Merge branch 'daisy' of https://github.com/cbalint13/opencv_contrib into daisy
cbalint13
10 years ago
commit
0c32bce3fa
15 changed files with 19 additions and 17360 deletions
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#include "perf_precomp.hpp" |
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using namespace std; |
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using namespace cv; |
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using namespace cv::xfeatures2d; |
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using namespace perf; |
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using std::tr1::make_tuple; |
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using std::tr1::get; |
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CV_ENUM(AgastType, AgastFeatureDetector::AGAST_5_8, AgastFeatureDetector::AGAST_7_12d, |
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AgastFeatureDetector::AGAST_7_12s, AgastFeatureDetector::OAST_9_16) |
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typedef std::tr1::tuple<string, AgastType> File_Type_t; |
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typedef perf::TestBaseWithParam<File_Type_t> agast; |
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#define AGAST_IMAGES \ |
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"cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png",\
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"stitching/a3.png" |
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PERF_TEST_P(agast, detect, testing::Combine( |
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testing::Values(AGAST_IMAGES), |
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AgastType::all() |
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)) |
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{ |
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string filename = getDataPath(get<0>(GetParam())); |
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int type = get<1>(GetParam()); |
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Mat frame = imread(filename, IMREAD_GRAYSCALE); |
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if (frame.empty()) |
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FAIL() << "Unable to load source image " << filename; |
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declare.in(frame); |
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Ptr<FeatureDetector> fd = AgastFeatureDetector::create(20, true, type); |
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ASSERT_FALSE( fd.empty() ); |
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vector<KeyPoint> points; |
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TEST_CYCLE() fd->detect(frame, points); |
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SANITY_CHECK_KEYPOINTS(points); |
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} |
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File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
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/* This is AGAST and OAST, an optimal and accelerated corner detector
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based on the accelerated segment tests |
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Below is the original copyright and the references */ |
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/*
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Copyright (C) 2010 Elmar Mair |
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All rights reserved. |
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Redistribution and use in source and binary forms, with or without |
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modification, are permitted provided that the following conditions |
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are met: |
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*Redistributions of source code must retain the above copyright |
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notice, this list of conditions and the following disclaimer. |
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*Redistributions in binary form must reproduce the above copyright |
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notice, this list of conditions and the following disclaimer in the |
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documentation and/or other materials provided with the distribution. |
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*Neither the name of the University of Cambridge nor the names of |
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its contributors may be used to endorse or promote products derived |
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from this software without specific prior written permission. |
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS |
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"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT |
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LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR |
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A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR |
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CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, |
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EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, |
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PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR |
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PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF |
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LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING |
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NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS |
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SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
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*/ |
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/*
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The references are: |
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* Adaptive and Generic Corner Detection Based on the Accelerated Segment Test, |
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Elmar Mair and Gregory D. Hager and Darius Burschka |
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and Michael Suppa and Gerhard Hirzinger ECCV 2010 |
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URL: http://www6.in.tum.de/Main/ResearchAgast
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*/ |
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#ifndef __OPENCV_FEATURES_2D_AGAST_HPP__ |
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#define __OPENCV_FEATURES_2D_AGAST_HPP__ |
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#ifdef __cplusplus |
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#include "precomp.hpp" |
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namespace cv |
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{ |
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namespace xfeatures2d |
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{ |
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void makeAgastOffsets(int pixel[16], int row_stride, int type); |
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template<int type> |
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int agast_cornerScore(const uchar* ptr, const int pixel[], int threshold); |
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} |
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} |
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#endif |
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#endif |
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@ -1,138 +0,0 @@ |
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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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using namespace std; |
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using namespace cv; |
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using namespace cv::xfeatures2d; |
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class CV_AgastTest : public cvtest::BaseTest |
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{ |
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public: |
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CV_AgastTest(); |
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~CV_AgastTest(); |
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protected: |
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void run(int); |
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}; |
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CV_AgastTest::CV_AgastTest() {} |
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CV_AgastTest::~CV_AgastTest() {} |
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void CV_AgastTest::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("agast/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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AGAST(gray1, keypoints1, 30, true, type); |
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AGAST(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_AGAST, regression) { CV_AgastTest test; test.safe_run(); } |
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