/*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) 2013, OpenCV Foundation, 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*/ #define OUTPUT_SAVING 0 #if OUTPUT_SAVING #define SAVE(x) std::vector params;\ params.push_back(16);\ params.push_back(0);\ imwrite(folder + "output.png", x ,params); #else #define SAVE(x) #endif #include "test_precomp.hpp" #include "opencv2/photo.hpp" #include using namespace cv; using namespace std; static const double numerical_precision = 1000.; TEST(Photo_SeamlessClone_normal, regression) { string folder = string(cvtest::TS::ptr()->get_data_path()) + "cloning/Normal_Cloning/"; string original_path1 = folder + "source1.png"; string original_path2 = folder + "destination1.png"; string original_path3 = folder + "mask.png"; string reference_path = folder + "reference.png"; Mat source = imread(original_path1, IMREAD_COLOR); Mat destination = imread(original_path2, IMREAD_COLOR); Mat mask = imread(original_path3, IMREAD_COLOR); ASSERT_FALSE(source.empty()) << "Could not load source image " << original_path1; ASSERT_FALSE(destination.empty()) << "Could not load destination image " << original_path2; ASSERT_FALSE(mask.empty()) << "Could not load mask image " << original_path3; Mat result; Point p; p.x = destination.size().width/2; p.y = destination.size().height/2; seamlessClone(source, destination, mask, p, result, 1); Mat reference = imread(reference_path); ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path; SAVE(result); double error = cvtest::norm(reference, result, NORM_L1); EXPECT_LE(error, numerical_precision); } TEST(Photo_SeamlessClone_mixed, regression) { string folder = string(cvtest::TS::ptr()->get_data_path()) + "cloning/Mixed_Cloning/"; string original_path1 = folder + "source1.png"; string original_path2 = folder + "destination1.png"; string original_path3 = folder + "mask.png"; string reference_path = folder + "reference.png"; Mat source = imread(original_path1, IMREAD_COLOR); Mat destination = imread(original_path2, IMREAD_COLOR); Mat mask = imread(original_path3, IMREAD_COLOR); ASSERT_FALSE(source.empty()) << "Could not load source image " << original_path1; ASSERT_FALSE(destination.empty()) << "Could not load destination image " << original_path2; ASSERT_FALSE(mask.empty()) << "Could not load mask image " << original_path3; Mat result; Point p; p.x = destination.size().width/2; p.y = destination.size().height/2; seamlessClone(source, destination, mask, p, result, 2); SAVE(result); Mat reference = imread(reference_path); ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path; double error = cvtest::norm(reference, result, NORM_L1); EXPECT_LE(error, numerical_precision); } TEST(Photo_SeamlessClone_featureExchange, regression) { string folder = string(cvtest::TS::ptr()->get_data_path()) + "cloning/Monochrome_Transfer/"; string original_path1 = folder + "source1.png"; string original_path2 = folder + "destination1.png"; string original_path3 = folder + "mask.png"; string reference_path = folder + "reference.png"; Mat source = imread(original_path1, IMREAD_COLOR); Mat destination = imread(original_path2, IMREAD_COLOR); Mat mask = imread(original_path3, IMREAD_COLOR); ASSERT_FALSE(source.empty()) << "Could not load source image " << original_path1; ASSERT_FALSE(destination.empty()) << "Could not load destination image " << original_path2; ASSERT_FALSE(mask.empty()) << "Could not load mask image " << original_path3; Mat result; Point p; p.x = destination.size().width/2; p.y = destination.size().height/2; seamlessClone(source, destination, mask, p, result, 3); SAVE(result); Mat reference = imread(reference_path); ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path; double error = cvtest::norm(reference, result, NORM_L1); EXPECT_LE(error, numerical_precision); } TEST(Photo_SeamlessClone_colorChange, regression) { string folder = string(cvtest::TS::ptr()->get_data_path()) + "cloning/color_change/"; string original_path1 = folder + "source1.png"; string original_path2 = folder + "mask.png"; string reference_path = folder + "reference.png"; Mat source = imread(original_path1, IMREAD_COLOR); Mat mask = imread(original_path2, IMREAD_COLOR); ASSERT_FALSE(source.empty()) << "Could not load source image " << original_path1; ASSERT_FALSE(mask.empty()) << "Could not load mask image " << original_path2; Mat result; colorChange(source, mask, result, 1.5, .5, .5); SAVE(result); Mat reference = imread(reference_path); ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path; double error = cvtest::norm(reference, result, NORM_L1); EXPECT_LE(error, numerical_precision); } TEST(Photo_SeamlessClone_illuminationChange, regression) { string folder = string(cvtest::TS::ptr()->get_data_path()) + "cloning/Illumination_Change/"; string original_path1 = folder + "source1.png"; string original_path2 = folder + "mask.png"; string reference_path = folder + "reference.png"; Mat source = imread(original_path1, IMREAD_COLOR); Mat mask = imread(original_path2, IMREAD_COLOR); ASSERT_FALSE(source.empty()) << "Could not load source image " << original_path1; ASSERT_FALSE(mask.empty()) << "Could not load mask image " << original_path2; Mat result; illuminationChange(source, mask, result, 0.2f, 0.4f); SAVE(result); Mat reference = imread(reference_path); double error = cvtest::norm(reference, result, NORM_L1); EXPECT_LE(error, numerical_precision); } TEST(Photo_SeamlessClone_textureFlattening, regression) { string folder = string(cvtest::TS::ptr()->get_data_path()) + "cloning/Texture_Flattening/"; string original_path1 = folder + "source1.png"; string original_path2 = folder + "mask.png"; string reference_path = folder + "reference.png"; Mat source = imread(original_path1, IMREAD_COLOR); Mat mask = imread(original_path2, IMREAD_COLOR); ASSERT_FALSE(source.empty()) << "Could not load source image " << original_path1; ASSERT_FALSE(mask.empty()) << "Could not load mask image " << original_path2; Mat result; textureFlattening(source, mask, result, 30, 45, 3); SAVE(result); Mat reference = imread(reference_path); ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path; double error = cvtest::norm(reference, result, NORM_L1); EXPECT_LE(error, numerical_precision); }