From a64d096369c93d5f09a0db999730b72b97e14020 Mon Sep 17 00:00:00 2001 From: LaurentBerger Date: Tue, 4 Aug 2015 22:58:22 +0200 Subject: [PATCH] remove test --- modules/imgproc/test/test_adpativethresh.cpp | 113 ------------------- 1 file changed, 113 deletions(-) delete mode 100644 modules/imgproc/test/test_adpativethresh.cpp diff --git a/modules/imgproc/test/test_adpativethresh.cpp b/modules/imgproc/test/test_adpativethresh.cpp deleted file mode 100644 index 19e342b3a..000000000 --- a/modules/imgproc/test/test_adpativethresh.cpp +++ /dev/null @@ -1,113 +0,0 @@ -/*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) 2000-2008, Intel Corporation, all rights reserved. -// Copyright (C) 2009, Willow Garage Inc., 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*/ - -#include "test_precomp.hpp" -#include - -using namespace cv; -using namespace std; - -class CV_Adaptivethresh : public cvtest::BaseTest -{ -public: - CV_Adaptivethresh(); - ~CV_Adaptivethresh(); -protected: - void run(int); -}; - -CV_Adaptivethresh::CV_Adaptivethresh() {} -CV_Adaptivethresh::~CV_Adaptivethresh() {} - -void CV_Adaptivethresh::run( int /* start_from */) -{ - string exp_path = string(ts->get_data_path()) + "adaptivethresh/lena_orig.png"; - Mat lena = imread(exp_path, 0); // CV_LOAD_IMAGE_GRAYSCALE=0 - if (lena.empty() ) - { - ts->set_failed_test_info( cvtest::TS::FAIL_MISSING_TEST_DATA ); - return; - } - int sum=0; - for (int i = 0; i < lena.rows; i++) - { - unsigned char *ptr = lena.ptr(i); - for (int j=0;jset_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA ); - return; - } - int windowSize[9] = {3,9,11,17,21,25,29,37,47}; - int expectedValueMean[9] = {96138,121836,124499,129096,130538,131330,131743,131616,131223}; - int expectedValueGaussNew[9] = {86308,112910,116197,122117,124672,126488,127855,129377,130387}; - int expectedValueGaussOld[9] = {88583,81365,154081,98049,149357,106414,179701,168433,90250}; - Mat im; - bool failed=false; - for(int i = 0; i<9; ++i ) - { - adaptiveThreshold( lena, im, 255,cv::ADAPTIVE_THRESH_MEAN_C,THRESH_BINARY,windowSize[i],0); - int numberWhite=countNonZero(im); - if (numberWhite != expectedValueMean[i]) - { - ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH ); - return; - } - adaptiveThreshold( lena, im, 255,cv::ADAPTIVE_THRESH_GAUSSIAN_C,THRESH_BINARY,windowSize[i],0); - if (numberWhite != expectedValueGaussNew[i]) - { - - if (numberWhite != expectedValueGaussOld[i]) - ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY ); - else - ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH ); - } - } - if (failed) - ts->set_failed_test_info(cvtest::TS::OK); - else - ts->set_failed_test_info(cvtest::TS::OK); -} - -TEST(Imgproc_Adaptivethresh, regression) { CV_Adaptivethresh test; test.safe_run(); }