139 lines
4.9 KiB
C++
139 lines
4.9 KiB
C++
/*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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namespace opencv_test { namespace {
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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, static_cast<FastFeatureDetector::DetectorType>(type));
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FAST(gray2, keypoints2, (type > 0 ? 30 : 20), true, static_cast<FastFeatureDetector::DetectorType>(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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}} // namespace
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