE
|
|
|
|
GPU_PERF_TEST(VIBE, cv::gpu::DeviceInfo, std::string, Channels)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
std::string inputFile = perf::TestBase::getDataPath(std::string("gpu/video/") + GET_PARAM(1));
|
|
int cn = GET_PARAM(2);
|
|
|
|
cv::VideoCapture cap(inputFile);
|
|
ASSERT_TRUE(cap.isOpened());
|
|
|
|
cv::Mat frame;
|
|
cap >> frame;
|
|
ASSERT_FALSE(frame.empty());
|
|
|
|
if (cn != 3)
|
|
{
|
|
cv::Mat temp;
|
|
if (cn == 1)
|
|
cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
|
|
else
|
|
cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
|
|
cv::swap(temp, frame);
|
|
}
|
|
|
|
cv::gpu::GpuMat d_frame(frame);
|
|
cv::gpu::VIBE_GPU vibe;
|
|
cv::gpu::GpuMat foreground;
|
|
|
|
vibe(d_frame, foreground);
|
|
|
|
for (int i = 0; i < 10; ++i)
|
|
{
|
|
cap >> frame;
|
|
ASSERT_FALSE(frame.empty());
|
|
|
|
if (cn != 3)
|
|
{
|
|
cv::Mat temp;
|
|
if (cn == 1)
|
|
cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
|
|
else
|
|
cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
|
|
cv::swap(temp, frame);
|
|
}
|
|
|
|
d_frame.upload(frame);
|
|
|
|
startTimer(); next();
|
|
vibe(d_frame, foreground);
|
|
stopTimer();
|
|
}
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Video, VIBE, testing::Combine(
|
|
ALL_DEVICES,
|
|
testing::Values(std::string("768x576.avi"), std::string("1920x1080.avi")),
|
|
testing::Values(Channels(1), Channels(3), Channels(4))));
|
|
|
|
//////////////////////////////////////////////////////
|
|
// VideoWriter
|
|
|
|
#ifdef WIN32
|
|
|
|
GPU_PERF_TEST(VideoWriter, cv::gpu::DeviceInfo, std::string)
|
|
{
|
|
const double FPS = 25.0;
|
|
|
|
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
std::string inputFile = perf::TestBase::getDataPath(std::string("gpu/video/") + GET_PARAM(1));
|
|
std::string outputFile = cv::tempfile(".avi");
|
|
|
|
cv::VideoCapture reader(inputFile);
|
|
ASSERT_TRUE( reader.isOpened() );
|
|
|
|
cv::gpu::VideoWriter_GPU d_writer;
|
|
|
|
cv::Mat frame;
|
|
cv::gpu::GpuMat d_frame;
|
|
|
|
declare.time(10);
|
|
|
|
for (int i = 0; i < 10; ++i)
|
|
{
|
|
reader >> frame;
|
|
ASSERT_FALSE(frame.empty());
|
|
|
|
d_frame.upload(frame);
|
|
|
|
if (!d_writer.isOpened())
|
|
d_writer.open(outputFile, frame.size(), FPS);
|
|
|
|
startTimer(); next();
|
|
d_writer.write(d_frame);
|
|
stopTimer();
|
|
}
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Video, VideoWriter, testing::Combine(
|
|
ALL_DEVICES,
|
|
testing::Values(std::string("768x576.avi"), std::string("1920x1080.avi"))));
|
|
|
|
#endif // WIN32
|
|
|
|
//////////////////////////////////////////////////////
|
|
// VideoReader
|
|
|
|
GPU_PERF_TEST(VideoReader, cv::gpu::DeviceInfo, std::string)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
std::string inputFile = perf::TestBase::getDataPath(std::string("gpu/video/") + GET_PARAM(1));
|
|
|
|
cv::gpu::VideoReader_GPU reader(inputFile);
|
|
ASSERT_TRUE( reader.isOpened() );
|
|
|
|
cv::gpu::GpuMat frame;
|
|
|
|
reader.read(frame);
|
|
|
|
declare.time(20);
|
|
|
|
TEST_CYCLE_N(10)
|
|
{
|
|
reader.read(frame);
|
|
}
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Video, VideoReader, testing::Combine(
|
|
ALL_DEVICES,
|
|
testing::Values(std::string("768x576.avi"), std::string("1920x1080.avi"))));
|
|
|
|
#endif
|