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https://github.com/opencv/opencv.git
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ef5579dc86
* Cleanup macros and enable expansion of `__VA_ARGS__` for Visual Studio * Macros for enum-arguments backwards compatibility * Convert struct Param to enum struct * Enabled ParamType.type for enum types * Enabled `cv.read` and `cv.write` for enum types * Rename unnamed enum to AAKAZE.DescriptorType * Rename unnamed enum to AccessFlag * Rename unnamed enum to AgastFeatureDetector.DetectorType * Convert struct DrawMatchesFlags to enum struct * Rename unnamed enum to FastFeatureDetector.DetectorType * Rename unnamed enum to Formatter.FormatType * Rename unnamed enum to HOGDescriptor.HistogramNormType * Rename unnamed enum to DescriptorMatcher.MatcherType * Rename unnamed enum to KAZE.DiffusivityType * Rename unnamed enum to ORB.ScoreType * Rename unnamed enum to UMatData.MemoryFlag * Rename unnamed enum to _InputArray.KindFlag * Rename unnamed enum to _OutputArray.DepthMask * Convert normType enums to static const NormTypes * Avoid conflicts with ElemType * Rename unnamed enum to DescriptorStorageFormat
127 lines
4.2 KiB
C++
127 lines
4.2 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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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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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TEST(Features2D_ORB, _1996)
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{
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Ptr<FeatureDetector> fd = ORB::create(10000, 1.2f, 8, 31, 0, 2, ORB::HARRIS_SCORE, 31, 20);
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Ptr<DescriptorExtractor> de = fd;
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Mat image = imread(string(cvtest::TS::ptr()->get_data_path()) + "shared/lena.png");
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ASSERT_FALSE(image.empty());
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Mat roi(image.size(), CV_8UC1, Scalar(0));
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Point poly[] = {Point(100, 20), Point(300, 50), Point(400, 200), Point(10, 500)};
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fillConvexPoly(roi, poly, int(sizeof(poly) / sizeof(poly[0])), Scalar(255));
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std::vector<KeyPoint> keypoints;
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fd->detect(image, keypoints, roi);
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Mat descriptors;
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de->compute(image, keypoints, descriptors);
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//image.setTo(Scalar(255,255,255), roi);
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int roiViolations = 0;
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for(std::vector<KeyPoint>::const_iterator kp = keypoints.begin(); kp != keypoints.end(); ++kp)
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{
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int x = cvRound(kp->pt.x);
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int y = cvRound(kp->pt.y);
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ASSERT_LE(0, x);
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ASSERT_LE(0, y);
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ASSERT_GT(image.cols, x);
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ASSERT_GT(image.rows, y);
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// if (!roi.at<uchar>(y,x))
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// {
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// roiViolations++;
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// circle(image, kp->pt, 3, Scalar(0,0,255));
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// }
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}
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// if(roiViolations)
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// {
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// imshow("img", image);
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// waitKey();
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// }
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ASSERT_EQ(0, roiViolations);
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}
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TEST(Features2D_ORB, crash)
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{
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cv::Mat image = cv::Mat::zeros(cv::Size(1920, 1080), CV_8UC3);
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int nfeatures = 8000;
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float orbScaleFactor = 1.2f;
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int nlevels = 18;
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int edgeThreshold = 4;
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int firstLevel = 0;
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int WTA_K = 2;
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ORB::ScoreType scoreType = cv::ORB::HARRIS_SCORE;
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int patchSize = 47;
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int fastThreshold = 20;
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Ptr<ORB> orb = cv::ORB::create(nfeatures, orbScaleFactor, nlevels, edgeThreshold, firstLevel, WTA_K, scoreType, patchSize, fastThreshold);
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std::vector<cv::KeyPoint> keypoints;
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cv::Mat descriptors;
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cv::KeyPoint kp;
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kp.pt.x = 443;
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kp.pt.y = 5;
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kp.size = 47;
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kp.angle = 53.4580612f;
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kp.response = 0.0000470733867f;
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kp.octave = 0;
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kp.class_id = -1;
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keypoints.push_back(kp);
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ASSERT_NO_THROW(orb->compute(image, keypoints, descriptors));
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}
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}} // namespace
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