1 /*M/////////////////////////////////////////////////////////////////////////////////////// 2 // 3 // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. 4 // 5 // By downloading, copying, installing or using the software you agree to this license. 6 // If you do not agree to this license, do not download, install, 7 // copy or use the software. 8 // 9 // 10 // License Agreement 11 // For Open Source Computer Vision Library 12 // 13 // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. 14 // Copyright (C) 2009, Willow Garage Inc., all rights reserved. 15 // Third party copyrights are property of their respective owners. 16 // 17 // Redistribution and use in source and binary forms, with or without modification, 18 // are permitted provided that the following conditions are met: 19 // 20 // * Redistribution's of source code must retain the above copyright notice, 21 // this list of conditions and the following disclaimer. 22 // 23 // * Redistribution's in binary form must reproduce the above copyright notice, 24 // this list of conditions and the following disclaimer in the documentation 25 // and/or other materials provided with the distribution. 26 // 27 // * The name of the copyright holders may not be used to endorse or promote products 28 // derived from this software without specific prior written permission. 29 // 30 // This software is provided by the copyright holders and contributors "as is" and 31 // any express or implied warranties, including, but not limited to, the implied 32 // warranties of merchantability and fitness for a particular purpose are disclaimed. 33 // In no event shall the Intel Corporation or contributors be liable for any direct, 34 // indirect, incidental, special, exemplary, or consequential damages 35 // (including, but not limited to, procurement of substitute goods or services; 36 // loss of use, data, or profits; or business interruption) however caused 37 // and on any theory of liability, whether in contract, strict liability, 38 // or tort (including negligence or otherwise) arising in any way out of 39 // the use of this software, even if advised of the possibility of such damage. 40 // 41 //M*/ 42 43 #include "test_precomp.hpp" 44 45 using namespace std; 46 using namespace cv; 47 48 class CV_FastTest : public cvtest::BaseTest 49 { 50 public: 51 CV_FastTest(); 52 ~CV_FastTest(); 53 protected: 54 void run(int); 55 }; 56 57 CV_FastTest::CV_FastTest() {} 58 CV_FastTest::~CV_FastTest() {} 59 60 void CV_FastTest::run( int ) 61 { 62 for(int type=0; type <= 2; ++type) { 63 Mat image1 = imread(string(ts->get_data_path()) + "inpaint/orig.png"); 64 Mat image2 = imread(string(ts->get_data_path()) + "cameracalibration/chess9.png"); 65 string xml = string(ts->get_data_path()) + format("fast/result%d.xml", type); 66 67 if (image1.empty() || image2.empty()) 68 { 69 ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA ); 70 return; 71 } 72 73 Mat gray1, gray2; 74 cvtColor(image1, gray1, COLOR_BGR2GRAY); 75 cvtColor(image2, gray2, COLOR_BGR2GRAY); 76 77 vector<KeyPoint> keypoints1; 78 vector<KeyPoint> keypoints2; 79 FAST(gray1, keypoints1, 30, true, type); 80 FAST(gray2, keypoints2, (type > 0 ? 30 : 20), true, type); 81 82 for(size_t i = 0; i < keypoints1.size(); ++i) 83 { 84 const KeyPoint& kp = keypoints1[i]; 85 cv::circle(image1, kp.pt, cvRound(kp.size/2), Scalar(255, 0, 0)); 86 } 87 88 for(size_t i = 0; i < keypoints2.size(); ++i) 89 { 90 const KeyPoint& kp = keypoints2[i]; 91 cv::circle(image2, kp.pt, cvRound(kp.size/2), Scalar(255, 0, 0)); 92 } 93 94 Mat kps1(1, (int)(keypoints1.size() * sizeof(KeyPoint)), CV_8U, &keypoints1[0]); 95 Mat kps2(1, (int)(keypoints2.size() * sizeof(KeyPoint)), CV_8U, &keypoints2[0]); 96 97 FileStorage fs(xml, FileStorage::READ); 98 if (!fs.isOpened()) 99 { 100 fs.open(xml, FileStorage::WRITE); 101 if (!fs.isOpened()) 102 { 103 ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA); 104 return; 105 } 106 fs << "exp_kps1" << kps1; 107 fs << "exp_kps2" << kps2; 108 fs.release(); 109 fs.open(xml, FileStorage::READ); 110 if (!fs.isOpened()) 111 { 112 ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA); 113 return; 114 } 115 } 116 117 Mat exp_kps1, exp_kps2; 118 read( fs["exp_kps1"], exp_kps1, Mat() ); 119 read( fs["exp_kps2"], exp_kps2, Mat() ); 120 fs.release(); 121 122 if ( exp_kps1.size != kps1.size || 0 != cvtest::norm(exp_kps1, kps1, NORM_L2) || 123 exp_kps2.size != kps2.size || 0 != cvtest::norm(exp_kps2, kps2, NORM_L2)) 124 { 125 ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH); 126 return; 127 } 128 129 /*cv::namedWindow("Img1"); cv::imshow("Img1", image1); 130 cv::namedWindow("Img2"); cv::imshow("Img2", image2); 131 cv::waitKey(0);*/ 132 } 133 134 ts->set_failed_test_info(cvtest::TS::OK); 135 } 136 137 TEST(Features2d_FAST, regression) { CV_FastTest test; test.safe_run(); } 138