/*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_CUDA using namespace cvtest; //////////////////////////////////////////////////////////////////////////////// // MeanShift struct MeanShift : testing::TestWithParam { cv::cuda::DeviceInfo devInfo; cv::Mat img; int spatialRad; int colorRad; virtual void SetUp() { devInfo = GetParam(); cv::cuda::setDevice(devInfo.deviceID()); img = readImageType("meanshift/cones.png", CV_8UC4); ASSERT_FALSE(img.empty()); spatialRad = 30; colorRad = 30; } }; GPU_TEST_P(MeanShift, Filtering) { cv::Mat img_template; if (supportFeature(devInfo, cv::cuda::FEATURE_SET_COMPUTE_20)) img_template = readImage("meanshift/con_result.png"); else img_template = readImage("meanshift/con_result_CC1X.png"); ASSERT_FALSE(img_template.empty()); cv::cuda::GpuMat d_dst; cv::cuda::meanShiftFiltering(loadMat(img), d_dst, spatialRad, colorRad); ASSERT_EQ(CV_8UC4, d_dst.type()); cv::Mat dst(d_dst); cv::Mat result; cv::cvtColor(dst, result, cv::COLOR_BGRA2BGR); EXPECT_MAT_NEAR(img_template, result, 0.0); } GPU_TEST_P(MeanShift, Proc) { cv::FileStorage fs; if (supportFeature(devInfo, cv::cuda::FEATURE_SET_COMPUTE_20)) fs.open(std::string(cvtest::TS::ptr()->get_data_path()) + "meanshift/spmap.yaml", cv::FileStorage::READ); else fs.open(std::string(cvtest::TS::ptr()->get_data_path()) + "meanshift/spmap_CC1X.yaml", cv::FileStorage::READ); ASSERT_TRUE(fs.isOpened()); cv::Mat spmap_template; fs["spmap"] >> spmap_template; ASSERT_FALSE(spmap_template.empty()); cv::cuda::GpuMat rmap_filtered; cv::cuda::meanShiftFiltering(loadMat(img), rmap_filtered, spatialRad, colorRad); cv::cuda::GpuMat rmap; cv::cuda::GpuMat spmap; cv::cuda::meanShiftProc(loadMat(img), rmap, spmap, spatialRad, colorRad); ASSERT_EQ(CV_8UC4, rmap.type()); EXPECT_MAT_NEAR(rmap_filtered, rmap, 0.0); EXPECT_MAT_NEAR(spmap_template, spmap, 0.0); } INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MeanShift, ALL_DEVICES); //////////////////////////////////////////////////////////////////////////////// // MeanShiftSegmentation namespace { IMPLEMENT_PARAM_CLASS(MinSize, int); } PARAM_TEST_CASE(MeanShiftSegmentation, cv::cuda::DeviceInfo, MinSize) { cv::cuda::DeviceInfo devInfo; int minsize; virtual void SetUp() { devInfo = GET_PARAM(0); minsize = GET_PARAM(1); cv::cuda::setDevice(devInfo.deviceID()); } }; GPU_TEST_P(MeanShiftSegmentation, Regression) { cv::Mat img = readImageType("meanshift/cones.png", CV_8UC4); ASSERT_FALSE(img.empty()); std::ostringstream path; path << "meanshift/cones_segmented_sp10_sr10_minsize" << minsize; if (supportFeature(devInfo, cv::cuda::FEATURE_SET_COMPUTE_20)) path << ".png"; else path << "_CC1X.png"; cv::Mat dst_gold = readImage(path.str()); ASSERT_FALSE(dst_gold.empty()); cv::Mat dst; cv::cuda::meanShiftSegmentation(loadMat(img), dst, 10, 10, minsize); cv::Mat dst_rgb; cv::cvtColor(dst, dst_rgb, cv::COLOR_BGRA2BGR); EXPECT_MAT_SIMILAR(dst_gold, dst_rgb, 1e-3); } INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MeanShiftSegmentation, testing::Combine( ALL_DEVICES, testing::Values(MinSize(0), MinSize(4), MinSize(20), MinSize(84), MinSize(340), MinSize(1364)))); #endif // HAVE_CUDA