// 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 cvtest { namespace ocl { PARAM_TEST_CASE(FastNlMeansDenoisingTestBase, Channels, int, bool, bool) { int cn, normType, templateWindowSize, searchWindowSize; std::vector 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 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(1, h[0]), templateWindowSize, searchWindowSize, normType)); OCL_ON(cv::fastNlMeansDenoising(usrc_roi, udst_roi, std::vector(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 cvtest::ocl #endif // HAVE_OPENCL