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Open Source Computer Vision Library
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137 lines
4.8 KiB
137 lines
4.8 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) 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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using namespace std; |
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using namespace cv; |
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class CV_FastTest : public cvtest::BaseTest |
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{ |
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public: |
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CV_FastTest(); |
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~CV_FastTest(); |
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protected: |
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void run(int); |
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}; |
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CV_FastTest::CV_FastTest() {} |
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CV_FastTest::~CV_FastTest() {} |
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void CV_FastTest::run( int ) |
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{ |
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for(int type=0; type <= 2; ++type) { |
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Mat image1 = imread(string(ts->get_data_path()) + "inpaint/orig.png"); |
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Mat image2 = imread(string(ts->get_data_path()) + "cameracalibration/chess9.png"); |
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string xml = string(ts->get_data_path()) + format("fast/result%d.xml", type); |
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if (image1.empty() || image2.empty()) |
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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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Mat gray1, gray2; |
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cvtColor(image1, gray1, COLOR_BGR2GRAY); |
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cvtColor(image2, gray2, COLOR_BGR2GRAY); |
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vector<KeyPoint> keypoints1; |
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vector<KeyPoint> keypoints2; |
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FAST(gray1, keypoints1, 30, true, type); |
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FAST(gray2, keypoints2, (type > 0 ? 30 : 20), true, type); |
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for(size_t i = 0; i < keypoints1.size(); ++i) |
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{ |
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const KeyPoint& kp = keypoints1[i]; |
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cv::circle(image1, kp.pt, cvRound(kp.size/2), Scalar(255, 0, 0)); |
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} |
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for(size_t i = 0; i < keypoints2.size(); ++i) |
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{ |
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const KeyPoint& kp = keypoints2[i]; |
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cv::circle(image2, kp.pt, cvRound(kp.size/2), Scalar(255, 0, 0)); |
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} |
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Mat kps1(1, (int)(keypoints1.size() * sizeof(KeyPoint)), CV_8U, &keypoints1[0]); |
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Mat kps2(1, (int)(keypoints2.size() * sizeof(KeyPoint)), CV_8U, &keypoints2[0]); |
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FileStorage fs(xml, FileStorage::READ); |
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if (!fs.isOpened()) |
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{ |
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fs.open(xml, FileStorage::WRITE); |
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if (!fs.isOpened()) |
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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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fs << "exp_kps1" << kps1; |
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fs << "exp_kps2" << kps2; |
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fs.release(); |
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fs.open(xml, FileStorage::READ); |
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if (!fs.isOpened()) |
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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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} |
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Mat exp_kps1, exp_kps2; |
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read( fs["exp_kps1"], exp_kps1, Mat() ); |
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read( fs["exp_kps2"], exp_kps2, Mat() ); |
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fs.release(); |
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if ( exp_kps1.size != kps1.size || 0 != cvtest::norm(exp_kps1, kps1, NORM_L2) || |
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exp_kps2.size != kps2.size || 0 != cvtest::norm(exp_kps2, kps2, NORM_L2)) |
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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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/*cv::namedWindow("Img1"); cv::imshow("Img1", image1); |
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cv::namedWindow("Img2"); cv::imshow("Img2", image2); |
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cv::waitKey(0);*/ |
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} |
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ts->set_failed_test_info(cvtest::TS::OK); |
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} |
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TEST(Features2d_FAST, regression) { CV_FastTest test; test.safe_run(); }
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