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introduced new RST/Sphinx domain ocv.

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This commit is contained in:
Vadim Pisarevsky
2011-06-16 12:48:23 +00:00
parent 4f3fb040a4
commit 8d8ef596c8
48 changed files with 2823 additions and 1691 deletions
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24
modules/features2d/doc/common_interfaces_of_descriptor_extractors.rst
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@@ -13,7 +13,7 @@ descriptor extractors inherit the
DescriptorExtractor
-------------------
.. cpp:class:: DescriptorExtractor
.. ocv:class:: DescriptorExtractor
Abstract base class for computing descriptors for image keypoints ::
@@ -51,7 +51,7 @@ descriptors is represented as
DescriptorExtractor::compute
--------------------------------
.. cpp:function:: void DescriptorExtractor::compute( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const
.. ocv:function:: void DescriptorExtractor::compute( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const
Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).
@@ -61,7 +61,7 @@ DescriptorExtractor::compute
:param descriptors: Descriptors. Row i is the descriptor for keypoint i.
.. cpp:function:: void DescriptorExtractor::compute( const vector<Mat>& images, vector<vector<KeyPoint> >& keypoints, vector<Mat>& descriptors ) const
.. ocv:function:: void DescriptorExtractor::compute( const vector<Mat>& images, vector<vector<KeyPoint> >& keypoints, vector<Mat>& descriptors ) const
:param images: Image set.
@@ -75,7 +75,7 @@ DescriptorExtractor::compute
DescriptorExtractor::read
-----------------------------
.. cpp:function:: void DescriptorExtractor::read( const FileNode& fn )
.. ocv:function:: void DescriptorExtractor::read( const FileNode& fn )
Reads the object of a descriptor extractor from a file node.
@@ -85,7 +85,7 @@ DescriptorExtractor::read
DescriptorExtractor::write
------------------------------
.. cpp:function:: void DescriptorExtractor::write( FileStorage& fs ) const
.. ocv:function:: void DescriptorExtractor::write( FileStorage& fs ) const
Writes the object of a descriptor extractor to a file storage.
@@ -95,7 +95,7 @@ DescriptorExtractor::write
DescriptorExtractor::create
-------------------------------
.. cpp:function:: Ptr<DescriptorExtractor> DescriptorExtractor::create( const string& descriptorExtractorType )
.. ocv:function:: Ptr<DescriptorExtractor> DescriptorExtractor::create( const string& descriptorExtractorType )
Creates a descriptor extractor by name.
@@ -118,7 +118,7 @@ for example: ``"OpponentSIFT"`` .
SiftDescriptorExtractor
-----------------------
.. cpp:class:: SiftDescriptorExtractor
.. ocv:class:: SiftDescriptorExtractor
Wrapping class for computing descriptors by using the
:ref:`SIFT` class ::
@@ -150,7 +150,7 @@ Wrapping class for computing descriptors by using the
SurfDescriptorExtractor
-----------------------
.. cpp:class:: SurfDescriptorExtractor
.. ocv:class:: SurfDescriptorExtractor
Wrapping class for computing descriptors by using the
:ref:`SURF` class ::
@@ -176,7 +176,7 @@ Wrapping class for computing descriptors by using the
OrbDescriptorExtractor
---------------------------
.. cpp:class:: OrbDescriptorExtractor
.. ocv:class:: OrbDescriptorExtractor
Wrapping class for computing descriptors by using the
:ref:`ORB` class ::
@@ -200,7 +200,7 @@ Wrapping class for computing descriptors by using the
CalonderDescriptorExtractor
---------------------------
.. cpp:class:: CalonderDescriptorExtractor
.. ocv:class:: CalonderDescriptorExtractor
Wrapping class for computing descriptors by using the
:ref:`RTreeClassifier` class ::
@@ -226,7 +226,7 @@ Wrapping class for computing descriptors by using the
OpponentColorDescriptorExtractor
--------------------------------
.. cpp:class:: OpponentColorDescriptorExtractor
.. ocv:class:: OpponentColorDescriptorExtractor
Class adapting a descriptor extractor to compute descriptors in the Opponent Color Space
(refer to Van de Sande et al., CGIV 2008 *Color Descriptors for Object Category Recognition*).
@@ -254,7 +254,7 @@ them into a single color descriptor. ::
BriefDescriptorExtractor
------------------------
.. cpp:class:: BriefDescriptorExtractor
.. ocv:class:: BriefDescriptorExtractor
Class for computing BRIEF descriptors described in a paper of Calonder M., Lepetit V.,
Strecha C., Fua P. *BRIEF: Binary Robust Independent Elementary Features* ,

34
modules/features2d/doc/common_interfaces_of_descriptor_matchers.rst
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@@ -15,7 +15,7 @@ descriptor matchers inherit
DMatch
------
.. cpp:class:: DMatch
.. ocv:class:: DMatch
Class for matching keypoint descriptors: query descriptor index,
train descriptor index, train image index, and distance between descriptors ::
@@ -108,7 +108,7 @@ with an image set. ::
DescriptorMatcher::add
--------------------------
.. cpp:function:: void add( const vector<Mat>& descriptors )
.. ocv:function:: void add( const vector<Mat>& descriptors )
Adds descriptors to train a descriptor collection. If the collection ``trainDescCollectionis`` is not empty, the new descriptors are added to existing train descriptors.
@@ -118,7 +118,7 @@ DescriptorMatcher::add
DescriptorMatcher::getTrainDescriptors
------------------------------------------
.. cpp:function:: const vector<Mat>& getTrainDescriptors() const
.. ocv:function:: const vector<Mat>& getTrainDescriptors() const
Returns a constant link to the train descriptor collection ``trainDescCollection`` .
@@ -126,7 +126,7 @@ DescriptorMatcher::getTrainDescriptors
DescriptorMatcher::clear
----------------------------
.. cpp:function:: void DescriptorMatcher::clear()
.. ocv:function:: void DescriptorMatcher::clear()
Clears the train descriptor collection.
@@ -134,7 +134,7 @@ DescriptorMatcher::clear
DescriptorMatcher::empty
----------------------------
.. cpp:function:: bool DescriptorMatcher::empty() const
.. ocv:function:: bool DescriptorMatcher::empty() const
Returns true if there are no train descriptors in the collection.
@@ -142,7 +142,7 @@ DescriptorMatcher::empty
DescriptorMatcher::isMaskSupported
--------------------------------------
.. cpp:function:: bool DescriptorMatcher::isMaskSupported()
.. ocv:function:: bool DescriptorMatcher::isMaskSupported()
Returns true if the descriptor matcher supports masking permissible matches.
@@ -150,7 +150,7 @@ DescriptorMatcher::isMaskSupported
DescriptorMatcher::train
----------------------------
.. cpp:function:: void DescriptorMatcher::train()
.. ocv:function:: void DescriptorMatcher::train()
Trains a descriptor matcher (for example, the flann index). In all methods to match, the method ``train()`` is run every time before matching. Some descriptor matchers (for example, ``BruteForceMatcher``) have an empty implementation of this method. Other matchers really train their inner structures (for example, ``FlannBasedMatcher`` trains ``flann::Index`` ).
@@ -158,9 +158,9 @@ DescriptorMatcher::train
DescriptorMatcher::match
----------------------------
.. cpp:function:: void DescriptorMatcher::match( const Mat& queryDescriptors, const Mat& trainDescriptors, vector<DMatch>& matches, const Mat& mask=Mat() ) const
.. ocv:function:: void DescriptorMatcher::match( const Mat& queryDescriptors, const Mat& trainDescriptors, vector<DMatch>& matches, const Mat& mask=Mat() ) const
.. cpp:function:: void DescriptorMatcher::match( const Mat& queryDescriptors, vector<DMatch>& matches, const vector<Mat>& masks=vector<Mat>() )
.. ocv:function:: void DescriptorMatcher::match( const Mat& queryDescriptors, vector<DMatch>& matches, const vector<Mat>& masks=vector<Mat>() )
Finds the best match for each descriptor from a query set.
@@ -180,9 +180,9 @@ In the first variant of this method, the train descriptors are passed as an inpu
DescriptorMatcher::knnMatch
-------------------------------
.. cpp:function:: void DescriptorMatcher::knnMatch( const Mat& queryDescriptors, const Mat& trainDescriptors, vector<vector<DMatch> >& matches, int k, const Mat& mask=Mat(), bool compactResult=false ) const
.. ocv:function:: void DescriptorMatcher::knnMatch( const Mat& queryDescriptors, const Mat& trainDescriptors, vector<vector<DMatch> >& matches, int k, const Mat& mask=Mat(), bool compactResult=false ) const
.. cpp:function:: void DescriptorMatcher::knnMatch( const Mat& queryDescriptors, vector<vector<DMatch> >& matches, int k, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
.. ocv:function:: void DescriptorMatcher::knnMatch( const Mat& queryDescriptors, vector<vector<DMatch> >& matches, int k, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
Finds the k best matches for each descriptor from a query set.
@@ -200,15 +200,15 @@ DescriptorMatcher::knnMatch
:param compactResult: Parameter that is used when the mask (or masks) is not empty. If ``compactResult`` is false, the ``matches`` vector has the same size as ``queryDescriptors`` rows. If ``compactResult`` is true, the ``matches`` vector does not contain matches for fully masked-out query descriptors.
These extended variants of :cpp:func:`DescriptorMatcher::match` methods find several best matches for each query descriptor. The matches are returned in the distance increasing order. See :cpp:func:`DescriptorMatcher::match` for the details about query and train descriptors.
These extended variants of :ocv:func:`DescriptorMatcher::match` methods find several best matches for each query descriptor. The matches are returned in the distance increasing order. See :ocv:func:`DescriptorMatcher::match` for the details about query and train descriptors.
.. index:: DescriptorMatcher::radiusMatch
DescriptorMatcher::radiusMatch
----------------------------------
.. cpp:function:: void DescriptorMatcher::radiusMatch( const Mat& queryDescriptors, const Mat& trainDescriptors, vector<vector<DMatch> >& matches, float maxDistance, const Mat& mask=Mat(), bool compactResult=false ) const
.. ocv:function:: void DescriptorMatcher::radiusMatch( const Mat& queryDescriptors, const Mat& trainDescriptors, vector<vector<DMatch> >& matches, float maxDistance, const Mat& mask=Mat(), bool compactResult=false ) const
.. cpp:function:: void DescriptorMatcher::radiusMatch( const Mat& queryDescriptors, vector<vector<DMatch> >& matches, float maxDistance, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
.. ocv:function:: void DescriptorMatcher::radiusMatch( const Mat& queryDescriptors, vector<vector<DMatch> >& matches, float maxDistance, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
For each query descriptor, finds the training descriptors not farther than the specified distance.
@@ -232,7 +232,7 @@ For each query descriptor, the methods find such training descriptors that the d
DescriptorMatcher::clone
----------------------------
.. cpp:function:: Ptr<DescriptorMatcher> DescriptorMatcher::clone( bool emptyTrainData ) const
.. ocv:function:: Ptr<DescriptorMatcher> DescriptorMatcher::clone( bool emptyTrainData ) const
Clones the matcher.
@@ -242,7 +242,7 @@ DescriptorMatcher::clone
DescriptorMatcher::create
-----------------------------
.. cpp:function:: Ptr<DescriptorMatcher> DescriptorMatcher::create( const string& descriptorMatcherType )
.. ocv:function:: Ptr<DescriptorMatcher> DescriptorMatcher::create( const string& descriptorMatcherType )
Creates a descriptor matcher of a given type with the default parameters (using default constructor).
@@ -353,7 +353,7 @@ FlannBasedMatcher
-----------------
.. c:type:: FlannBasedMatcher
Flann-based descriptor matcher. This matcher trains :ref:`flann::Index` on a train descriptor collection and calls its nearest search methods to find the best matches. So, this matcher may be faster when matching a large train collection than the brute force matcher. ``FlannBasedMatcher`` does not support masking permissible matches of descriptor sets because :cpp:func:`flann::Index` does not support this. ::
Flann-based descriptor matcher. This matcher trains :ref:`flann::Index` on a train descriptor collection and calls its nearest search methods to find the best matches. So, this matcher may be faster when matching a large train collection than the brute force matcher. ``FlannBasedMatcher`` does not support masking permissible matches of descriptor sets because :ocv:func:`flann::Index` does not support this. ::
class FlannBasedMatcher : public DescriptorMatcher
{

56
modules/features2d/doc/common_interfaces_of_feature_detectors.rst
View File

@@ -14,7 +14,7 @@ inherit the
KeyPoint
--------
.. cpp:class:: KeyPoint
.. ocv:class:: KeyPoint
Data structure for salient point detectors ::
@@ -75,7 +75,7 @@ Data structure for salient point detectors ::
FeatureDetector
---------------
.. cpp:class:: FeatureDetector
.. ocv:class:: FeatureDetector
Abstract base class for 2D image feature detectors ::
@@ -105,7 +105,7 @@ Abstract base class for 2D image feature detectors ::
FeatureDetector::detect
---------------------------
.. cpp:function:: void FeatureDetector::detect( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const
.. ocv:function:: void FeatureDetector::detect( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const
Detects keypoints in an image (first variant) or image set (second variant).
@@ -115,7 +115,7 @@ FeatureDetector::detect
:param mask: Mask specifying where to look for keypoints (optional). It must be a char matrix with non-zero values in the region of interest.
.. cpp:function:: void FeatureDetector::detect( const vector<Mat>& images, vector<vector<KeyPoint> >& keypoints, const vector<Mat>& masks=vector<Mat>() ) const
.. ocv:function:: void FeatureDetector::detect( const vector<Mat>& images, vector<vector<KeyPoint> >& keypoints, const vector<Mat>& masks=vector<Mat>() ) const
:param images: Image set.
@@ -127,7 +127,7 @@ FeatureDetector::detect
FeatureDetector::read
-------------------------
.. cpp:function:: void FeatureDetector::read( const FileNode& fn )
.. ocv:function:: void FeatureDetector::read( const FileNode& fn )
Reads a feature detector object from a file node.
@@ -137,7 +137,7 @@ FeatureDetector::read
FeatureDetector::write
--------------------------
.. cpp:function:: void FeatureDetector::write( FileStorage& fs ) const
.. ocv:function:: void FeatureDetector::write( FileStorage& fs ) const
Writes a feature detector object to a file storage.
@@ -147,7 +147,7 @@ FeatureDetector::write
FeatureDetector::create
---------------------------
.. cpp:function:: Ptr<FeatureDetector> FeatureDetector::create( const string& detectorType )
.. ocv:function:: Ptr<FeatureDetector> FeatureDetector::create( const string& detectorType )
Creates a feature detector by its name.
@@ -175,7 +175,7 @@ for example: ``"GridFAST"``, ``"PyramidSTAR"`` .
FastFeatureDetector
-------------------
.. cpp:class:: FastFeatureDetector
.. ocv:class:: FastFeatureDetector
Wrapping class for feature detection using the
:ref:`FAST` method ::
@@ -197,7 +197,7 @@ Wrapping class for feature detection using the
GoodFeaturesToTrackDetector
---------------------------
.. cpp:class:: GoodFeaturesToTrackDetector
.. ocv:class:: GoodFeaturesToTrackDetector
Wrapping class for feature detection using the
:ref:`goodFeaturesToTrack` function ::
@@ -240,7 +240,7 @@ Wrapping class for feature detection using the
MserFeatureDetector
-------------------
.. cpp:class:: MserFeatureDetector
.. ocv:class:: MserFeatureDetector
Wrapping class for feature detection using the
:ref:`MSER` class ::
@@ -266,7 +266,7 @@ Wrapping class for feature detection using the
StarFeatureDetector
-------------------
.. cpp:class:: StarFeatureDetector
.. ocv:class:: StarFeatureDetector
Wrapping class for feature detection using the
:ref:`StarDetector` class ::
@@ -290,7 +290,7 @@ Wrapping class for feature detection using the
SiftFeatureDetector
-------------------
.. cpp:class:: SiftFeatureDetector
.. ocv:class:: SiftFeatureDetector
Wrapping class for feature detection using the
:ref:`SIFT` class ::
@@ -319,7 +319,7 @@ Wrapping class for feature detection using the
SurfFeatureDetector
-------------------
.. cpp:class:: SurfFeatureDetector
.. ocv:class:: SurfFeatureDetector
Wrapping class for feature detection using the
:ref:`SURF` class ::
@@ -342,7 +342,7 @@ Wrapping class for feature detection using the
OrbFeatureDetector
-------------------
.. cpp:class:: OrbFeatureDetector
.. ocv:class:: OrbFeatureDetector
Wrapping class for feature detection using the
:ref:`ORB` class ::
@@ -364,7 +364,7 @@ Wrapping class for feature detection using the
SimpleBlobDetector
-------------------
.. cpp:class:: SimpleBlobDetector
.. ocv:class:: SimpleBlobDetector
Class for extracting blobs from an image ::
@@ -402,7 +402,7 @@ Class for extracting blobs from an image ::
...
};
The class implements a simple algorithm for extracting blobs from an image. It converts the source image to binary images by applying thresholding with several thresholds from ``minThreshold`` (inclusive) to ``maxThreshold`` (exclusive) with distance ``thresholdStep`` between neighboring thresholds. Then connected components are extracted from every binary image by :cpp:func:`findContours` and their centers are calculated. Centers from several binary images are grouped by their coordinates. Close centers form one group that corresponds to one blob and this is controled by the ``minDistBetweenBlobs`` parameter. Then final centers of blobs and their radiuses are estimated from these groups and returned as locations and sizes of keypoints.
The class implements a simple algorithm for extracting blobs from an image. It converts the source image to binary images by applying thresholding with several thresholds from ``minThreshold`` (inclusive) to ``maxThreshold`` (exclusive) with distance ``thresholdStep`` between neighboring thresholds. Then connected components are extracted from every binary image by :ocv:func:`findContours` and their centers are calculated. Centers from several binary images are grouped by their coordinates. Close centers form one group that corresponds to one blob and this is controled by the ``minDistBetweenBlobs`` parameter. Then final centers of blobs and their radiuses are estimated from these groups and returned as locations and sizes of keypoints.
This class performs several filtrations of returned blobs. You should set ``filterBy*`` to true/false to turn on/off corresponding filtration. Available filtrations:
@@ -426,7 +426,7 @@ Default values of parameters are tuned to extract dark circular blobs.
GridAdaptedFeatureDetector
--------------------------
.. cpp:class:: GridAdaptedFeatureDetector
.. ocv:class:: GridAdaptedFeatureDetector
Class adapting a detector to partition the source image into a grid and detect points in each cell ::
@@ -456,7 +456,7 @@ Class adapting a detector to partition the source image into a grid and detect p
PyramidAdaptedFeatureDetector
-----------------------------
.. cpp:class:: PyramidAdaptedFeatureDetector
.. ocv:class:: PyramidAdaptedFeatureDetector
Class adapting a detector to detect points over multiple levels of a Gaussian pyramid. Consider using this class for detectors that are not inherently scaled. ::
@@ -477,7 +477,7 @@ Class adapting a detector to detect points over multiple levels of a Gaussian py
DynamicAdaptedFeatureDetector
-----------------------------
.. cpp:class:: DynamicAdaptedFeatureDetector
.. ocv:class:: DynamicAdaptedFeatureDetector
Adaptively adjusting detector that iteratively detects features until the desired number is found ::
@@ -522,7 +522,7 @@ Example of creating ``DynamicAdaptedFeatureDetector`` : ::
DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector
----------------------------------------------------------------
.. cpp:function:: DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector( const Ptr<AdjusterAdapter>& adjuster, int min_features, int max_features, int max_iters )
.. ocv:function:: DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector( const Ptr<AdjusterAdapter>& adjuster, int min_features, int max_features, int max_iters )
Constructs the class.
@@ -539,7 +539,7 @@ DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector
AdjusterAdapter
---------------
.. cpp:class:: AdjusterAdapter
.. ocv:class:: AdjusterAdapter
Class providing an interface for adjusting parameters of a feature detector. This interface is used by :ref:`DynamicAdaptedFeatureDetector` . It is a wrapper for :ref:`FeatureDetector` that enables adjusting parameters after feature detection. ::
@@ -563,7 +563,7 @@ See
AdjusterAdapter::tooFew
---------------------------
.. cpp:function:: void AdjusterAdapter::tooFew(int min, int n_detected)
.. ocv:function:: void AdjusterAdapter::tooFew(int min, int n_detected)
Adjusts the detector parameters to detect more features.
@@ -583,7 +583,7 @@ Example: ::
AdjusterAdapter::tooMany
----------------------------
.. cpp:function:: void AdjusterAdapter::tooMany(int max, int n_detected)
.. ocv:function:: void AdjusterAdapter::tooMany(int max, int n_detected)
Adjusts the detector parameters to detect less features.
@@ -603,7 +603,7 @@ Example: ::
AdjusterAdapter::good
-------------------------
.. cpp:function:: bool AdjusterAdapter::good() const
.. ocv:function:: bool AdjusterAdapter::good() const
Returns false if the detector parameters cannot be adjusted any more.
@@ -620,7 +620,7 @@ Example: ::
FastAdjuster
------------
.. cpp:class:: FastAdjuster
.. ocv:class:: FastAdjuster
:ref:`AdjusterAdapter` for :ref:`FastFeatureDetector`. This class decreases or increases the threshold value by 1. ::
@@ -636,7 +636,7 @@ FastAdjuster
StarAdjuster
------------
.. cpp:class:: StarAdjuster
.. ocv:class:: StarAdjuster
:ref:`AdjusterAdapter` for :ref:`StarFeatureDetector`. This class adjusts the ``responseThreshhold`` of ``StarFeatureDetector``. ::
@@ -651,7 +651,7 @@ StarAdjuster
SurfAdjuster
------------
.. cpp:class:: SurfAdjuster
.. ocv:class:: SurfAdjuster
:ref:`AdjusterAdapter` for :ref:`SurfFeatureDetector`. This class adjusts the ``hessianThreshold`` of ``SurfFeatureDetector``. ::
@@ -665,7 +665,7 @@ SurfAdjuster
FeatureDetector
---------------
.. cpp:class:: FeatureDetector
.. ocv:class:: FeatureDetector
Abstract base class for 2D image feature detectors ::

46
modules/features2d/doc/common_interfaces_of_generic_descriptor_matchers.rst
View File

@@ -7,15 +7,15 @@ Matchers of keypoint descriptors in OpenCV have wrappers with a common interface
between different algorithms solving the same problem. This section is devoted to matching descriptors
that cannot be represented as vectors in a multidimensional space. ``GenericDescriptorMatcher`` is a more generic interface for descriptors. It does not make any assumptions about descriptor representation.
Every descriptor with the
:cpp:class:`DescriptorExtractor` interface has a wrapper with the ``GenericDescriptorMatcher`` interface (see
:cpp:class:`VectorDescriptorMatcher` ).
:ocv:class:`DescriptorExtractor` interface has a wrapper with the ``GenericDescriptorMatcher`` interface (see
:ocv:class:`VectorDescriptorMatcher` ).
There are descriptors such as the One-way descriptor and Ferns that have the ``GenericDescriptorMatcher`` interface implemented but do not support ``DescriptorExtractor``.
.. index:: GenericDescriptorMatcher
GenericDescriptorMatcher
------------------------
.. cpp:class:: GenericDescriptorMatcher
.. ocv:class:: GenericDescriptorMatcher
Abstract interface for extracting and matching a keypoint descriptor. There are also :ref:`DescriptorExtractor` and :ref:`DescriptorMatcher` for these purposes but their interfaces are intended for descriptors represented as vectors in a multidimensional space. ``GenericDescriptorMatcher`` is a more generic interface for descriptors. :ref:`DescriptorMatcher` and ``GenericDescriptorMatcher`` have two groups of match methods: for matching keypoints of an image with another image or with an image set. ::
@@ -83,7 +83,7 @@ Abstract interface for extracting and matching a keypoint descriptor. There are
GenericDescriptorMatcher::add
---------------------------------
.. cpp:function:: void GenericDescriptorMatcher::add( const vector<Mat>& images, vector<vector<KeyPoint> >& keypoints )
.. ocv:function:: void GenericDescriptorMatcher::add( const vector<Mat>& images, vector<vector<KeyPoint> >& keypoints )
Adds images and their keypoints to the training collection stored in the class instance.
@@ -95,7 +95,7 @@ GenericDescriptorMatcher::add
GenericDescriptorMatcher::getTrainImages
--------------------------------------------
.. cpp:function:: const vector<Mat>& GenericDescriptorMatcher::getTrainImages() const
.. ocv:function:: const vector<Mat>& GenericDescriptorMatcher::getTrainImages() const
Returns a train image collection.
@@ -103,7 +103,7 @@ GenericDescriptorMatcher::getTrainImages
GenericDescriptorMatcher::getTrainKeypoints
-----------------------------------------------
.. cpp:function:: const vector<vector<KeyPoint> >& GenericDescriptorMatcher::getTrainKeypoints() const
.. ocv:function:: const vector<vector<KeyPoint> >& GenericDescriptorMatcher::getTrainKeypoints() const
Returns a train keypoints collection.
@@ -111,7 +111,7 @@ GenericDescriptorMatcher::getTrainKeypoints
GenericDescriptorMatcher::clear
-----------------------------------
.. cpp:function:: void GenericDescriptorMatcher::clear()
.. ocv:function:: void GenericDescriptorMatcher::clear()
Clears a train collection (images and keypoints).
@@ -119,7 +119,7 @@ GenericDescriptorMatcher::clear
GenericDescriptorMatcher::train
-----------------------------------
.. cpp:function:: void GenericDescriptorMatcher::train()
.. ocv:function:: void GenericDescriptorMatcher::train()
Trains an object, for example, a tree-based structure, to extract descriptors or to optimize descriptors matching.
@@ -127,7 +127,7 @@ GenericDescriptorMatcher::train
GenericDescriptorMatcher::isMaskSupported
---------------------------------------------
.. cpp:function:: void GenericDescriptorMatcher::isMaskSupported()
.. ocv:function:: void GenericDescriptorMatcher::isMaskSupported()
Returns true if a generic descriptor matcher supports masking permissible matches.
@@ -135,9 +135,9 @@ GenericDescriptorMatcher::isMaskSupported
GenericDescriptorMatcher::classify
--------------------------------------
.. cpp:function:: void GenericDescriptorMatcher::classify( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, const Mat& trainImage, vector<KeyPoint>& trainKeypoints ) const
.. ocv:function:: void GenericDescriptorMatcher::classify( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, const Mat& trainImage, vector<KeyPoint>& trainKeypoints ) const
.. cpp:function:: void GenericDescriptorMatcher::classify( const Mat& queryImage, vector<KeyPoint>& queryKeypoints )
.. ocv:function:: void GenericDescriptorMatcher::classify( const Mat& queryImage, vector<KeyPoint>& queryKeypoints )
Classify keypoints from a query set.
@@ -163,9 +163,9 @@ GenericDescriptorMatcher::classify
GenericDescriptorMatcher::match
-----------------------------------
.. cpp:function:: void GenericDescriptorMatcher::match( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, const Mat& trainImage, vector<KeyPoint>& trainKeypoints, vector<DMatch>& matches, const Mat& mask=Mat() ) const
.. ocv:function:: void GenericDescriptorMatcher::match( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, const Mat& trainImage, vector<KeyPoint>& trainKeypoints, vector<DMatch>& matches, const Mat& mask=Mat() ) const
.. cpp:function:: void GenericDescriptorMatcher::match( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, vector<DMatch>& matches, const vector<Mat>& masks=vector<Mat>() )
.. ocv:function:: void GenericDescriptorMatcher::match( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, vector<DMatch>& matches, const vector<Mat>& masks=vector<Mat>() )
Find the best match in the training set for each keypoint from the query set.
@@ -189,9 +189,9 @@ The methods find the best match for each query keypoint. In the first variant of
GenericDescriptorMatcher::knnMatch
--------------------------------------
.. cpp:function:: void GenericDescriptorMatcher::knnMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, const Mat& trainImage, vector<KeyPoint>& trainKeypoints, vector<vector<DMatch> >& matches, int k, const Mat& mask=Mat(), bool compactResult=false ) const
.. ocv:function:: void GenericDescriptorMatcher::knnMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, const Mat& trainImage, vector<KeyPoint>& trainKeypoints, vector<vector<DMatch> >& matches, int k, const Mat& mask=Mat(), bool compactResult=false ) const
.. cpp:function:: void GenericDescriptorMatcher::knnMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, vector<vector<DMatch> >& matches, int k, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
.. ocv:function:: void GenericDescriptorMatcher::knnMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, vector<vector<DMatch> >& matches, int k, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
Find the ``k`` best matches for each query keypoint.
@@ -201,9 +201,9 @@ The methods are extended variants of ``GenericDescriptorMatch::match``. The para
GenericDescriptorMatcher::radiusMatch
-----------------------------------------
.. cpp:function:: void GenericDescriptorMatcher::radiusMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, const Mat& trainImage, vector<KeyPoint>& trainKeypoints, vector<vector<DMatch> >& matches, float maxDistance, const Mat& mask=Mat(), bool compactResult=false ) const
.. ocv:function:: void GenericDescriptorMatcher::radiusMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, const Mat& trainImage, vector<KeyPoint>& trainKeypoints, vector<vector<DMatch> >& matches, float maxDistance, const Mat& mask=Mat(), bool compactResult=false ) const
.. cpp:function:: void GenericDescriptorMatcher::radiusMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, vector<vector<DMatch> >& matches, float maxDistance, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
.. ocv:function:: void GenericDescriptorMatcher::radiusMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, vector<vector<DMatch> >& matches, float maxDistance, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
For each query keypoint, find the training keypoints not farther than the specified distance.
@@ -213,7 +213,7 @@ The methods are similar to ``DescriptorMatcher::radiusM. But this class does not
GenericDescriptorMatcher::read
----------------------------------
.. cpp:function:: void GenericDescriptorMatcher::read( const FileNode& fn )
.. ocv:function:: void GenericDescriptorMatcher::read( const FileNode& fn )
Reads a matcher object from a file node.
@@ -221,7 +221,7 @@ GenericDescriptorMatcher::read
GenericDescriptorMatcher::write
-----------------------------------
.. cpp:function:: void GenericDescriptorMatcher::write( FileStorage& fs ) const
.. ocv:function:: void GenericDescriptorMatcher::write( FileStorage& fs ) const
Writes a match object to a file storage.
@@ -229,7 +229,7 @@ GenericDescriptorMatcher::write
GenericDescriptorMatcher::clone
-----------------------------------
.. cpp:function:: Ptr<GenericDescriptorMatcher> GenericDescriptorMatcher::clone( bool emptyTrainData ) const
.. ocv:function:: Ptr<GenericDescriptorMatcher> GenericDescriptorMatcher::clone( bool emptyTrainData ) const
Clones the matcher.
@@ -243,7 +243,7 @@ GenericDescriptorMatcher::clone
OneWayDescriptorMatcher
-----------------------
.. cpp:class:: OneWayDescriptorMatcher
.. ocv:class:: OneWayDescriptorMatcher
Wrapping class for computing, matching, and classifying descriptors using the
:ref:`OneWayDescriptorBase` class ::
@@ -302,7 +302,7 @@ Wrapping class for computing, matching, and classifying descriptors using the
FernDescriptorMatcher
---------------------
.. cpp:class:: FernDescriptorMatcher
.. ocv:class:: FernDescriptorMatcher
Wrapping class for computing, matching, and classifying descriptors using the
:ref:`FernClassifier` class ::
@@ -361,7 +361,7 @@ Wrapping class for computing, matching, and classifying descriptors using the
VectorDescriptorMatcher
-----------------------
.. cpp:class:: VectorDescriptorMatcher
.. ocv:class:: VectorDescriptorMatcher
Class used for matching descriptors that can be described as vectors in a finite-dimensional space ::

6
modules/features2d/doc/drawing_function_of_keypoints_and_matches.rst
View File

@@ -6,9 +6,9 @@ Drawing Function of Keypoints and Matches
drawMatches
---------------
.. cpp:function:: void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1, const Mat& img2, const vector<KeyPoint>& keypoints2, const vector<DMatch>& matches1to2, Mat& outImg, const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1), const vector<char>& matchesMask=vector<char>(), int flags=DrawMatchesFlags::DEFAULT )
.. ocv:function:: void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1, const Mat& img2, const vector<KeyPoint>& keypoints2, const vector<DMatch>& matches1to2, Mat& outImg, const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1), const vector<char>& matchesMask=vector<char>(), int flags=DrawMatchesFlags::DEFAULT )
.. cpp:function:: void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1, const Mat& img2, const vector<KeyPoint>& keypoints2, const vector<vector<DMatch> >& matches1to2, Mat& outImg, const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1), const vector<vector<char>>& matchesMask= vector<vector<char> >(), int flags=DrawMatchesFlags::DEFAULT )
.. ocv:function:: void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1, const Mat& img2, const vector<KeyPoint>& keypoints2, const vector<vector<DMatch> >& matches1to2, Mat& outImg, const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1), const vector<vector<char>>& matchesMask= vector<vector<char> >(), int flags=DrawMatchesFlags::DEFAULT )
Draw the found matches of keypoints from two images
@@ -63,7 +63,7 @@ This function draws matches of keypoints from two images in the output image. Ma
drawKeypoints
-----------------
.. cpp:function:: void drawKeypoints( const Mat& image, const vector<KeyPoint>& keypoints, Mat& outImg, const Scalar& color=Scalar::all(-1), int flags=DrawMatchesFlags::DEFAULT )
.. ocv:function:: void drawKeypoints( const Mat& image, const vector<KeyPoint>& keypoints, Mat& outImg, const Scalar& color=Scalar::all(-1), int flags=DrawMatchesFlags::DEFAULT )
Draws keypoints.

54
modules/features2d/doc/feature_detection_and_description.rst
View File

@@ -7,7 +7,7 @@ Feature Detection and Description
FAST
--------
.. cpp:function:: void FAST( const Mat& image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSupression=true )
.. ocv:function:: void FAST( const Mat& image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSupression=true )
Detects corners using the FAST algorithm by E. Rosten (*Machine learning for high-speed corner detection*, 2006).
@@ -25,7 +25,7 @@ FAST
MSER
----
.. cpp:class:: MSER
.. ocv:class:: MSER
Maximally stable extremal region extractor ::
@@ -54,7 +54,7 @@ http://en.wikipedia.org/wiki/Maximally_stable_extremal_regions).
StarDetector
------------
.. cpp:class:: StarDetector
.. ocv:class:: StarDetector
Class implementing the Star keypoint detector ::
@@ -93,7 +93,7 @@ The class implements a modified version of the ``CenSurE`` keypoint detector des
SIFT
----
.. cpp:class:: SIFT
.. ocv:class:: SIFT
Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) approach ::
@@ -183,7 +183,7 @@ Class for extracting keypoints and computing descriptors using the Scale Invaria
SURF
----
.. cpp:class:: SURF
.. ocv:class:: SURF
Class for extracting Speeded Up Robust Features from an image ::
@@ -223,7 +223,7 @@ The algorithm can be used for object tracking and localization, image stitching,
ORB
----
.. cpp:class:: ORB
.. ocv:class:: ORB
Class for extracting ORB features and descriptors from an image ::
@@ -281,7 +281,7 @@ The class implements ORB
RandomizedTree
--------------
.. cpp:class:: RandomizedTree
.. ocv:class:: RandomizedTree
Class containing a base structure for ``RTreeClassifier`` ::
@@ -355,11 +355,11 @@ Class containing a base structure for ``RTreeClassifier`` ::
RandomizedTree::train
-------------------------
.. cpp:function:: void train(std::vector<BaseKeypoint> const& base_set, RNG& rng, PatchGenerator& make_patch, int depth, int views, size_t reduced_num_dim, int num_quant_bits)
.. ocv:function:: void train(std::vector<BaseKeypoint> const& base_set, RNG& rng, PatchGenerator& make_patch, int depth, int views, size_t reduced_num_dim, int num_quant_bits)
Trains a randomized tree using an input set of keypoints.
.. cpp:function:: void train(std::vector<BaseKeypoint> const& base_set, RNG& rng, PatchGenerator& make_patch, int depth, int views, size_t reduced_num_dim, int num_quant_bits)
.. ocv:function:: void train(std::vector<BaseKeypoint> const& base_set, RNG& rng, PatchGenerator& make_patch, int depth, int views, size_t reduced_num_dim, int num_quant_bits)
:param base_set: Vector of the ``BaseKeypoint`` type. It contains image keypoints used for training.
@@ -379,9 +379,9 @@ RandomizedTree::train
RandomizedTree::read
------------------------
.. cpp:function:: read(const char* file_name, int num_quant_bits)
.. ocv:function:: read(const char* file_name, int num_quant_bits)
.. cpp:function:: read(std::istream &is, int num_quant_bits)
.. ocv:function:: read(std::istream &is, int num_quant_bits)
Reads a pre-saved randomized tree from a file or stream.
@@ -395,11 +395,11 @@ RandomizedTree::read
RandomizedTree::write
-------------------------
.. cpp:function:: void write(const char* file_name) const
.. ocv:function:: void write(const char* file_name) const
Writes the current randomized tree to a file or stream.
.. cpp:function:: void write(std::ostream \&os) const
.. ocv:function:: void write(std::ostream \&os) const
:param file_name: Name of the file where randomized tree data is stored.
@@ -409,7 +409,7 @@ RandomizedTree::write
RandomizedTree::applyQuantization
-------------------------------------
.. cpp:function:: void applyQuantization(int num_quant_bits)
.. ocv:function:: void applyQuantization(int num_quant_bits)
Applies quantization to the current randomized tree.
@@ -421,7 +421,7 @@ RandomizedTree::applyQuantization
RTreeNode
---------
.. cpp:class:: RTreeNode
.. ocv:class:: RTreeNode
Class containing a base structure for ``RandomizedTree`` ::
@@ -449,7 +449,7 @@ Class containing a base structure for ``RandomizedTree`` ::
RTreeClassifier
---------------
.. cpp:class:: RTreeClassifier
.. ocv:class:: RTreeClassifier
Class containing ``RTreeClassifier``. It represents the Calonder descriptor that was originally introduced by Michael Calonder. ::
@@ -519,11 +519,11 @@ Class containing ``RTreeClassifier``. It represents the Calonder descriptor that
RTreeClassifier::train
--------------------------
.. cpp:function:: void train(vector<BaseKeypoint> const& base_set, RNG& rng, int num_trees = RTreeClassifier::DEFAULT_TREES, int depth = DEFAULT_DEPTH, int views = DEFAULT_VIEWS, size_t reduced_num_dim = DEFAULT_REDUCED_NUM_DIM, int num_quant_bits = DEFAULT_NUM_QUANT_BITS, bool print_status = true)
.. ocv:function:: void train(vector<BaseKeypoint> const& base_set, RNG& rng, int num_trees = RTreeClassifier::DEFAULT_TREES, int depth = DEFAULT_DEPTH, int views = DEFAULT_VIEWS, size_t reduced_num_dim = DEFAULT_REDUCED_NUM_DIM, int num_quant_bits = DEFAULT_NUM_QUANT_BITS, bool print_status = true)
Trains a randomized tree classifier using an input set of keypoints.
.. cpp:function:: void train(vector<BaseKeypoint> const& base_set, RNG& rng, PatchGenerator& make_patch, int num_trees = RTreeClassifier::DEFAULT_TREES, int depth = DEFAULT_DEPTH, int views = DEFAULT_VIEWS, size_t reduced_num_dim = DEFAULT_REDUCED_NUM_DIM, int num_quant_bits = DEFAULT_NUM_QUANT_BITS, bool print_status = true)
.. ocv:function:: void train(vector<BaseKeypoint> const& base_set, RNG& rng, PatchGenerator& make_patch, int num_trees = RTreeClassifier::DEFAULT_TREES, int depth = DEFAULT_DEPTH, int views = DEFAULT_VIEWS, size_t reduced_num_dim = DEFAULT_REDUCED_NUM_DIM, int num_quant_bits = DEFAULT_NUM_QUANT_BITS, bool print_status = true)
:param base_set: Vector of the ``BaseKeypoint`` type. It contains image keypoints used for training.
@@ -547,11 +547,11 @@ RTreeClassifier::train
RTreeClassifier::getSignature
---------------------------------
.. cpp:function:: void getSignature(IplImage *patch, uchar *sig)
.. ocv:function:: void getSignature(IplImage *patch, uchar *sig)
Returns a signature for an image patch.
.. cpp:function:: void getSignature(IplImage *patch, float *sig)
.. ocv:function:: void getSignature(IplImage *patch, float *sig)
:param patch: Image patch to calculate the signature for.
:param sig: Output signature (array dimension is ``reduced_num_dim)`` .
@@ -561,7 +561,7 @@ RTreeClassifier::getSignature
RTreeClassifier::getSparseSignature
---------------------------------------
.. cpp:function:: void getSparseSignature(IplImage *patch, float *sig, float thresh)
.. ocv:function:: void getSparseSignature(IplImage *patch, float *sig, float thresh)
Returns a signature for an image patch similarly to ``getSignature`` but uses a threshold for removing all signature elements below the threshold so that the signature is compressed.
@@ -575,7 +575,7 @@ RTreeClassifier::getSparseSignature
RTreeClassifier::countNonZeroElements
-----------------------------------------
.. cpp:function:: static int countNonZeroElements(float *vec, int n, double tol=1e-10)
.. ocv:function:: static int countNonZeroElements(float *vec, int n, double tol=1e-10)
Returns the number of non-zero elements in an input array.
@@ -589,11 +589,11 @@ RTreeClassifier::countNonZeroElements
RTreeClassifier::read
-------------------------
.. cpp:function:: read(const char* file_name)
.. ocv:function:: read(const char* file_name)
Reads a pre-saved ``RTreeClassifier`` from a file or stream.
.. cpp:function:: read(std::istream& is)
.. ocv:function:: read(std::istream& is)
:param file_name: Name of the file that contains randomized tree data.
@@ -603,11 +603,11 @@ RTreeClassifier::read
RTreeClassifier::write
--------------------------
.. cpp:function:: void write(const char* file_name) const
.. ocv:function:: void write(const char* file_name) const
Writes the current ``RTreeClassifier`` to a file or stream.
.. cpp:function:: void write(std::ostream &os) const
.. ocv:function:: void write(std::ostream &os) const
:param file_name: Name of the file where randomized tree data is stored.
@@ -617,7 +617,7 @@ RTreeClassifier::write
RTreeClassifier::setQuantization
------------------------------------
.. cpp:function:: void setQuantization(int num_quant_bits)
.. ocv:function:: void setQuantization(int num_quant_bits)
Applies quantization to the current randomized tree.

28
modules/features2d/doc/object_categorization.rst
View File

@@ -11,7 +11,7 @@ This section describes approaches based on local 2D features and used to categor
BOWTrainer
----------
.. cpp:class:: BOWTrainer
.. ocv:class:: BOWTrainer
Abstract base class for training the *bag of visual words* vocabulary from a set of descriptors.
For details, see, for example, *Visual Categorization with Bags of Keypoints* by Gabriella Csurka, Christopher R. Dance,
@@ -41,7 +41,7 @@ Lixin Fan, Jutta Willamowski, Cedric Bray, 2004. ::
BOWTrainer::add
-------------------
.. cpp:function:: void BOWTrainer::add( const Mat& descriptors )
.. ocv:function:: void BOWTrainer::add( const Mat& descriptors )
Adds descriptors to a training set. The training set is clustered using ``clustermethod`` to construct the vocabulary.
@@ -51,7 +51,7 @@ BOWTrainer::add
BOWTrainer::getDescriptors
------------------------------
.. cpp:function:: const vector<Mat>& BOWTrainer::getDescriptors() const
.. ocv:function:: const vector<Mat>& BOWTrainer::getDescriptors() const
Returns a training set of descriptors.
@@ -59,7 +59,7 @@ BOWTrainer::getDescriptors
BOWTrainer::descripotorsCount
---------------------------------
.. cpp:function:: const vector<Mat>& BOWTrainer::descripotorsCount() const
.. ocv:function:: const vector<Mat>& BOWTrainer::descripotorsCount() const
Returns the count of all descriptors stored in the training set.
@@ -67,11 +67,11 @@ BOWTrainer::descripotorsCount
BOWTrainer::cluster
-----------------------
.. cpp:function:: Mat BOWTrainer::cluster() const
.. ocv:function:: Mat BOWTrainer::cluster() const
Clusters train descriptors. The vocabulary consists of cluster centers. So, this method returns the vocabulary. In the first variant of the method, train descriptors stored in the object are clustered. In the second variant, input descriptors are clustered.
.. cpp:function:: Mat BOWTrainer::cluster( const Mat& descriptors ) const
.. ocv:function:: Mat BOWTrainer::cluster( const Mat& descriptors ) const
:param descriptors: Descriptors to cluster. Each row of the ``descriptors`` matrix is a descriptor. Descriptors are not added to the inner train descriptor set.
@@ -81,7 +81,7 @@ BOWTrainer::cluster
BOWKMeansTrainer
----------------
.. cpp:class:: BOWKMeansTrainer
.. ocv:class:: BOWKMeansTrainer
:ref:`kmeans` -based class to train visual vocabulary using the *bag of visual words* approach ::
@@ -111,7 +111,7 @@ arguments.
BOWImgDescriptorExtractor
-------------------------
.. cpp:class:: BOWImgDescriptorExtractor
.. ocv:class:: BOWImgDescriptorExtractor
Class to compute an image descriptor using the ''bag of visual words''. Such a computation consists of the following steps:
@@ -146,7 +146,7 @@ Here is the class declaration ::
BOWImgDescriptorExtractor::BOWImgDescriptorExtractor
--------------------------------------------------------
.. cpp:function:: BOWImgDescriptorExtractor::BOWImgDescriptorExtractor( const Ptr<DescriptorExtractor>& dextractor, const Ptr<DescriptorMatcher>& dmatcher )
.. ocv:function:: BOWImgDescriptorExtractor::BOWImgDescriptorExtractor( const Ptr<DescriptorExtractor>& dextractor, const Ptr<DescriptorMatcher>& dmatcher )
The class constructor.
@@ -158,7 +158,7 @@ BOWImgDescriptorExtractor::BOWImgDescriptorExtractor
BOWImgDescriptorExtractor::setVocabulary
--------------------------------------------
.. cpp:function:: void BOWImgDescriptorExtractor::setVocabulary( const Mat& vocabulary )
.. ocv:function:: void BOWImgDescriptorExtractor::setVocabulary( const Mat& vocabulary )
Sets a visual vocabulary.
@@ -168,7 +168,7 @@ BOWImgDescriptorExtractor::setVocabulary
BOWImgDescriptorExtractor::getVocabulary
--------------------------------------------
.. cpp:function:: const Mat& BOWImgDescriptorExtractor::getVocabulary() const
.. ocv:function:: const Mat& BOWImgDescriptorExtractor::getVocabulary() const
Returns the set vocabulary.
@@ -176,7 +176,7 @@ BOWImgDescriptorExtractor::getVocabulary
BOWImgDescriptorExtractor::compute
--------------------------------------
.. cpp:function:: void BOWImgDescriptorExtractor::compute( const Mat& image, vector<KeyPoint>& keypoints, Mat& imgDescriptor, vector<vector<int> >* pointIdxsOfClusters=0, Mat* descriptors=0 )
.. ocv:function:: void BOWImgDescriptorExtractor::compute( const Mat& image, vector<KeyPoint>& keypoints, Mat& imgDescriptor, vector<vector<int> >* pointIdxsOfClusters=0, Mat* descriptors=0 )
Computes an image descriptor using the set visual vocabulary.
@@ -194,7 +194,7 @@ BOWImgDescriptorExtractor::compute
BOWImgDescriptorExtractor::descriptorSize
---------------------------------------------
.. cpp:function:: int BOWImgDescriptorExtractor::descriptorSize() const
.. ocv:function:: int BOWImgDescriptorExtractor::descriptorSize() const
Returns an image discriptor size if the vocabulary is set. Otherwise, it returns 0.
@@ -202,7 +202,7 @@ BOWImgDescriptorExtractor::descriptorSize
BOWImgDescriptorExtractor::descriptorType
---------------------------------------------
.. cpp:function:: int BOWImgDescriptorExtractor::descriptorType() const
.. ocv:function:: int BOWImgDescriptorExtractor::descriptorType() const
Returns an image descriptor type.