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

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This commit is contained in:
Andrey Kamaev 2013-03-26 17:20:51 +04:00
parent 49f6dad13f
commit 2edfae5070
3 changed files with 89 additions and 86 deletions
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89
modules/core/doc/basic_structures.rst
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@ -368,6 +368,95 @@ The static method ``Range::all()`` returns a special variable that means "the wh
}
KeyPoint
--------
.. ocv:class:: KeyPoint
Data structure for salient point detectors.
.. ocv:member:: Point2f pt
coordinates of the keypoint
.. ocv:member:: float size
diameter of the meaningful keypoint neighborhood
.. ocv:member:: float angle
computed orientation of the keypoint (-1 if not applicable). Its possible values are in a range [0,360) degrees. It is measured relative to image coordinate system (y-axis is directed downward), ie in clockwise.
.. ocv:member:: float response
the response by which the most strong keypoints have been selected. Can be used for further sorting or subsampling
.. ocv:member:: int octave
octave (pyramid layer) from which the keypoint has been extracted
.. ocv:member:: int class_id
object id that can be used to clustered keypoints by an object they belong to
KeyPoint::KeyPoint
------------------
The keypoint constructors
.. ocv:function:: KeyPoint::KeyPoint()
.. ocv:function:: KeyPoint::KeyPoint(Point2f _pt, float _size, float _angle=-1, float _response=0, int _octave=0, int _class_id=-1)
.. ocv:function:: KeyPoint::KeyPoint(float x, float y, float _size, float _angle=-1, float _response=0, int _octave=0, int _class_id=-1)
.. ocv:pyfunction:: cv2.KeyPoint([x, y, _size[, _angle[, _response[, _octave[, _class_id]]]]]) -> <KeyPoint object>
:param x: x-coordinate of the keypoint
:param y: y-coordinate of the keypoint
:param _pt: x & y coordinates of the keypoint
:param _size: keypoint diameter
:param _angle: keypoint orientation
:param _response: keypoint detector response on the keypoint (that is, strength of the keypoint)
:param _octave: pyramid octave in which the keypoint has been detected
:param _class_id: object id
DMatch
------
.. ocv:struct:: DMatch
Class for matching keypoint descriptors: query descriptor index,
train descriptor index, train image index, and distance between descriptors. ::
struct DMatch
{
DMatch() : queryIdx(-1), trainIdx(-1), imgIdx(-1),
distance(std::numeric_limits<float>::max()) {}
DMatch( int _queryIdx, int _trainIdx, float _distance ) :
queryIdx(_queryIdx), trainIdx(_trainIdx), imgIdx(-1),
distance(_distance) {}
DMatch( int _queryIdx, int _trainIdx, int _imgIdx, float _distance ) :
queryIdx(_queryIdx), trainIdx(_trainIdx), imgIdx(_imgIdx),
distance(_distance) {}
int queryIdx; // query descriptor index
int trainIdx; // train descriptor index
int imgIdx; // train image index
float distance;
// less is better
bool operator<( const DMatch &m ) const;
};
.. _Ptr:
Ptr

28
modules/features2d/doc/common_interfaces_of_descriptor_matchers.rst
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@ -9,34 +9,6 @@ that are represented as vectors in a multidimensional space. All objects that im
descriptor matchers inherit the
:ocv:class:`DescriptorMatcher` interface.
DMatch
------
.. ocv:struct:: DMatch
Class for matching keypoint descriptors: query descriptor index,
train descriptor index, train image index, and distance between descriptors. ::
struct DMatch
{
DMatch() : queryIdx(-1), trainIdx(-1), imgIdx(-1),
distance(std::numeric_limits<float>::max()) {}
DMatch( int _queryIdx, int _trainIdx, float _distance ) :
queryIdx(_queryIdx), trainIdx(_trainIdx), imgIdx(-1),
distance(_distance) {}
DMatch( int _queryIdx, int _trainIdx, int _imgIdx, float _distance ) :
queryIdx(_queryIdx), trainIdx(_trainIdx), imgIdx(_imgIdx),
distance(_distance) {}
int queryIdx; // query descriptor index
int trainIdx; // train descriptor index
int imgIdx; // train image index
float distance;
// less is better
bool operator<( const DMatch &m ) const;
};
DescriptorMatcher
-----------------

58
modules/features2d/doc/common_interfaces_of_feature_detectors.rst
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@ -8,64 +8,6 @@ between different algorithms solving the same problem. All objects that implemen
inherit the
:ocv:class:`FeatureDetector` interface.
KeyPoint
--------
.. ocv:class:: KeyPoint
Data structure for salient point detectors.
.. ocv:member:: Point2f pt
coordinates of the keypoint
.. ocv:member:: float size
diameter of the meaningful keypoint neighborhood
.. ocv:member:: float angle
computed orientation of the keypoint (-1 if not applicable). Its possible values are in a range [0,360) degrees. It is measured relative to image coordinate system (y-axis is directed downward), ie in clockwise.
.. ocv:member:: float response
the response by which the most strong keypoints have been selected. Can be used for further sorting or subsampling
.. ocv:member:: int octave
octave (pyramid layer) from which the keypoint has been extracted
.. ocv:member:: int class_id
object id that can be used to clustered keypoints by an object they belong to
KeyPoint::KeyPoint
------------------
The keypoint constructors
.. ocv:function:: KeyPoint::KeyPoint()
.. ocv:function:: KeyPoint::KeyPoint(Point2f _pt, float _size, float _angle=-1, float _response=0, int _octave=0, int _class_id=-1)
.. ocv:function:: KeyPoint::KeyPoint(float x, float y, float _size, float _angle=-1, float _response=0, int _octave=0, int _class_id=-1)
.. ocv:pyfunction:: cv2.KeyPoint([x, y, _size[, _angle[, _response[, _octave[, _class_id]]]]]) -> <KeyPoint object>
:param x: x-coordinate of the keypoint
:param y: y-coordinate of the keypoint
:param _pt: x & y coordinates of the keypoint
:param _size: keypoint diameter
:param _angle: keypoint orientation
:param _response: keypoint detector response on the keypoint (that is, strength of the keypoint)
:param _octave: pyramid octave in which the keypoint has been detected
:param _class_id: object id
FeatureDetector
---------------