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- /*M///////////////////////////////////////////////////////////////////////////////////////
- //
- // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
- //
- // By downloading, copying, installing or using the software you agree to this license.
- // If you do not agree to this license, do not download, install,
- // copy or use the software.
- //
- //
- // Intel License Agreement
- // For Open Source Computer Vision Library
- //
- // Copyright (C) 2000, Intel Corporation, all rights reserved.
- // Third party copyrights are property of their respective owners.
- //
- // Redistribution and use in source and binary forms, with or without modification,
- // are permitted provided that the following conditions are met:
- //
- // * Redistribution's of source code must retain the above copyright notice,
- // this list of conditions and the following disclaimer.
- //
- // * Redistribution's in binary form must reproduce the above copyright notice,
- // this list of conditions and the following disclaimer in the documentation
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- //
- // * The name of Intel Corporation may not be used to endorse or promote products
- // derived from this software without specific prior written permission.
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- // indirect, incidental, special, exemplary, or consequential damages
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- // loss of use, data, or profits; or business interruption) however caused
- // and on any theory of liability, whether in contract, strict liability,
- // or tort (including negligence or otherwise) arising in any way out of
- // the use of this software, even if advised of the possibility of such damage.
- //
- //M*/
- #include "test_precomp.hpp"
- namespace opencv_test { namespace {
- TEST(Features2D_ORB, _1996)
- {
- Ptr<FeatureDetector> fd = ORB::create(10000, 1.2f, 8, 31, 0, 2, ORB::HARRIS_SCORE, 31, 20);
- Ptr<DescriptorExtractor> de = fd;
- Mat image = imread(string(cvtest::TS::ptr()->get_data_path()) + "shared/lena.png");
- ASSERT_FALSE(image.empty());
- Mat roi(image.size(), CV_8UC1, Scalar(0));
- Point poly[] = {Point(100, 20), Point(300, 50), Point(400, 200), Point(10, 500)};
- fillConvexPoly(roi, poly, int(sizeof(poly) / sizeof(poly[0])), Scalar(255));
- std::vector<KeyPoint> keypoints;
- fd->detect(image, keypoints, roi);
- Mat descriptors;
- de->compute(image, keypoints, descriptors);
- //image.setTo(Scalar(255,255,255), roi);
- int roiViolations = 0;
- for(std::vector<KeyPoint>::const_iterator kp = keypoints.begin(); kp != keypoints.end(); ++kp)
- {
- int x = cvRound(kp->pt.x);
- int y = cvRound(kp->pt.y);
- ASSERT_LE(0, x);
- ASSERT_LE(0, y);
- ASSERT_GT(image.cols, x);
- ASSERT_GT(image.rows, y);
- // if (!roi.at<uchar>(y,x))
- // {
- // roiViolations++;
- // circle(image, kp->pt, 3, Scalar(0,0,255));
- // }
- }
- // if(roiViolations)
- // {
- // imshow("img", image);
- // waitKey();
- // }
- ASSERT_EQ(0, roiViolations);
- }
- TEST(Features2D_ORB, crash_5031)
- {
- cv::Mat image = cv::Mat::zeros(cv::Size(1920, 1080), CV_8UC3);
- int nfeatures = 8000;
- float orbScaleFactor = 1.2f;
- int nlevels = 18;
- int edgeThreshold = 4;
- int firstLevel = 0;
- int WTA_K = 2;
- ORB::ScoreType scoreType = cv::ORB::HARRIS_SCORE;
- int patchSize = 47;
- int fastThreshold = 20;
- Ptr<ORB> orb = cv::ORB::create(nfeatures, orbScaleFactor, nlevels, edgeThreshold, firstLevel, WTA_K, scoreType, patchSize, fastThreshold);
- std::vector<cv::KeyPoint> keypoints;
- cv::Mat descriptors;
- cv::KeyPoint kp;
- kp.pt.x = 443;
- kp.pt.y = 5;
- kp.size = 47;
- kp.angle = 53.4580612f;
- kp.response = 0.0000470733867f;
- kp.octave = 0;
- kp.class_id = -1;
- keypoints.push_back(kp);
- ASSERT_NO_THROW(orb->compute(image, keypoints, descriptors));
- }
- TEST(Features2D_ORB, regression_16197)
- {
- Mat img(Size(72, 72), CV_8UC1, Scalar::all(0));
- Ptr<ORB> orbPtr = ORB::create();
- orbPtr->setNLevels(5);
- orbPtr->setFirstLevel(3);
- orbPtr->setScaleFactor(1.8);
- orbPtr->setPatchSize(8);
- orbPtr->setEdgeThreshold(8);
- std::vector<KeyPoint> kps;
- Mat fv;
- // exception in debug mode, crash in release
- ASSERT_NO_THROW(orbPtr->detectAndCompute(img, noArray(), kps, fv));
- }
- // https://github.com/opencv/opencv-python/issues/537
- BIGDATA_TEST(Features2D_ORB, regression_opencv_python_537) // memory usage: ~3 Gb
- {
- applyTestTag(
- CV_TEST_TAG_LONG,
- CV_TEST_TAG_DEBUG_VERYLONG,
- CV_TEST_TAG_MEMORY_6GB
- );
- const int width = 25000;
- const int height = 25000;
- Mat img(Size(width, height), CV_8UC1, Scalar::all(0));
- const int border = 23, num_lines = 23;
- for (int i = 0; i < num_lines; i++)
- {
- cv::Point2i point1(border + i * 100, border + i * 100);
- cv::Point2i point2(width - border - i * 100, height - border * i * 100);
- cv::line(img, point1, point2, 255, 1, LINE_AA);
- }
- Ptr<ORB> orbPtr = ORB::create(31);
- std::vector<KeyPoint> kps;
- Mat fv;
- ASSERT_NO_THROW(orbPtr->detectAndCompute(img, noArray(), kps, fv));
- }
- }} // namespace
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