init - 初始化项目

2022-05-06 01:58:53 +08:00
commit 90a5cc7cb6
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--- a/modules/features2d/test/test_orb.cpp
+++ b/modules/features2d/test/test_orb.cpp
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+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
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+//  copy or use the software.
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+//
+//                        Intel License Agreement
+//                For Open Source Computer Vision Library
+//
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+//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));
+}
+
+
+}} // namespace