142 lines
5.3 KiB
C++
Executable File
142 lines
5.3 KiB
C++
Executable File
/*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 error = cvtest::norm(reference, result, NORM_L1);
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EXPECT_LE(error, numerical_precision);
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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 error = cvtest::norm(reference, result, NORM_L1);
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EXPECT_LE(error, numerical_precision);
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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 error = cvtest::norm(reference, result, NORM_L1);
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EXPECT_LE(error, numerical_precision);
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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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