/*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; //////////////////////////////////////////////////////// // BilateralFilter PARAM_TEST_CASE(BilateralFilter, cv::gpu::DeviceInfo, cv::Size, MatType) { cv::gpu::DeviceInfo devInfo; cv::Size size; int type; int kernel_size; float sigma_color; float sigma_spatial; virtual void SetUp() { devInfo = GET_PARAM(0); size = GET_PARAM(1); type = GET_PARAM(2); kernel_size = 5; sigma_color = 10.f; sigma_spatial = 3.5f; cv::gpu::setDevice(devInfo.deviceID()); } }; GPU_TEST_P(BilateralFilter, Accuracy) { cv::Mat src = randomMat(size, type); src.convertTo(src, type); cv::gpu::GpuMat dst; cv::gpu::bilateralFilter(loadMat(src), dst, kernel_size, sigma_color, sigma_spatial); cv::Mat dst_gold; cv::bilateralFilter(src, dst_gold, kernel_size, sigma_color, sigma_spatial); EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-3 : 1.0); } INSTANTIATE_TEST_CASE_P(GPU_Denoising, BilateralFilter, testing::Combine( ALL_DEVICES, testing::Values(cv::Size(128, 128), cv::Size(113, 113), cv::Size(639, 481)), testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_32FC1), MatType(CV_32FC3)) )); //////////////////////////////////////////////////////// // Brute Force Non local means struct BruteForceNonLocalMeans: testing::TestWithParam { cv::gpu::DeviceInfo devInfo; virtual void SetUp() { devInfo = GetParam(); cv::gpu::setDevice(devInfo.deviceID()); } }; GPU_TEST_P(BruteForceNonLocalMeans, Regression) { using cv::gpu::GpuMat; cv::Mat bgr = readImage("denoising/lena_noised_gaussian_sigma=20_multi_0.png", cv::IMREAD_COLOR); ASSERT_FALSE(bgr.empty()); cv::Mat gray; cv::cvtColor(bgr, gray, CV_BGR2GRAY); GpuMat dbgr, dgray; cv::gpu::nonLocalMeans(GpuMat(bgr), dbgr, 20); cv::gpu::nonLocalMeans(GpuMat(gray), dgray, 20); #if 0 dumpImage("denoising/nlm_denoised_lena_bgr.png", cv::Mat(dbgr)); dumpImage("denoising/nlm_denoised_lena_gray.png", cv::Mat(dgray)); #endif cv::Mat bgr_gold = readImage("denoising/nlm_denoised_lena_bgr.png", cv::IMREAD_COLOR); cv::Mat gray_gold = readImage("denoising/nlm_denoised_lena_gray.png", cv::IMREAD_GRAYSCALE); ASSERT_FALSE(bgr_gold.empty() || gray_gold.empty()); EXPECT_MAT_NEAR(bgr_gold, dbgr, 1e-4); EXPECT_MAT_NEAR(gray_gold, dgray, 1e-4); } INSTANTIATE_TEST_CASE_P(GPU_Denoising, BruteForceNonLocalMeans, ALL_DEVICES); //////////////////////////////////////////////////////// // Fast Force Non local means struct FastNonLocalMeans: testing::TestWithParam { cv::gpu::DeviceInfo devInfo; virtual void SetUp() { devInfo = GetParam(); cv::gpu::setDevice(devInfo.deviceID()); } }; GPU_TEST_P(FastNonLocalMeans, Regression) { using cv::gpu::GpuMat; cv::Mat bgr = readImage("denoising/lena_noised_gaussian_sigma=20_multi_0.png", cv::IMREAD_COLOR); ASSERT_FALSE(bgr.empty()); cv::Mat gray; cv::cvtColor(bgr, gray, CV_BGR2GRAY); GpuMat dbgr, dgray; cv::gpu::FastNonLocalMeansDenoising fnlmd; fnlmd.simpleMethod(GpuMat(gray), dgray, 20); fnlmd.labMethod(GpuMat(bgr), dbgr, 20, 10); #if 0 dumpImage("denoising/fnlm_denoised_lena_bgr.png", cv::Mat(dbgr)); dumpImage("denoising/fnlm_denoised_lena_gray.png", cv::Mat(dgray)); #endif cv::Mat bgr_gold = readImage("denoising/fnlm_denoised_lena_bgr.png", cv::IMREAD_COLOR); cv::Mat gray_gold = readImage("denoising/fnlm_denoised_lena_gray.png", cv::IMREAD_GRAYSCALE); ASSERT_FALSE(bgr_gold.empty() || gray_gold.empty()); EXPECT_MAT_NEAR(bgr_gold, dbgr, 1); EXPECT_MAT_NEAR(gray_gold, dgray, 1); } INSTANTIATE_TEST_CASE_P(GPU_Denoising, FastNonLocalMeans, ALL_DEVICES); #endif // HAVE_CUDA