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https://github.com/opencv/opencv_contrib.git
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ca6ccac67f
Incremental commit. Theory updated. Theory finished. Inpainting in progress. Inpainting done plus minor fix in kernel computation. Tutorials done. Documentation done. Whitespace fix. Update. Conversion to jpg. Documentation links fixed.
114 lines
4.1 KiB
C++
114 lines
4.1 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2015, University of Ostrava, Institute for Research and Applications of Fuzzy Modeling,
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// Pavel Vlasanek, all rights reserved. Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "test_precomp.hpp"
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#include <string>
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using namespace std;
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using namespace cv;
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TEST(fuzzy_image, inpainting)
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{
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string folder = string(cvtest::TS::ptr()->get_data_path()) + "fuzzy/";
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Mat orig = imread(folder + "orig.png");
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Mat exp1 = imread(folder + "exp1.png");
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Mat exp2 = imread(folder + "exp2.png");
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Mat exp3 = imread(folder + "exp3.png");
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Mat mask1 = imread(folder + "mask1.png", IMREAD_GRAYSCALE);
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Mat mask2 = imread(folder + "mask2.png", IMREAD_GRAYSCALE);
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EXPECT_TRUE(!orig.empty() && !exp1.empty() && !exp2.empty() && !exp3.empty() && !mask1.empty() && !mask2.empty());
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Mat res1, res2, res3;
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ft::inpaint(orig, mask1, res1, 2, ft::LINEAR, ft::ONE_STEP);
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ft::inpaint(orig, mask2, res2, 2, ft::LINEAR, ft::MULTI_STEP);
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ft::inpaint(orig, mask2, res3, 2, ft::LINEAR, ft::ITERATIVE);
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res1.convertTo(res1, CV_8UC3);
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res2.convertTo(res2, CV_8UC3);
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res3.convertTo(res3, CV_8UC3);
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double n1 = cvtest::norm(exp1, res1, NORM_INF);
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double n2 = cvtest::norm(exp2, res2, NORM_INF);
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double n3 = cvtest::norm(exp3, res3, NORM_INF);
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EXPECT_LE(n1, 1);
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EXPECT_LE(n2, 1);
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EXPECT_LE(n3, 1);
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}
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TEST(fuzzy_image, filtering)
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{
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string folder = string(cvtest::TS::ptr()->get_data_path()) + "fuzzy/";
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Mat orig = imread(folder + "orig.png");
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Mat exp4 = imread(folder + "exp4.png");
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EXPECT_TRUE(!orig.empty() && !exp4.empty());
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Mat kernel;
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ft::createKernel(ft::LINEAR, 20, kernel, 3);
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Mat res4;
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ft::filter(orig, kernel, res4);
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res4.convertTo(res4, CV_8UC3);
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double n1 = cvtest::norm(exp4, res4, NORM_INF);
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EXPECT_LE(n1, 1);
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}
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TEST(fuzzy_image, kernel)
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{
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Mat kernel1;
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ft::createKernel(ft::LINEAR, 2, kernel1, 1);
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Mat vectorA = (Mat_<float>(1, 5) << 0, 0.5, 1, 0.5, 0);
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Mat vectorB = (Mat_<float>(5, 1) << 0, 0.5, 1, 0.5, 0);
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Mat kernel2;
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ft::createKernel(vectorA, vectorB, kernel2, 1);
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double diff = cvtest::norm(kernel1, kernel2, NORM_INF);
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EXPECT_DOUBLE_EQ(diff, 0);
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} |