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Open Source Computer Vision Library
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247 lines
9.9 KiB
247 lines
9.9 KiB
/*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) 2013, OpenCV Foundation, all rights reserved. |
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// 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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namespace opencv_test { namespace { |
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#define OUTPUT_SAVING 0 |
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#if OUTPUT_SAVING |
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#define SAVE(x) std::vector<int> params;\ |
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params.push_back(16);\ |
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params.push_back(0);\ |
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imwrite(folder + "output.png", x ,params); |
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#else |
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#define SAVE(x) |
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#endif |
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static const double numerical_precision = 0.05; // 95% of pixels should have exact values |
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TEST(Photo_SeamlessClone_normal, regression) |
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{ |
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string folder = string(cvtest::TS::ptr()->get_data_path()) + "cloning/Normal_Cloning/"; |
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string original_path1 = folder + "source1.png"; |
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string original_path2 = folder + "destination1.png"; |
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string original_path3 = folder + "mask.png"; |
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string reference_path = folder + "reference.png"; |
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Mat source = imread(original_path1, IMREAD_COLOR); |
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Mat destination = imread(original_path2, IMREAD_COLOR); |
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Mat mask = imread(original_path3, IMREAD_COLOR); |
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ASSERT_FALSE(source.empty()) << "Could not load source image " << original_path1; |
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ASSERT_FALSE(destination.empty()) << "Could not load destination image " << original_path2; |
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ASSERT_FALSE(mask.empty()) << "Could not load mask image " << original_path3; |
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Mat result; |
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Point p; |
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p.x = destination.size().width/2; |
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p.y = destination.size().height/2; |
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seamlessClone(source, destination, mask, p, result, 1); |
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Mat reference = imread(reference_path); |
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ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path; |
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SAVE(result); |
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double errorINF = cvtest::norm(reference, result, NORM_INF); |
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EXPECT_LE(errorINF, 1); |
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double errorL1 = cvtest::norm(reference, result, NORM_L1); |
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EXPECT_LE(errorL1, reference.total() * numerical_precision) << "size=" << reference.size(); |
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mask = Scalar(0, 0, 0); |
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seamlessClone(source, destination, mask, p, result, 1); |
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reference = destination; |
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errorINF = cvtest::norm(reference, result, NORM_INF); |
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EXPECT_LE(errorINF, 1); |
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errorL1 = cvtest::norm(reference, result, NORM_L1); |
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EXPECT_LE(errorL1, reference.total() * numerical_precision) << "size=" << reference.size(); |
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} |
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TEST(Photo_SeamlessClone_mixed, regression) |
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{ |
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string folder = string(cvtest::TS::ptr()->get_data_path()) + "cloning/Mixed_Cloning/"; |
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string original_path1 = folder + "source1.png"; |
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string original_path2 = folder + "destination1.png"; |
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string original_path3 = folder + "mask.png"; |
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string reference_path = folder + "reference.png"; |
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Mat source = imread(original_path1, IMREAD_COLOR); |
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Mat destination = imread(original_path2, IMREAD_COLOR); |
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Mat mask = imread(original_path3, IMREAD_COLOR); |
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ASSERT_FALSE(source.empty()) << "Could not load source image " << original_path1; |
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ASSERT_FALSE(destination.empty()) << "Could not load destination image " << original_path2; |
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ASSERT_FALSE(mask.empty()) << "Could not load mask image " << original_path3; |
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Mat result; |
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Point p; |
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p.x = destination.size().width/2; |
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p.y = destination.size().height/2; |
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seamlessClone(source, destination, mask, p, result, 2); |
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SAVE(result); |
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Mat reference = imread(reference_path); |
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ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path; |
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double errorINF = cvtest::norm(reference, result, NORM_INF); |
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EXPECT_LE(errorINF, 1); |
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double errorL1 = cvtest::norm(reference, result, NORM_L1); |
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EXPECT_LE(errorL1, reference.total() * numerical_precision) << "size=" << reference.size(); |
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} |
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TEST(Photo_SeamlessClone_featureExchange, regression) |
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{ |
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string folder = string(cvtest::TS::ptr()->get_data_path()) + "cloning/Monochrome_Transfer/"; |
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string original_path1 = folder + "source1.png"; |
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string original_path2 = folder + "destination1.png"; |
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string original_path3 = folder + "mask.png"; |
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string reference_path = folder + "reference.png"; |
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Mat source = imread(original_path1, IMREAD_COLOR); |
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Mat destination = imread(original_path2, IMREAD_COLOR); |
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Mat mask = imread(original_path3, IMREAD_COLOR); |
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ASSERT_FALSE(source.empty()) << "Could not load source image " << original_path1; |
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ASSERT_FALSE(destination.empty()) << "Could not load destination image " << original_path2; |
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ASSERT_FALSE(mask.empty()) << "Could not load mask image " << original_path3; |
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Mat result; |
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Point p; |
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p.x = destination.size().width/2; |
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p.y = destination.size().height/2; |
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seamlessClone(source, destination, mask, p, result, 3); |
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SAVE(result); |
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Mat reference = imread(reference_path); |
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ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path; |
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double errorINF = cvtest::norm(reference, result, NORM_INF); |
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EXPECT_LE(errorINF, 1); |
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double errorL1 = cvtest::norm(reference, result, NORM_L1); |
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EXPECT_LE(errorL1, reference.total() * numerical_precision) << "size=" << reference.size(); |
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} |
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TEST(Photo_SeamlessClone_colorChange, regression) |
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{ |
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string folder = string(cvtest::TS::ptr()->get_data_path()) + "cloning/color_change/"; |
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string original_path1 = folder + "source1.png"; |
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string original_path2 = folder + "mask.png"; |
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string reference_path = folder + "reference.png"; |
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Mat source = imread(original_path1, IMREAD_COLOR); |
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Mat mask = imread(original_path2, IMREAD_COLOR); |
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ASSERT_FALSE(source.empty()) << "Could not load source image " << original_path1; |
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ASSERT_FALSE(mask.empty()) << "Could not load mask image " << original_path2; |
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Mat result; |
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colorChange(source, mask, result, 1.5, .5, .5); |
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SAVE(result); |
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Mat reference = imread(reference_path); |
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ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path; |
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double errorINF = cvtest::norm(reference, result, NORM_INF); |
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EXPECT_LE(errorINF, 1); |
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double errorL1 = cvtest::norm(reference, result, NORM_L1); |
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EXPECT_LE(errorL1, reference.total() * numerical_precision) << "size=" << reference.size(); |
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} |
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TEST(Photo_SeamlessClone_illuminationChange, regression) |
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{ |
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string folder = string(cvtest::TS::ptr()->get_data_path()) + "cloning/Illumination_Change/"; |
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string original_path1 = folder + "source1.png"; |
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string original_path2 = folder + "mask.png"; |
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string reference_path = folder + "reference.png"; |
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Mat source = imread(original_path1, IMREAD_COLOR); |
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Mat mask = imread(original_path2, IMREAD_COLOR); |
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ASSERT_FALSE(source.empty()) << "Could not load source image " << original_path1; |
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ASSERT_FALSE(mask.empty()) << "Could not load mask image " << original_path2; |
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Mat result; |
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illuminationChange(source, mask, result, 0.2f, 0.4f); |
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SAVE(result); |
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Mat reference = imread(reference_path); |
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ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path; |
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double errorINF = cvtest::norm(reference, result, NORM_INF); |
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EXPECT_LE(errorINF, 1); |
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double errorL1 = cvtest::norm(reference, result, NORM_L1); |
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EXPECT_LE(errorL1, reference.total() * numerical_precision) << "size=" << reference.size(); |
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} |
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TEST(Photo_SeamlessClone_textureFlattening, regression) |
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{ |
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string folder = string(cvtest::TS::ptr()->get_data_path()) + "cloning/Texture_Flattening/"; |
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string original_path1 = folder + "source1.png"; |
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string original_path2 = folder + "mask.png"; |
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string reference_path = folder + "reference.png"; |
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Mat source = imread(original_path1, IMREAD_COLOR); |
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Mat mask = imread(original_path2, IMREAD_COLOR); |
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ASSERT_FALSE(source.empty()) << "Could not load source image " << original_path1; |
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ASSERT_FALSE(mask.empty()) << "Could not load mask image " << original_path2; |
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Mat result; |
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textureFlattening(source, mask, result, 30, 45, 3); |
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SAVE(result); |
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Mat reference = imread(reference_path); |
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ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path; |
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double errorINF = cvtest::norm(reference, result, NORM_INF); |
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EXPECT_LE(errorINF, 1); |
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double errorL1 = cvtest::norm(reference, result, NORM_L1); |
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EXPECT_LE(errorL1, reference.total() * numerical_precision) << "size=" << reference.size(); |
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} |
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}} // namespace
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