LaurentBerger
10 years ago
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/*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) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., 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 <string> |
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using namespace cv; |
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using namespace std; |
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class CV_Adaptivethresh : public cvtest::BaseTest |
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{ |
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public: |
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CV_Adaptivethresh(); |
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~CV_Adaptivethresh(); |
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protected: |
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void run(int); |
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}; |
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CV_Adaptivethresh::CV_Adaptivethresh() {} |
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CV_Adaptivethresh::~CV_Adaptivethresh() {} |
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void CV_Adaptivethresh::run( int /* start_from */) |
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{ |
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string exp_path = string(ts->get_data_path()) + "adaptivethresh/lena_orig.png"; |
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Mat lena = imread(exp_path, 0); // CV_LOAD_IMAGE_GRAYSCALE=0
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if (lena.empty() ) |
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{ |
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ts->set_failed_test_info( cvtest::TS::FAIL_MISSING_TEST_DATA ); |
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return; |
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} |
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int sum=0; |
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for (int i = 0; i < lena.rows; i++) |
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{ |
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unsigned char *ptr = lena.ptr(i); |
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for (int j=0;j<lena.cols;j++,ptr++) |
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sum+=*ptr; |
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} |
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if (sum!=31910861) |
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{ |
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ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA ); |
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return; |
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} |
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int windowSize[9] = {3,9,11,17,21,25,29,37,47}; |
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int expectedValueMean[9] = {96138,121836,124499,129096,130538,131330,131743,131616,131223}; |
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int expectedValueGaussNew[9] = {86308,112910,116197,122117,124672,126488,127855,129377,130387}; |
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int expectedValueGaussOld[9] = {88583,81365,154081,98049,149357,106414,179701,168433,90250}; |
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Mat im; |
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bool failed=false; |
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for(int i = 0; i<9; ++i ) |
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{ |
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adaptiveThreshold( lena, im, 255,cv::ADAPTIVE_THRESH_MEAN_C,THRESH_BINARY,windowSize[i],0); |
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int numberWhite=countNonZero(im); |
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if (numberWhite != expectedValueMean[i]) |
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{ |
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ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH ); |
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return; |
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} |
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adaptiveThreshold( lena, im, 255,cv::ADAPTIVE_THRESH_GAUSSIAN_C,THRESH_BINARY,windowSize[i],0); |
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if (numberWhite != expectedValueGaussNew[i]) |
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{
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if (numberWhite != expectedValueGaussOld[i]) |
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY ); |
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else |
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ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH ); |
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} |
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} |
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if (failed) |
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ts->set_failed_test_info(cvtest::TS::OK); |
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else |
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ts->set_failed_test_info(cvtest::TS::OK); |
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} |
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TEST(Imgproc_Adaptivethresh, regression) { CV_Adaptivethresh test; test.safe_run(); } |
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