mirror of
https://github.com/opencv/opencv.git
synced 2024-12-11 14:39:11 +08:00
98 lines
2.9 KiB
C++
98 lines
2.9 KiB
C++
// This file is part of OpenCV project.
|
|
// It is subject to the license terms in the LICENSE file found in the top-level directory
|
|
// of this distribution and at http://opencv.org/license.html.
|
|
|
|
// Copyright (C) 2014, Advanced Micro Devices, Inc., all rights reserved.
|
|
// Third party copyrights are property of their respective owners.
|
|
|
|
#include "../perf_precomp.hpp"
|
|
#include "opencv2/ts/ocl_perf.hpp"
|
|
|
|
#ifdef HAVE_OPENCL
|
|
|
|
namespace cvtest {
|
|
namespace ocl {
|
|
|
|
OCL_PERF_TEST(Photo, DenoisingGrayscale)
|
|
{
|
|
Mat _original = imread(getDataPath("cv/denoising/lena_noised_gaussian_sigma=10.png"), IMREAD_GRAYSCALE);
|
|
ASSERT_FALSE(_original.empty()) << "Could not load input image";
|
|
|
|
UMat result(_original.size(), _original.type()), original;
|
|
_original.copyTo(original);
|
|
|
|
declare.in(original).out(result).iterations(10);
|
|
|
|
OCL_TEST_CYCLE()
|
|
cv::fastNlMeansDenoising(original, result, 10);
|
|
|
|
SANITY_CHECK(result, 1);
|
|
}
|
|
|
|
OCL_PERF_TEST(Photo, DenoisingColored)
|
|
{
|
|
Mat _original = imread(getDataPath("cv/denoising/lena_noised_gaussian_sigma=10.png"));
|
|
ASSERT_FALSE(_original.empty()) << "Could not load input image";
|
|
|
|
UMat result(_original.size(), _original.type()), original;
|
|
_original.copyTo(original);
|
|
|
|
declare.in(original).out(result).iterations(10);
|
|
|
|
OCL_TEST_CYCLE()
|
|
cv::fastNlMeansDenoisingColored(original, result, 10, 10);
|
|
|
|
SANITY_CHECK(result, 2);
|
|
}
|
|
|
|
OCL_PERF_TEST(Photo, DISABLED_DenoisingGrayscaleMulti)
|
|
{
|
|
const int imgs_count = 3;
|
|
|
|
vector<UMat> original(imgs_count);
|
|
Mat tmp;
|
|
for (int i = 0; i < imgs_count; i++)
|
|
{
|
|
string original_path = format("cv/denoising/lena_noised_gaussian_sigma=20_multi_%d.png", i);
|
|
tmp = imread(getDataPath(original_path), IMREAD_GRAYSCALE);
|
|
ASSERT_FALSE(tmp.empty()) << "Could not load input image " << original_path;
|
|
tmp.copyTo(original[i]);
|
|
declare.in(original[i]);
|
|
}
|
|
UMat result(tmp.size(), tmp.type());
|
|
declare.out(result).iterations(10);
|
|
|
|
OCL_TEST_CYCLE()
|
|
cv::fastNlMeansDenoisingMulti(original, result, imgs_count / 2, imgs_count, 15);
|
|
|
|
SANITY_CHECK(result);
|
|
}
|
|
|
|
OCL_PERF_TEST(Photo, DISABLED_DenoisingColoredMulti)
|
|
{
|
|
const int imgs_count = 3;
|
|
|
|
vector<UMat> original(imgs_count);
|
|
Mat tmp;
|
|
for (int i = 0; i < imgs_count; i++)
|
|
{
|
|
string original_path = format("cv/denoising/lena_noised_gaussian_sigma=20_multi_%d.png", i);
|
|
tmp = imread(getDataPath(original_path), IMREAD_COLOR);
|
|
ASSERT_FALSE(tmp.empty()) << "Could not load input image " << original_path;
|
|
|
|
tmp.copyTo(original[i]);
|
|
declare.in(original[i]);
|
|
}
|
|
UMat result(tmp.size(), tmp.type());
|
|
declare.out(result).iterations(10);
|
|
|
|
OCL_TEST_CYCLE()
|
|
cv::fastNlMeansDenoisingColoredMulti(original, result, imgs_count / 2, imgs_count, 10, 15);
|
|
|
|
SANITY_CHECK(result);
|
|
}
|
|
|
|
} } // namespace cvtest::ocl
|
|
|
|
#endif // HAVE_OPENCL
|