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142 lines
5.2 KiB
142 lines
5.2 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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#include "opencv2/photo.hpp" |
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#include <string> |
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using namespace cv; |
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using namespace std; |
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static const double numerical_precision = 100.; |
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TEST(Photo_NPR_EdgePreserveSmoothing_RecursiveFilter, regression) |
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{ |
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string folder = string(cvtest::TS::ptr()->get_data_path()) + "npr/"; |
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string original_path = folder + "test1.png"; |
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Mat source = imread(original_path, IMREAD_COLOR); |
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ASSERT_FALSE(source.empty()) << "Could not load input image " << original_path; |
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Mat result; |
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edgePreservingFilter(source,result,1); |
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Mat reference = imread(folder + "smoothened_RF_reference.png"); |
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double psnr = cvtest::PSNR(reference, result); |
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EXPECT_GT(psnr, 60.0); |
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} |
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TEST(Photo_NPR_EdgePreserveSmoothing_NormConvFilter, regression) |
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{ |
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string folder = string(cvtest::TS::ptr()->get_data_path()) + "npr/"; |
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string original_path = folder + "test1.png"; |
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Mat source = imread(original_path, IMREAD_COLOR); |
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ASSERT_FALSE(source.empty()) << "Could not load input image " << original_path; |
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Mat result; |
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edgePreservingFilter(source,result,2); |
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Mat reference = imread(folder + "smoothened_NCF_reference.png"); |
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double psnr = cvtest::PSNR(reference, result); |
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EXPECT_GT(psnr, 60.0); |
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} |
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TEST(Photo_NPR_DetailEnhance, regression) |
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{ |
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string folder = string(cvtest::TS::ptr()->get_data_path()) + "npr/"; |
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string original_path = folder + "test1.png"; |
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Mat source = imread(original_path, IMREAD_COLOR); |
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ASSERT_FALSE(source.empty()) << "Could not load input image " << original_path; |
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Mat result; |
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detailEnhance(source,result); |
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Mat reference = imread(folder + "detail_enhanced_reference.png"); |
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double psnr = cvtest::PSNR(reference, result); |
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EXPECT_GT(psnr, 60.0); |
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} |
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TEST(Photo_NPR_PencilSketch, regression) |
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{ |
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string folder = string(cvtest::TS::ptr()->get_data_path()) + "npr/"; |
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string original_path = folder + "test1.png"; |
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Mat source = imread(original_path, IMREAD_COLOR); |
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ASSERT_FALSE(source.empty()) << "Could not load input image " << original_path; |
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Mat pencil_result, color_pencil_result; |
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pencilSketch(source,pencil_result, color_pencil_result, 10, 0.1f, 0.03f); |
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Mat pencil_reference = imread(folder + "pencil_sketch_reference.png", 0 /* == grayscale*/); |
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double pencil_error = norm(pencil_reference, pencil_result, NORM_L1); |
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EXPECT_LE(pencil_error, numerical_precision); |
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Mat color_pencil_reference = imread(folder + "color_pencil_sketch_reference.png"); |
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double color_pencil_error = cvtest::norm(color_pencil_reference, color_pencil_result, NORM_L1); |
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EXPECT_LE(color_pencil_error, numerical_precision); |
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} |
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TEST(Photo_NPR_Stylization, regression) |
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{ |
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string folder = string(cvtest::TS::ptr()->get_data_path()) + "npr/"; |
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string original_path = folder + "test1.png"; |
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Mat source = imread(original_path, IMREAD_COLOR); |
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ASSERT_FALSE(source.empty()) << "Could not load input image " << original_path; |
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Mat result; |
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stylization(source,result); |
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Mat stylized_reference = imread(folder + "stylized_reference.png"); |
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double stylized_error = cvtest::norm(stylized_reference, result, NORM_L1); |
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EXPECT_LE(stylized_error, numerical_precision); |
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}
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