/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "test_precomp.hpp" #ifdef HAVE_OPENCV_LEGACY # include "opencv2/legacy.hpp" #endif #ifdef HAVE_CUDA using namespace cvtest; #if defined(HAVE_XINE) || \ defined(HAVE_GSTREAMER) || \ defined(HAVE_QUICKTIME) || \ defined(HAVE_QTKIT) || \ defined(HAVE_AVFOUNDATION) || \ defined(HAVE_FFMPEG) || \ defined(WIN32) /* assume that we have ffmpeg */ # define BUILD_WITH_VIDEO_INPUT_SUPPORT 1 #else # define BUILD_WITH_VIDEO_INPUT_SUPPORT 0 #endif ////////////////////////////////////////////////////// // FGDStatModel #if BUILD_WITH_VIDEO_INPUT_SUPPORT && defined(HAVE_OPENCV_LEGACY) namespace cv { template<> void DefaultDeleter::operator ()(CvBGStatModel* obj) const { cvReleaseBGStatModel(&obj); } } PARAM_TEST_CASE(FGDStatModel, cv::cuda::DeviceInfo, std::string) { cv::cuda::DeviceInfo devInfo; std::string inputFile; virtual void SetUp() { devInfo = GET_PARAM(0); cv::cuda::setDevice(devInfo.deviceID()); inputFile = std::string(cvtest::TS::ptr()->get_data_path()) + "video/" + GET_PARAM(1); } }; CUDA_TEST_P(FGDStatModel, Update) { cv::VideoCapture cap(inputFile); ASSERT_TRUE(cap.isOpened()); cv::Mat frame; cap >> frame; ASSERT_FALSE(frame.empty()); IplImage ipl_frame = frame; cv::Ptr model(cvCreateFGDStatModel(&ipl_frame)); cv::cuda::GpuMat d_frame(frame); cv::Ptr d_fgd = cv::cuda::createBackgroundSubtractorFGD(); cv::cuda::GpuMat d_foreground, d_background; std::vector< std::vector > foreground_regions; d_fgd->apply(d_frame, d_foreground); for (int i = 0; i < 5; ++i) { cap >> frame; ASSERT_FALSE(frame.empty()); ipl_frame = frame; int gold_count = cvUpdateBGStatModel(&ipl_frame, model); d_frame.upload(frame); d_fgd->apply(d_frame, d_foreground); d_fgd->getBackgroundImage(d_background); d_fgd->getForegroundRegions(foreground_regions); int count = (int) foreground_regions.size(); cv::Mat gold_background = cv::cvarrToMat(model->background); cv::Mat gold_foreground = cv::cvarrToMat(model->foreground); ASSERT_MAT_NEAR(gold_background, d_background, 1.0); ASSERT_MAT_NEAR(gold_foreground, d_foreground, 0.0); ASSERT_EQ(gold_count, count); } } INSTANTIATE_TEST_CASE_P(CUDA_BgSegm, FGDStatModel, testing::Combine( ALL_DEVICES, testing::Values(std::string("768x576.avi")))); #endif ////////////////////////////////////////////////////// // MOG #if BUILD_WITH_VIDEO_INPUT_SUPPORT namespace { IMPLEMENT_PARAM_CLASS(UseGray, bool) IMPLEMENT_PARAM_CLASS(LearningRate, double) } PARAM_TEST_CASE(MOG, cv::cuda::DeviceInfo, std::string, UseGray, LearningRate, UseRoi) { cv::cuda::DeviceInfo devInfo; std::string inputFile; bool useGray; double learningRate; bool useRoi; virtual void SetUp() { devInfo = GET_PARAM(0); cv::cuda::setDevice(devInfo.deviceID()); inputFile = std::string(cvtest::TS::ptr()->get_data_path()) + "video/" + GET_PARAM(1); useGray = GET_PARAM(2); learningRate = GET_PARAM(3); useRoi = GET_PARAM(4); } }; CUDA_TEST_P(MOG, Update) { cv::VideoCapture cap(inputFile); ASSERT_TRUE(cap.isOpened()); cv::Mat frame; cap >> frame; ASSERT_FALSE(frame.empty()); cv::Ptr mog = cv::cuda::createBackgroundSubtractorMOG(); cv::cuda::GpuMat foreground = createMat(frame.size(), CV_8UC1, useRoi); cv::Ptr mog_gold = cv::createBackgroundSubtractorMOG(); cv::Mat foreground_gold; for (int i = 0; i < 10; ++i) { cap >> frame; ASSERT_FALSE(frame.empty()); if (useGray) { cv::Mat temp; cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY); cv::swap(temp, frame); } mog->apply(loadMat(frame, useRoi), foreground, learningRate); mog_gold->apply(frame, foreground_gold, learningRate); ASSERT_MAT_NEAR(foreground_gold, foreground, 0.0); } } INSTANTIATE_TEST_CASE_P(CUDA_BgSegm, MOG, testing::Combine( ALL_DEVICES, testing::Values(std::string("768x576.avi")), testing::Values(UseGray(true), UseGray(false)), testing::Values(LearningRate(0.0), LearningRate(0.01)), WHOLE_SUBMAT)); #endif ////////////////////////////////////////////////////// // MOG2 #if BUILD_WITH_VIDEO_INPUT_SUPPORT namespace { IMPLEMENT_PARAM_CLASS(DetectShadow, bool) } PARAM_TEST_CASE(MOG2, cv::cuda::DeviceInfo, std::string, UseGray, DetectShadow, UseRoi) { cv::cuda::DeviceInfo devInfo; std::string inputFile; bool useGray; bool detectShadow; bool useRoi; virtual void SetUp() { devInfo = GET_PARAM(0); cv::cuda::setDevice(devInfo.deviceID()); inputFile = std::string(cvtest::TS::ptr()->get_data_path()) + "video/" + GET_PARAM(1); useGray = GET_PARAM(2); detectShadow = GET_PARAM(3); useRoi = GET_PARAM(4); } }; CUDA_TEST_P(MOG2, Update) { cv::VideoCapture cap(inputFile); ASSERT_TRUE(cap.isOpened()); cv::Mat frame; cap >> frame; ASSERT_FALSE(frame.empty()); cv::Ptr mog2 = cv::cuda::createBackgroundSubtractorMOG2(); mog2->setDetectShadows(detectShadow); cv::cuda::GpuMat foreground = createMat(frame.size(), CV_8UC1, useRoi); cv::Ptr mog2_gold = cv::createBackgroundSubtractorMOG2(); mog2_gold->setDetectShadows(detectShadow); cv::Mat foreground_gold; for (int i = 0; i < 10; ++i) { cap >> frame; ASSERT_FALSE(frame.empty()); if (useGray) { cv::Mat temp; cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY); cv::swap(temp, frame); } mog2->apply(loadMat(frame, useRoi), foreground); mog2_gold->apply(frame, foreground_gold); if (detectShadow) { ASSERT_MAT_SIMILAR(foreground_gold, foreground, 1e-2); } else { ASSERT_MAT_NEAR(foreground_gold, foreground, 0); } } } CUDA_TEST_P(MOG2, getBackgroundImage) { if (useGray) return; cv::VideoCapture cap(inputFile); ASSERT_TRUE(cap.isOpened()); cv::Mat frame; cv::Ptr mog2 = cv::cuda::createBackgroundSubtractorMOG2(); mog2->setDetectShadows(detectShadow); cv::cuda::GpuMat foreground; cv::Ptr mog2_gold = cv::createBackgroundSubtractorMOG2(); mog2_gold->setDetectShadows(detectShadow); cv::Mat foreground_gold; for (int i = 0; i < 10; ++i) { cap >> frame; ASSERT_FALSE(frame.empty()); mog2->apply(loadMat(frame, useRoi), foreground); mog2_gold->apply(frame, foreground_gold); } cv::cuda::GpuMat background = createMat(frame.size(), frame.type(), useRoi); mog2->getBackgroundImage(background); cv::Mat background_gold; mog2_gold->getBackgroundImage(background_gold); ASSERT_MAT_NEAR(background_gold, background, 0); } INSTANTIATE_TEST_CASE_P(CUDA_BgSegm, MOG2, testing::Combine( ALL_DEVICES, testing::Values(std::string("768x576.avi")), testing::Values(UseGray(true), UseGray(false)), testing::Values(DetectShadow(true), DetectShadow(false)), WHOLE_SUBMAT)); #endif ////////////////////////////////////////////////////// // GMG PARAM_TEST_CASE(GMG, cv::cuda::DeviceInfo, cv::Size, MatDepth, Channels, UseRoi) { }; CUDA_TEST_P(GMG, Accuracy) { const cv::cuda::DeviceInfo devInfo = GET_PARAM(0); cv::cuda::setDevice(devInfo.deviceID()); const cv::Size size = GET_PARAM(1); const int depth = GET_PARAM(2); const int channels = GET_PARAM(3); const bool useRoi = GET_PARAM(4); const int type = CV_MAKE_TYPE(depth, channels); const cv::Mat zeros(size, CV_8UC1, cv::Scalar::all(0)); const cv::Mat fullfg(size, CV_8UC1, cv::Scalar::all(255)); cv::Mat frame = randomMat(size, type, 0, 100); cv::cuda::GpuMat d_frame = loadMat(frame, useRoi); cv::Ptr gmg = cv::cuda::createBackgroundSubtractorGMG(); gmg->setNumFrames(5); gmg->setSmoothingRadius(0); cv::cuda::GpuMat d_fgmask = createMat(size, CV_8UC1, useRoi); for (int i = 0; i < gmg->getNumFrames(); ++i) { gmg->apply(d_frame, d_fgmask); // fgmask should be entirely background during training ASSERT_MAT_NEAR(zeros, d_fgmask, 0); } frame = randomMat(size, type, 160, 255); d_frame = loadMat(frame, useRoi); gmg->apply(d_frame, d_fgmask); // now fgmask should be entirely foreground ASSERT_MAT_NEAR(fullfg, d_fgmask, 0); } INSTANTIATE_TEST_CASE_P(CUDA_BgSegm, GMG, testing::Combine( ALL_DEVICES, DIFFERENT_SIZES, testing::Values(MatType(CV_8U), MatType(CV_16U), MatType(CV_32F)), testing::Values(Channels(1), Channels(3), Channels(4)), WHOLE_SUBMAT)); #endif // HAVE_CUDA