OpenCV_4.2.0/opencv-4.2.0/modules/photo/test/ocl/test_denoising.cpp

134 lines
4.3 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 "../test_precomp.hpp"
#include "opencv2/ts/ocl_test.hpp"
#ifdef HAVE_OPENCL
namespace opencv_test {
namespace ocl {
PARAM_TEST_CASE(FastNlMeansDenoisingTestBase, Channels, int, bool, bool)
{
int cn, normType, templateWindowSize, searchWindowSize;
std::vector<float> h;
bool use_roi, use_image;
TEST_DECLARE_INPUT_PARAMETER(src);
TEST_DECLARE_OUTPUT_PARAMETER(dst);
virtual void SetUp()
{
cn = GET_PARAM(0);
normType = GET_PARAM(1);
use_roi = GET_PARAM(2);
use_image = GET_PARAM(3);
templateWindowSize = 7;
searchWindowSize = 21;
h.resize(cn);
for (int i=0; i<cn; i++)
h[i] = 3.0f + 0.5f*i;
}
void generateTestData()
{
const int type = CV_8UC(cn);
Mat image;
if (use_image) {
image = readImage("denoising/lena_noised_gaussian_sigma=10.png",
cn == 1 ? IMREAD_GRAYSCALE : IMREAD_COLOR);
ASSERT_FALSE(image.empty());
}
Size roiSize = use_image ? image.size() : randomSize(1, MAX_VALUE);
Border srcBorder = randomBorder(0, use_roi ? MAX_VALUE : 0);
randomSubMat(src, src_roi, roiSize, srcBorder, type, 0, 255);
if (use_image) {
ASSERT_TRUE(cn > 0 && cn <= 4);
if (cn == 2) {
int from_to[] = { 0,0, 1,1 };
src_roi.create(roiSize, type);
mixChannels(&image, 1, &src_roi, 1, from_to, 2);
}
else if (cn == 4) {
int from_to[] = { 0,0, 1,1, 2,2, 1,3};
src_roi.create(roiSize, type);
mixChannels(&image, 1, &src_roi, 1, from_to, 4);
}
else image.copyTo(src_roi);
}
Border dstBorder = randomBorder(0, use_roi ? MAX_VALUE : 0);
randomSubMat(dst, dst_roi, roiSize, dstBorder, type, 0, 255);
UMAT_UPLOAD_INPUT_PARAMETER(src);
UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
}
};
typedef FastNlMeansDenoisingTestBase FastNlMeansDenoising;
OCL_TEST_P(FastNlMeansDenoising, Mat)
{
for (int j = 0; j < test_loop_times; j++)
{
generateTestData();
OCL_OFF(cv::fastNlMeansDenoising(src_roi, dst_roi, std::vector<float>(1, h[0]), templateWindowSize, searchWindowSize, normType));
OCL_ON(cv::fastNlMeansDenoising(usrc_roi, udst_roi, std::vector<float>(1, h[0]), templateWindowSize, searchWindowSize, normType));
OCL_EXPECT_MATS_NEAR(dst, 1);
}
}
typedef FastNlMeansDenoisingTestBase FastNlMeansDenoising_hsep;
OCL_TEST_P(FastNlMeansDenoising_hsep, Mat)
{
for (int j = 0; j < test_loop_times; j++)
{
generateTestData();
OCL_OFF(cv::fastNlMeansDenoising(src_roi, dst_roi, h, templateWindowSize, searchWindowSize, normType));
OCL_ON(cv::fastNlMeansDenoising(usrc_roi, udst_roi, h, templateWindowSize, searchWindowSize, normType));
OCL_EXPECT_MATS_NEAR(dst, 1);
}
}
typedef FastNlMeansDenoisingTestBase FastNlMeansDenoisingColored;
OCL_TEST_P(FastNlMeansDenoisingColored, Mat)
{
for (int j = 0; j < test_loop_times; j++)
{
generateTestData();
OCL_OFF(cv::fastNlMeansDenoisingColored(src_roi, dst_roi, h[0], h[0], templateWindowSize, searchWindowSize));
OCL_ON(cv::fastNlMeansDenoisingColored(usrc_roi, udst_roi, h[0], h[0], templateWindowSize, searchWindowSize));
OCL_EXPECT_MATS_NEAR(dst, 1);
}
}
OCL_INSTANTIATE_TEST_CASE_P(Photo, FastNlMeansDenoising,
Combine(Values(1, 2, 3, 4), Values((int)NORM_L2, (int)NORM_L1),
Bool(), Values(true)));
OCL_INSTANTIATE_TEST_CASE_P(Photo, FastNlMeansDenoising_hsep,
Combine(Values(1, 2, 3, 4), Values((int)NORM_L2, (int)NORM_L1),
Bool(), Values(true)));
OCL_INSTANTIATE_TEST_CASE_P(Photo, FastNlMeansDenoisingColored,
Combine(Values(3, 4), Values((int)NORM_L2), Bool(), Values(false)));
} } // namespace opencv_test::ocl
#endif // HAVE_OPENCL