/*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. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2015, University of Ostrava, Institute for Research and Applications of Fuzzy Modeling, // Pavel Vlasanek, 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 the copyright holders 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" namespace opencv_test { namespace { TEST(fuzzy_image, inpainting) { string folder = string(cvtest::TS::ptr()->get_data_path()) + "fuzzy/"; Mat orig = imread(folder + "orig.png"); Mat exp1 = imread(folder + "exp1.png"); Mat exp2 = imread(folder + "exp2.png"); Mat exp3 = imread(folder + "exp3.png"); Mat mask1 = imread(folder + "mask1.png", IMREAD_GRAYSCALE); Mat mask2 = imread(folder + "mask2.png", IMREAD_GRAYSCALE); EXPECT_TRUE(!orig.empty() && !exp1.empty() && !exp2.empty() && !exp3.empty() && !mask1.empty() && !mask2.empty()); Mat res1, res2, res3; ft::inpaint(orig, mask1, res1, 2, ft::LINEAR, ft::ONE_STEP); ft::inpaint(orig, mask2, res2, 2, ft::LINEAR, ft::MULTI_STEP); ft::inpaint(orig, mask2, res3, 2, ft::LINEAR, ft::ITERATIVE); res1.convertTo(res1, CV_8UC3); res2.convertTo(res2, CV_8UC3); res3.convertTo(res3, CV_8UC3); double n1 = cvtest::norm(exp1, res1, NORM_INF); double n2 = cvtest::norm(exp2, res2, NORM_INF); double n3 = cvtest::norm(exp3, res3, NORM_INF); EXPECT_LE(n1, 1); EXPECT_LE(n2, 1); EXPECT_LE(n3, 1); } TEST(fuzzy_image, filtering) { string folder = string(cvtest::TS::ptr()->get_data_path()) + "fuzzy/"; Mat orig = imread(folder + "orig.png"); Mat exp4 = imread(folder + "exp4.png"); EXPECT_TRUE(!orig.empty() && !exp4.empty()); Mat kernel; ft::createKernel(ft::LINEAR, 20, kernel, 3); Mat res4; ft::filter(orig, kernel, res4); res4.convertTo(res4, CV_8UC3); double n1 = cvtest::norm(exp4, res4, NORM_INF); EXPECT_LE(n1, 1); } TEST(fuzzy_image, kernel) { Mat kernel1; ft::createKernel(ft::LINEAR, 2, kernel1, 1); Mat vectorA = (Mat_(1, 5) << 0, 0.5, 1, 0.5, 0); Mat vectorB = (Mat_(5, 1) << 0, 0.5, 1, 0.5, 0); Mat kernel2; ft::createKernel(vectorA, vectorB, kernel2, 1); double diff = cvtest::norm(kernel1, kernel2, NORM_INF); EXPECT_DOUBLE_EQ(diff, 0); } }} // namespace