1321 lines
34 KiB
C++
1321 lines
34 KiB
C++
/*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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#if defined(HAVE_XINE) || \
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defined(HAVE_GSTREAMER) || \
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defined(HAVE_QUICKTIME) || \
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defined(HAVE_QTKIT) || \
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defined(HAVE_AVFOUNDATION) || \
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defined(HAVE_FFMPEG) || \
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defined(WIN32) /* assume that we have ffmpeg */
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# define BUILD_WITH_VIDEO_INPUT_SUPPORT 1
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#else
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# define BUILD_WITH_VIDEO_INPUT_SUPPORT 0
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#endif
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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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//////////////////////////////////////////////////////
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// InterpolateFrames
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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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PERF_TEST_P(ImagePair, Video_InterpolateFrames,
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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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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_GPU())
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{
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const cv::gpu::GpuMat d_frame0(frame0);
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const cv::gpu::GpuMat d_frame1(frame1);
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cv::gpu::GpuMat d_fu, d_fv;
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cv::gpu::GpuMat d_bu, d_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(d_frame0, d_frame1, d_fu, d_fv);
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d_flow(d_frame1, d_frame0, d_bu, d_bv);
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cv::gpu::GpuMat newFrame;
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cv::gpu::GpuMat d_buf;
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TEST_CYCLE() cv::gpu::interpolateFrames(d_frame0, d_frame1, d_fu, d_fv, d_bu, d_bv, 0.5f, newFrame, d_buf);
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GPU_SANITY_CHECK(newFrame, 1e-4);
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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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// CreateOpticalFlowNeedleMap
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PERF_TEST_P(ImagePair, Video_CreateOpticalFlowNeedleMap,
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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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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_GPU())
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{
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const cv::gpu::GpuMat d_frame0(frame0);
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const cv::gpu::GpuMat d_frame1(frame1);
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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(d_frame0, d_frame1, u, v);
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cv::gpu::GpuMat vertex, colors;
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TEST_CYCLE() cv::gpu::createOpticalFlowNeedleMap(u, v, vertex, colors);
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GPU_SANITY_CHECK(vertex, 1e-6);
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GPU_SANITY_CHECK(colors);
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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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// GoodFeaturesToTrack
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DEF_PARAM_TEST(Image_MinDistance, string, double);
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PERF_TEST_P(Image_MinDistance, Video_GoodFeaturesToTrack,
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Combine(Values<string>("gpu/perf/aloe.png"),
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Values(0.0, 3.0)))
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{
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const string fileName = GET_PARAM(0);
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const double minDistance = GET_PARAM(1);
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const cv::Mat image = readImage(fileName, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(image.empty());
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const int maxCorners = 8000;
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const double qualityLevel = 0.01;
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if (PERF_RUN_GPU())
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{
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cv::gpu::GoodFeaturesToTrackDetector_GPU d_detector(maxCorners, qualityLevel, minDistance);
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const cv::gpu::GpuMat d_image(image);
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cv::gpu::GpuMat pts;
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TEST_CYCLE() d_detector(d_image, pts);
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GPU_SANITY_CHECK(pts);
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}
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else
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{
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cv::Mat pts;
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TEST_CYCLE() cv::goodFeaturesToTrack(image, pts, maxCorners, qualityLevel, minDistance);
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CPU_SANITY_CHECK(pts);
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}
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}
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//////////////////////////////////////////////////////
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// BroxOpticalFlow
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PERF_TEST_P(ImagePair, Video_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_GPU())
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{
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const cv::gpu::GpuMat d_frame0(frame0);
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const cv::gpu::GpuMat d_frame1(frame1);
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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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TEST_CYCLE() d_flow(d_frame0, d_frame1, u, v);
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GPU_SANITY_CHECK(u, 1e-1);
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GPU_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, Video_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_GPU())
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{
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const cv::gpu::GpuMat d_pts(pts.reshape(2, 1));
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cv::gpu::PyrLKOpticalFlow d_pyrLK;
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d_pyrLK.winSize = cv::Size(winSize, winSize);
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d_pyrLK.maxLevel = levels - 1;
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d_pyrLK.iters = iters;
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const cv::gpu::GpuMat d_frame0(frame0);
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const cv::gpu::GpuMat d_frame1(frame1);
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cv::gpu::GpuMat nextPts;
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cv::gpu::GpuMat status;
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TEST_CYCLE() d_pyrLK.sparse(d_frame0, d_frame1, d_pts, nextPts, status);
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GPU_SANITY_CHECK(nextPts);
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GPU_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, Video_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_GPU())
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{
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const cv::gpu::GpuMat d_frame0(frame0);
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const cv::gpu::GpuMat d_frame1(frame1);
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cv::gpu::GpuMat u;
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cv::gpu::GpuMat v;
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cv::gpu::PyrLKOpticalFlow d_pyrLK;
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d_pyrLK.winSize = cv::Size(winSize, winSize);
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d_pyrLK.maxLevel = levels - 1;
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d_pyrLK.iters = iters;
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TEST_CYCLE() d_pyrLK.dense(d_frame0, d_frame1, u, v);
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GPU_SANITY_CHECK(u);
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GPU_SANITY_CHECK(v);
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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, Video_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_GPU())
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{
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const cv::gpu::GpuMat d_frame0(frame0);
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const cv::gpu::GpuMat d_frame1(frame1);
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cv::gpu::GpuMat u;
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cv::gpu::GpuMat v;
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cv::gpu::FarnebackOpticalFlow d_farneback;
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d_farneback.numLevels = numLevels;
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d_farneback.pyrScale = pyrScale;
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d_farneback.winSize = winSize;
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d_farneback.numIters = numIters;
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d_farneback.polyN = polyN;
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d_farneback.polySigma = polySigma;
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d_farneback.flags = flags;
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TEST_CYCLE() d_farneback(d_frame0, d_frame1, u, v);
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GPU_SANITY_CHECK(u, 1e-4);
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GPU_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, Video_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_GPU())
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{
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const cv::gpu::GpuMat d_frame0(frame0);
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const cv::gpu::GpuMat d_frame1(frame1);
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cv::gpu::GpuMat u;
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cv::gpu::GpuMat v;
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cv::gpu::OpticalFlowDual_TVL1_GPU d_alg;
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TEST_CYCLE() d_alg(d_frame0, d_frame1, u, v);
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GPU_SANITY_CHECK(u, 1e-1);
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GPU_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::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
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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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//////////////////////////////////////////////////////
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// OpticalFlowBM
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void calcOpticalFlowBM(const cv::Mat& prev, const cv::Mat& curr,
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cv::Size bSize, cv::Size shiftSize, cv::Size maxRange, int usePrevious,
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cv::Mat& velx, cv::Mat& vely)
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{
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cv::Size sz((curr.cols - bSize.width + shiftSize.width)/shiftSize.width, (curr.rows - bSize.height + shiftSize.height)/shiftSize.height);
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velx.create(sz, CV_32FC1);
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vely.create(sz, CV_32FC1);
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CvMat cvprev = prev;
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CvMat cvcurr = curr;
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CvMat cvvelx = velx;
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CvMat cvvely = vely;
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cvCalcOpticalFlowBM(&cvprev, &cvcurr, bSize, shiftSize, maxRange, usePrevious, &cvvelx, &cvvely);
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}
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PERF_TEST_P(ImagePair, Video_OpticalFlowBM,
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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(400);
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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 cv::Size block_size(16, 16);
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const cv::Size shift_size(1, 1);
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const cv::Size max_range(16, 16);
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if (PERF_RUN_GPU())
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{
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const cv::gpu::GpuMat d_frame0(frame0);
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const cv::gpu::GpuMat d_frame1(frame1);
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cv::gpu::GpuMat u, v, buf;
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|
|
TEST_CYCLE() cv::gpu::calcOpticalFlowBM(d_frame0, d_frame1, block_size, shift_size, max_range, false, u, v, buf);
|
|
|
|
GPU_SANITY_CHECK(u);
|
|
GPU_SANITY_CHECK(v);
|
|
}
|
|
else
|
|
{
|
|
cv::Mat u, v;
|
|
|
|
TEST_CYCLE() calcOpticalFlowBM(frame0, frame1, block_size, shift_size, max_range, false, u, v);
|
|
|
|
CPU_SANITY_CHECK(u);
|
|
CPU_SANITY_CHECK(v);
|
|
}
|
|
}
|
|
|
|
PERF_TEST_P(ImagePair, DISABLED_Video_FastOpticalFlowBM,
|
|
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
|
|
{
|
|
declare.time(400);
|
|
|
|
const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
|
|
ASSERT_FALSE(frame0.empty());
|
|
|
|
const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
|
|
ASSERT_FALSE(frame1.empty());
|
|
|
|
const cv::Size block_size(16, 16);
|
|
const cv::Size shift_size(1, 1);
|
|
const cv::Size max_range(16, 16);
|
|
|
|
if (PERF_RUN_GPU())
|
|
{
|
|
const cv::gpu::GpuMat d_frame0(frame0);
|
|
const cv::gpu::GpuMat d_frame1(frame1);
|
|
cv::gpu::GpuMat u, v;
|
|
|
|
cv::gpu::FastOpticalFlowBM fastBM;
|
|
|
|
TEST_CYCLE() fastBM(d_frame0, d_frame1, u, v, max_range.width, block_size.width);
|
|
|
|
GPU_SANITY_CHECK(u, 2);
|
|
GPU_SANITY_CHECK(v, 2);
|
|
}
|
|
else
|
|
{
|
|
FAIL_NO_CPU();
|
|
}
|
|
}
|
|
|
|
//////////////////////////////////////////////////////
|
|
// FGDStatModel
|
|
|
|
#if BUILD_WITH_VIDEO_INPUT_SUPPORT
|
|
|
|
DEF_PARAM_TEST_1(Video, string);
|
|
|
|
PERF_TEST_P(Video, Video_FGDStatModel,
|
|
Values(string("gpu/video/768x576.avi")))
|
|
{
|
|
const int numIters = 10;
|
|
|
|
declare.time(60);
|
|
|
|
const string inputFile = perf::TestBase::getDataPath(GetParam());
|
|
|
|
cv::VideoCapture cap(inputFile);
|
|
ASSERT_TRUE(cap.isOpened());
|
|
|
|
cv::Mat frame;
|
|
cap >> frame;
|
|
ASSERT_FALSE(frame.empty());
|
|
|
|
if (PERF_RUN_GPU())
|
|
{
|
|
cv::gpu::GpuMat d_frame(frame);
|
|
|
|
cv::gpu::FGDStatModel d_model(4);
|
|
d_model.create(d_frame);
|
|
|
|
int i = 0;
|
|
|
|
// collect performance data
|
|
for (; i < numIters; ++i)
|
|
{
|
|
cap >> frame;
|
|
ASSERT_FALSE(frame.empty());
|
|
|
|
d_frame.upload(frame);
|
|
|
|
startTimer();
|
|
if(!next())
|
|
break;
|
|
|
|
d_model.update(d_frame);
|
|
|
|
stopTimer();
|
|
}
|
|
|
|
// process last frame in sequence to get data for sanity test
|
|
for (; i < numIters; ++i)
|
|
{
|
|
cap >> frame;
|
|
ASSERT_FALSE(frame.empty());
|
|
|
|
d_frame.upload(frame);
|
|
|
|
d_model.update(d_frame);
|
|
}
|
|
|
|
const cv::gpu::GpuMat background = d_model.background;
|
|
const cv::gpu::GpuMat foreground = d_model.foreground;
|
|
|
|
GPU_SANITY_CHECK(background, 1e-2, ERROR_RELATIVE);
|
|
GPU_SANITY_CHECK(foreground, 1e-2, ERROR_RELATIVE);
|
|
}
|
|
else
|
|
{
|
|
IplImage ipl_frame = frame;
|
|
cv::Ptr<CvBGStatModel> model(cvCreateFGDStatModel(&ipl_frame));
|
|
|
|
int i = 0;
|
|
|
|
// collect performance data
|
|
for (; i < numIters; ++i)
|
|
{
|
|
cap >> frame;
|
|
ASSERT_FALSE(frame.empty());
|
|
|
|
ipl_frame = frame;
|
|
|
|
startTimer();
|
|
if(!next())
|
|
break;
|
|
|
|
cvUpdateBGStatModel(&ipl_frame, model);
|
|
|
|
stopTimer();
|
|
}
|
|
|
|
// process last frame in sequence to get data for sanity test
|
|
for (; i < numIters; ++i)
|
|
{
|
|
cap >> frame;
|
|
ASSERT_FALSE(frame.empty());
|
|
|
|
ipl_frame = frame;
|
|
|
|
cvUpdateBGStatModel(&ipl_frame, model);
|
|
}
|
|
|
|
const cv::Mat background = model->background;
|
|
const cv::Mat foreground = model->foreground;
|
|
|
|
CPU_SANITY_CHECK(background);
|
|
CPU_SANITY_CHECK(foreground);
|
|
}
|
|
}
|
|
|
|
#endif
|
|
|
|
//////////////////////////////////////////////////////
|
|
// MOG
|
|
|
|
#if BUILD_WITH_VIDEO_INPUT_SUPPORT
|
|
|
|
DEF_PARAM_TEST(Video_Cn_LearningRate, string, MatCn, double);
|
|
|
|
PERF_TEST_P(Video_Cn_LearningRate, Video_MOG,
|
|
Combine(Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
|
|
GPU_CHANNELS_1_3_4,
|
|
Values(0.0, 0.01)))
|
|
{
|
|
const int numIters = 10;
|
|
|
|
const string inputFile = perf::TestBase::getDataPath(GET_PARAM(0));
|
|
const int cn = GET_PARAM(1);
|
|
const float learningRate = static_cast<float>(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);
|
|
}
|
|
|
|
if (PERF_RUN_GPU())
|
|
{
|
|
cv::gpu::GpuMat d_frame(frame);
|
|
cv::gpu::MOG_GPU d_mog;
|
|
cv::gpu::GpuMat foreground;
|
|
|
|
d_mog(d_frame, foreground, learningRate);
|
|
|
|
int i = 0;
|
|
|
|
// collect performance data
|
|
for (; i < numIters; ++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();
|
|
if(!next())
|
|
break;
|
|
|
|
d_mog(d_frame, foreground, learningRate);
|
|
|
|
stopTimer();
|
|
}
|
|
|
|
// process last frame in sequence to get data for sanity test
|
|
for (; i < numIters; ++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);
|
|
|
|
d_mog(d_frame, foreground, learningRate);
|
|
}
|
|
|
|
GPU_SANITY_CHECK(foreground);
|
|
}
|
|
else
|
|
{
|
|
cv::BackgroundSubtractorMOG mog;
|
|
cv::Mat foreground;
|
|
|
|
mog(frame, foreground, learningRate);
|
|
|
|
int i = 0;
|
|
|
|
// collect performance data
|
|
for (; i < numIters; ++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);
|
|
}
|
|
|
|
startTimer();
|
|
if(!next())
|
|
break;
|
|
|
|
mog(frame, foreground, learningRate);
|
|
|
|
stopTimer();
|
|
}
|
|
|
|
// process last frame in sequence to get data for sanity test
|
|
for (; i < numIters; ++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);
|
|
}
|
|
|
|
mog(frame, foreground, learningRate);
|
|
}
|
|
|
|
CPU_SANITY_CHECK(foreground);
|
|
}
|
|
}
|
|
|
|
#endif
|
|
|
|
//////////////////////////////////////////////////////
|
|
// MOG2
|
|
|
|
#if BUILD_WITH_VIDEO_INPUT_SUPPORT
|
|
|
|
DEF_PARAM_TEST(Video_Cn, string, int);
|
|
|
|
PERF_TEST_P(Video_Cn, DISABLED_Video_MOG2,
|
|
Combine(Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
|
|
GPU_CHANNELS_1_3_4))
|
|
{
|
|
const int numIters = 10;
|
|
|
|
const string inputFile = perf::TestBase::getDataPath(GET_PARAM(0));
|
|
const int cn = GET_PARAM(1);
|
|
|
|
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);
|
|
}
|
|
|
|
if (PERF_RUN_GPU())
|
|
{
|
|
cv::gpu::MOG2_GPU d_mog2;
|
|
d_mog2.bShadowDetection = false;
|
|
|
|
cv::gpu::GpuMat d_frame(frame);
|
|
cv::gpu::GpuMat foreground;
|
|
|
|
d_mog2(d_frame, foreground);
|
|
|
|
int i = 0;
|
|
|
|
// collect performance data
|
|
for (; i < numIters; ++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();
|
|
if(!next())
|
|
break;
|
|
|
|
d_mog2(d_frame, foreground);
|
|
|
|
stopTimer();
|
|
}
|
|
|
|
// process last frame in sequence to get data for sanity test
|
|
for (; i < numIters; ++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);
|
|
|
|
d_mog2(d_frame, foreground);
|
|
}
|
|
|
|
GPU_SANITY_CHECK(foreground);
|
|
}
|
|
else
|
|
{
|
|
cv::BackgroundSubtractorMOG2 mog2;
|
|
mog2.set("detectShadows", false);
|
|
|
|
cv::Mat foreground;
|
|
|
|
mog2(frame, foreground);
|
|
|
|
int i = 0;
|
|
|
|
// collect performance data
|
|
for (; i < numIters; ++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);
|
|
}
|
|
|
|
startTimer();
|
|
if(!next())
|
|
break;
|
|
|
|
mog2(frame, foreground);
|
|
|
|
stopTimer();
|
|
}
|
|
|
|
// process last frame in sequence to get data for sanity test
|
|
for (; i < numIters; ++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);
|
|
}
|
|
|
|
mog2(frame, foreground);
|
|
}
|
|
|
|
CPU_SANITY_CHECK(foreground);
|
|
}
|
|
}
|
|
|
|
#endif
|
|
|
|
//////////////////////////////////////////////////////
|
|
// MOG2GetBackgroundImage
|
|
|
|
#if BUILD_WITH_VIDEO_INPUT_SUPPORT
|
|
|
|
PERF_TEST_P(Video_Cn, Video_MOG2GetBackgroundImage,
|
|
Combine(Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
|
|
GPU_CHANNELS_1_3_4))
|
|
{
|
|
const string inputFile = perf::TestBase::getDataPath(GET_PARAM(0));
|
|
const int cn = GET_PARAM(1);
|
|
|
|
cv::VideoCapture cap(inputFile);
|
|
ASSERT_TRUE(cap.isOpened());
|
|
|
|
cv::Mat frame;
|
|
|
|
if (PERF_RUN_GPU())
|
|
{
|
|
cv::gpu::GpuMat d_frame;
|
|
cv::gpu::MOG2_GPU d_mog2;
|
|
cv::gpu::GpuMat d_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);
|
|
|
|
d_mog2(d_frame, d_foreground);
|
|
}
|
|
|
|
cv::gpu::GpuMat background;
|
|
|
|
TEST_CYCLE() d_mog2.getBackgroundImage(background);
|
|
|
|
GPU_SANITY_CHECK(background, 1);
|
|
}
|
|
else
|
|
{
|
|
cv::BackgroundSubtractorMOG2 mog2;
|
|
cv::Mat 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);
|
|
}
|
|
|
|
mog2(frame, foreground);
|
|
}
|
|
|
|
cv::Mat background;
|
|
|
|
TEST_CYCLE() mog2.getBackgroundImage(background);
|
|
|
|
CPU_SANITY_CHECK(background);
|
|
}
|
|
}
|
|
|
|
#endif
|
|
|
|
//////////////////////////////////////////////////////
|
|
// GMG
|
|
|
|
#if BUILD_WITH_VIDEO_INPUT_SUPPORT
|
|
|
|
DEF_PARAM_TEST(Video_Cn_MaxFeatures, string, MatCn, int);
|
|
|
|
PERF_TEST_P(Video_Cn_MaxFeatures, Video_GMG,
|
|
Combine(Values(string("gpu/video/768x576.avi")),
|
|
GPU_CHANNELS_1_3_4,
|
|
Values(20, 40, 60)))
|
|
{
|
|
const int numIters = 150;
|
|
|
|
const std::string inputFile = perf::TestBase::getDataPath(GET_PARAM(0));
|
|
const int cn = GET_PARAM(1);
|
|
const int maxFeatures = 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);
|
|
}
|
|
|
|
if (PERF_RUN_GPU())
|
|
{
|
|
cv::gpu::GpuMat d_frame(frame);
|
|
cv::gpu::GpuMat foreground;
|
|
|
|
cv::gpu::GMG_GPU d_gmg;
|
|
d_gmg.maxFeatures = maxFeatures;
|
|
|
|
d_gmg(d_frame, foreground);
|
|
|
|
int i = 0;
|
|
|
|
// collect performance data
|
|
for (; i < numIters; ++i)
|
|
{
|
|
cap >> frame;
|
|
if (frame.empty())
|
|
{
|
|
cap.release();
|
|
cap.open(inputFile);
|
|
cap >> frame;
|
|
}
|
|
|
|
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();
|
|
if(!next())
|
|
break;
|
|
|
|
d_gmg(d_frame, foreground);
|
|
|
|
stopTimer();
|
|
}
|
|
|
|
// process last frame in sequence to get data for sanity test
|
|
for (; i < numIters; ++i)
|
|
{
|
|
cap >> frame;
|
|
if (frame.empty())
|
|
{
|
|
cap.release();
|
|
cap.open(inputFile);
|
|
cap >> frame;
|
|
}
|
|
|
|
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);
|
|
|
|
d_gmg(d_frame, foreground);
|
|
}
|
|
|
|
GPU_SANITY_CHECK(foreground);
|
|
}
|
|
else
|
|
{
|
|
cv::Mat foreground;
|
|
cv::Mat zeros(frame.size(), CV_8UC1, cv::Scalar::all(0));
|
|
|
|
cv::BackgroundSubtractorGMG gmg;
|
|
gmg.set("maxFeatures", maxFeatures);
|
|
gmg.initialize(frame.size(), 0.0, 255.0);
|
|
|
|
gmg(frame, foreground);
|
|
|
|
int i = 0;
|
|
|
|
// collect performance data
|
|
for (; i < numIters; ++i)
|
|
{
|
|
cap >> frame;
|
|
if (frame.empty())
|
|
{
|
|
cap.release();
|
|
cap.open(inputFile);
|
|
cap >> frame;
|
|
}
|
|
|
|
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);
|
|
}
|
|
|
|
startTimer();
|
|
if(!next())
|
|
break;
|
|
|
|
gmg(frame, foreground);
|
|
|
|
stopTimer();
|
|
}
|
|
|
|
// process last frame in sequence to get data for sanity test
|
|
for (; i < numIters; ++i)
|
|
{
|
|
cap >> frame;
|
|
if (frame.empty())
|
|
{
|
|
cap.release();
|
|
cap.open(inputFile);
|
|
cap >> frame;
|
|
}
|
|
|
|
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);
|
|
}
|
|
|
|
gmg(frame, foreground);
|
|
}
|
|
|
|
CPU_SANITY_CHECK(foreground);
|
|
}
|
|
}
|
|
|
|
#endif
|
|
|
|
//////////////////////////////////////////////////////
|
|
// VideoReader
|
|
|
|
#if defined(HAVE_NVCUVID) && BUILD_WITH_VIDEO_INPUT_SUPPORT
|
|
|
|
PERF_TEST_P(Video, DISABLED_Video_VideoReader, Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"))
|
|
{
|
|
declare.time(20);
|
|
|
|
const string inputFile = perf::TestBase::getDataPath(GetParam());
|
|
|
|
if (PERF_RUN_GPU())
|
|
{
|
|
cv::gpu::VideoReader_GPU d_reader(inputFile);
|
|
ASSERT_TRUE( d_reader.isOpened() );
|
|
|
|
cv::gpu::GpuMat frame;
|
|
|
|
TEST_CYCLE_N(10) d_reader.read(frame);
|
|
|
|
GPU_SANITY_CHECK(frame);
|
|
}
|
|
else
|
|
{
|
|
cv::VideoCapture reader(inputFile);
|
|
ASSERT_TRUE( reader.isOpened() );
|
|
|
|
cv::Mat frame;
|
|
|
|
TEST_CYCLE_N(10) reader >> frame;
|
|
|
|
CPU_SANITY_CHECK(frame);
|
|
}
|
|
}
|
|
|
|
#endif
|
|
|
|
//////////////////////////////////////////////////////
|
|
// VideoWriter
|
|
|
|
#if defined(HAVE_NVCUVID) && defined(WIN32)
|
|
|
|
PERF_TEST_P(Video, DISABLED_Video_VideoWriter, Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"))
|
|
{
|
|
declare.time(30);
|
|
|
|
const string inputFile = perf::TestBase::getDataPath(GetParam());
|
|
const string outputFile = cv::tempfile(".avi");
|
|
|
|
const double FPS = 25.0;
|
|
|
|
cv::VideoCapture reader(inputFile);
|
|
ASSERT_TRUE( reader.isOpened() );
|
|
|
|
cv::Mat frame;
|
|
|
|
if (PERF_RUN_GPU())
|
|
{
|
|
cv::gpu::VideoWriter_GPU d_writer;
|
|
|
|
cv::gpu::GpuMat d_frame;
|
|
|
|
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();
|
|
}
|
|
}
|
|
else
|
|
{
|
|
cv::VideoWriter writer;
|
|
|
|
for (int i = 0; i < 10; ++i)
|
|
{
|
|
reader >> frame;
|
|
ASSERT_FALSE(frame.empty());
|
|
|
|
if (!writer.isOpened())
|
|
writer.open(outputFile, CV_FOURCC('X', 'V', 'I', 'D'), FPS, frame.size());
|
|
|
|
startTimer(); next();
|
|
writer.write(frame);
|
|
stopTimer();
|
|
}
|
|
}
|
|
|
|
SANITY_CHECK(frame);
|
|
}
|
|
|
|
#endif
|