Move cv::KeyPoint and cv::DMatch to core

modules/core/include/opencv2/core.hpp

@@ -826,6 +826,96 @@ public:
     int start, end;
 };
 
+
+
+/////////////////////////////// KeyPoint ////////////////////////////////
+
+/*!
+ The Keypoint Class
+
+ The class instance stores a keypoint, i.e. a point feature found by one of many available keypoint detectors, such as
+ Harris corner detector, cv::FAST, cv::StarDetector, cv::SURF, cv::SIFT, cv::LDetector etc.
+
+ The keypoint is characterized by the 2D position, scale
+ (proportional to the diameter of the neighborhood that needs to be taken into account),
+ orientation and some other parameters. The keypoint neighborhood is then analyzed by another algorithm that builds a descriptor
+ (usually represented as a feature vector). The keypoints representing the same object in different images can then be matched using
+ cv::KDTree or another method.
+*/
+class CV_EXPORTS_W_SIMPLE KeyPoint
+{
+public:
+    //! the default constructor
+    CV_WRAP KeyPoint();
+    //! the full constructor
+    KeyPoint(Point2f _pt, float _size, float _angle=-1, float _response=0, int _octave=0, int _class_id=-1);
+    //! another form of the full constructor
+    CV_WRAP KeyPoint(float x, float y, float _size, float _angle=-1, float _response=0, int _octave=0, int _class_id=-1);
+
+    size_t hash() const;
+
+    //! converts vector of keypoints to vector of points
+    static void convert(const std::vector<KeyPoint>& keypoints,
+                        CV_OUT std::vector<Point2f>& points2f,
+                        const std::vector<int>& keypointIndexes=std::vector<int>());
+    //! converts vector of points to the vector of keypoints, where each keypoint is assigned the same size and the same orientation
+    static void convert(const std::vector<Point2f>& points2f,
+                        CV_OUT std::vector<KeyPoint>& keypoints,
+                        float size=1, float response=1, int octave=0, int class_id=-1);
+
+    //! computes overlap for pair of keypoints;
+    //! overlap is a ratio between area of keypoint regions intersection and
+    //! area of keypoint regions union (now keypoint region is circle)
+    static float overlap(const KeyPoint& kp1, const KeyPoint& kp2);
+
+    CV_PROP_RW Point2f pt; //!< coordinates of the keypoints
+    CV_PROP_RW float size; //!< diameter of the meaningful keypoint neighborhood
+    CV_PROP_RW float angle; //!< computed orientation of the keypoint (-1 if not applicable);
+                            //!< it's in [0,360) degrees and measured relative to
+                            //!< image coordinate system, ie in clockwise.
+    CV_PROP_RW float response; //!< the response by which the most strong keypoints have been selected. Can be used for the further sorting or subsampling
+    CV_PROP_RW int octave; //!< octave (pyramid layer) from which the keypoint has been extracted
+    CV_PROP_RW int class_id; //!< object class (if the keypoints need to be clustered by an object they belong to)
+};
+
+inline KeyPoint::KeyPoint() : pt(0,0), size(0), angle(-1), response(0), octave(0), class_id(-1) {}
+inline KeyPoint::KeyPoint(Point2f _pt, float _size, float _angle, float _response, int _octave, int _class_id)
+                : pt(_pt), size(_size), angle(_angle), response(_response), octave(_octave), class_id(_class_id) {}
+inline KeyPoint::KeyPoint(float x, float y, float _size, float _angle, float _response, int _octave, int _class_id)
+                : pt(x, y), size(_size), angle(_angle), response(_response), octave(_octave), class_id(_class_id) {}
+
+
+
+//////////////////////////////// DMatch /////////////////////////////////
+
+/*
+ * Struct for matching: query descriptor index, train descriptor index, train image index and distance between descriptors.
+ */
+struct CV_EXPORTS_W_SIMPLE DMatch
+{
+    CV_WRAP DMatch();
+    CV_WRAP DMatch(int _queryIdx, int _trainIdx, float _distance);
+    CV_WRAP DMatch(int _queryIdx, int _trainIdx, int _imgIdx, float _distance);
+
+    CV_PROP_RW int queryIdx; // query descriptor index
+    CV_PROP_RW int trainIdx; // train descriptor index
+    CV_PROP_RW int imgIdx;   // train image index
+
+    CV_PROP_RW float distance;
+
+    // less is better
+    bool operator<(const DMatch &m) const;
+};
+
+inline DMatch::DMatch() : queryIdx(-1), trainIdx(-1), imgIdx(-1), distance(FLT_MAX) {}
+inline DMatch::DMatch(int _queryIdx, int _trainIdx, float _distance)
+              : queryIdx(_queryIdx), trainIdx(_trainIdx), imgIdx(-1), distance(_distance) {}
+inline DMatch::DMatch(int _queryIdx, int _trainIdx, int _imgIdx, float _distance)
+              : queryIdx(_queryIdx), trainIdx(_trainIdx), imgIdx(_imgIdx), distance(_distance) {}
+inline bool DMatch::operator<(const DMatch &m) const { return distance < m.distance; }
+
+
+
 /////////////////////////////// DataType ////////////////////////////////
 
 /*!