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134 lines
4.3 KiB
C++
134 lines
4.3 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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// Copyright (C) 2014, Advanced Micro Devices, Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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#include "../test_precomp.hpp"
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#include "opencv2/ts/ocl_test.hpp"
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#ifdef HAVE_OPENCL
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namespace cvtest {
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namespace ocl {
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PARAM_TEST_CASE(FastNlMeansDenoisingTestBase, Channels, int, bool, bool)
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{
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int cn, normType, templateWindowSize, searchWindowSize;
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std::vector<float> h;
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bool use_roi, use_image;
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TEST_DECLARE_INPUT_PARAMETER(src);
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TEST_DECLARE_OUTPUT_PARAMETER(dst);
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virtual void SetUp()
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{
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cn = GET_PARAM(0);
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normType = GET_PARAM(1);
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use_roi = GET_PARAM(2);
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use_image = GET_PARAM(3);
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templateWindowSize = 7;
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searchWindowSize = 21;
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h.resize(cn);
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for (int i=0; i<cn; i++)
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h[i] = 3.0f + 0.5f*i;
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}
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virtual void generateTestData()
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{
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const int type = CV_8UC(cn);
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Mat image;
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if (use_image) {
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image = readImage("denoising/lena_noised_gaussian_sigma=10.png",
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cn == 1 ? IMREAD_GRAYSCALE : IMREAD_COLOR);
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ASSERT_FALSE(image.empty());
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}
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Size roiSize = use_image ? image.size() : randomSize(1, MAX_VALUE);
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Border srcBorder = randomBorder(0, use_roi ? MAX_VALUE : 0);
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randomSubMat(src, src_roi, roiSize, srcBorder, type, 0, 255);
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if (use_image) {
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ASSERT_TRUE(cn > 0 && cn <= 4);
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if (cn == 2) {
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int from_to[] = { 0,0, 1,1 };
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src_roi.create(roiSize, type);
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mixChannels(&image, 1, &src_roi, 1, from_to, 2);
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}
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else if (cn == 4) {
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int from_to[] = { 0,0, 1,1, 2,2, 1,3};
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src_roi.create(roiSize, type);
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mixChannels(&image, 1, &src_roi, 1, from_to, 4);
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}
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else image.copyTo(src_roi);
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}
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Border dstBorder = randomBorder(0, use_roi ? MAX_VALUE : 0);
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randomSubMat(dst, dst_roi, roiSize, dstBorder, type, 0, 255);
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UMAT_UPLOAD_INPUT_PARAMETER(src);
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UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
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}
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};
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typedef FastNlMeansDenoisingTestBase FastNlMeansDenoising;
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OCL_TEST_P(FastNlMeansDenoising, Mat)
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{
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for (int j = 0; j < test_loop_times; j++)
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{
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generateTestData();
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OCL_OFF(cv::fastNlMeansDenoising(src_roi, dst_roi, std::vector<float>(1, h[0]), templateWindowSize, searchWindowSize, normType));
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OCL_ON(cv::fastNlMeansDenoising(usrc_roi, udst_roi, std::vector<float>(1, h[0]), templateWindowSize, searchWindowSize, normType));
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OCL_EXPECT_MATS_NEAR(dst, 1);
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}
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}
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typedef FastNlMeansDenoisingTestBase FastNlMeansDenoising_hsep;
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OCL_TEST_P(FastNlMeansDenoising_hsep, Mat)
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{
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for (int j = 0; j < test_loop_times; j++)
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{
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generateTestData();
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OCL_OFF(cv::fastNlMeansDenoising(src_roi, dst_roi, h, templateWindowSize, searchWindowSize, normType));
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OCL_ON(cv::fastNlMeansDenoising(usrc_roi, udst_roi, h, templateWindowSize, searchWindowSize, normType));
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OCL_EXPECT_MATS_NEAR(dst, 1);
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}
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}
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typedef FastNlMeansDenoisingTestBase FastNlMeansDenoisingColored;
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OCL_TEST_P(FastNlMeansDenoisingColored, Mat)
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{
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for (int j = 0; j < test_loop_times; j++)
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{
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generateTestData();
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OCL_OFF(cv::fastNlMeansDenoisingColored(src_roi, dst_roi, h[0], h[0], templateWindowSize, searchWindowSize));
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OCL_ON(cv::fastNlMeansDenoisingColored(usrc_roi, udst_roi, h[0], h[0], templateWindowSize, searchWindowSize));
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OCL_EXPECT_MATS_NEAR(dst, 1);
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}
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}
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OCL_INSTANTIATE_TEST_CASE_P(Photo, FastNlMeansDenoising,
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Combine(Values(1, 2, 3, 4), Values((int)NORM_L2, (int)NORM_L1),
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Bool(), Values(true)));
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OCL_INSTANTIATE_TEST_CASE_P(Photo, FastNlMeansDenoising_hsep,
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Combine(Values(1, 2, 3, 4), Values((int)NORM_L2, (int)NORM_L1),
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Bool(), Values(true)));
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OCL_INSTANTIATE_TEST_CASE_P(Photo, FastNlMeansDenoisingColored,
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Combine(Values(3, 4), Values((int)NORM_L2), Bool(), Values(false)));
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} } // namespace cvtest::ocl
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#endif // HAVE_OPENCL
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