Python bindings for KeyPoint methods
Usage: import numpy as np import cv2 img = cv2.imread('messi5.jpg',0) sift = cv2.SIFT() kp = sift.detect(img) pts = cv2.KeyPoint_convert(kp) kps = cv2.KeyPoint_convert(pts.reshape(-1,1,2)) overlap = cv2.KeyPoint_overlap(kp[0],kp[1])
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@@ -551,18 +551,18 @@ public:
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size_t hash() const;
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//! converts vector of keypoints to vector of points
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static void convert(const std::vector<KeyPoint>& keypoints,
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CV_WRAP static void convert(const std::vector<KeyPoint>& keypoints,
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CV_OUT std::vector<Point2f>& points2f,
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const std::vector<int>& keypointIndexes=std::vector<int>());
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//! converts vector of points to the vector of keypoints, where each keypoint is assigned the same size and the same orientation
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static void convert(const std::vector<Point2f>& points2f,
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CV_WRAP static void convert(const std::vector<Point2f>& points2f,
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CV_OUT std::vector<KeyPoint>& keypoints,
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float size=1, float response=1, int octave=0, int class_id=-1);
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//! computes overlap for pair of keypoints;
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//! overlap is a ratio between area of keypoint regions intersection and
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//! area of keypoint regions union (now keypoint region is circle)
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static float overlap(const KeyPoint& kp1, const KeyPoint& kp2);
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CV_WRAP static float overlap(const KeyPoint& kp1, const KeyPoint& kp2);
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CV_PROP_RW Point2f pt; //!< coordinates of the keypoints
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CV_PROP_RW float size; //!< diameter of the meaningful keypoint neighborhood
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