mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
182 lines
5.9 KiB
182 lines
5.9 KiB
/*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. |
|
// |
|
// |
|
// Intel License Agreement |
|
// For Open Source Computer Vision Library |
|
// |
|
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 |
|
|
|
//////////////////////////////////////////////////////// |
|
// 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> |
|
{ |
|
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> |
|
{ |
|
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
|
|
|