fixed #1140 and made some other updates of features2d docs

pull/13383/head
Maria Dimashova 14 years ago
parent 3be51ded5d
commit 4f86b30abc
  1. 6
      doc/check_docs_whitelist.txt
  2. 2
      modules/features2d/doc/common_interfaces_of_descriptor_extractors.rst
  3. 99
      modules/features2d/doc/common_interfaces_of_feature_detectors.rst
  4. 22
      modules/features2d/doc/object_categorization.rst

@ -31,6 +31,12 @@ cv::BaseRowFilter
cv::BaseColumnFilter cv::BaseColumnFilter
cv::Moments cv::Moments
###################################### features2d###################################
cv::BOWKMeansTrainer::cluster
cv::BOWTrainer::BOWTrainer
cv::BOWTrainer::clear
cv::AdjusterAdapter::clone
######################################## calib3d ################################### ######################################## calib3d ###################################
CvLevMarq CvLevMarq
Mat cv::findFundamentalMat( InputArray points1, InputArray points2, OutputArray mask, int method=FM_RANSAC, double param1=3., double param2=0.99) Mat cv::findFundamentalMat( InputArray points1, InputArray points2, OutputArray mask, int method=FM_RANSAC, double param1=3., double param2=0.99)

@ -57,7 +57,7 @@ DescriptorExtractor::compute
:param image: Image. :param image: Image.
:param keypoints: Keypoints. Keypoints for which a descriptor cannot be computed are removed. :param keypoints: Keypoints. Keypoints for which a descriptor cannot be computed are removed. Somtimes new keypoints can be added, eg SIFT duplicates keypoint with several dominant orientations (for each orientation).
:param descriptors: Descriptors. Row i is the descriptor for keypoint i. :param descriptors: Descriptors. Row i is the descriptor for keypoint i.

@ -8,10 +8,6 @@ between different algorithms solving the same problem. All objects that implemen
inherit the inherit the
:ref:`FeatureDetector` interface. :ref:`FeatureDetector` interface.
.. index:: KeyPoint
.. KeyPoint:
KeyPoint KeyPoint
-------- --------
.. ocv:class:: KeyPoint .. ocv:class:: KeyPoint
@ -68,11 +64,6 @@ Data structure for salient point detectors ::
.. ..
.. index:: FeatureDetector
.. _FeatureDetector:
FeatureDetector FeatureDetector
--------------- ---------------
.. ocv:class:: FeatureDetector .. ocv:class:: FeatureDetector
@ -100,9 +91,6 @@ Abstract base class for 2D image feature detectors ::
... ...
}; };
.. index:: FeatureDetector::detect
FeatureDetector::detect FeatureDetector::detect
--------------------------- ---------------------------
.. ocv: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
@ -123,8 +111,6 @@ FeatureDetector::detect
:param masks: Masks for each input image specifying where to look for keypoints (optional). ``masks[i]`` is a mask for ``images[i]`` . Each element of the ``masks`` vector must be a char matrix with non-zero values in the region of interest. :param masks: Masks for each input image specifying where to look for keypoints (optional). ``masks[i]`` is a mask for ``images[i]`` . Each element of the ``masks`` vector must be a char matrix with non-zero values in the region of interest.
.. index:: FeatureDetector::read
FeatureDetector::read FeatureDetector::read
------------------------- -------------------------
.. ocv:function:: void FeatureDetector::read( const FileNode& fn ) .. ocv:function:: void FeatureDetector::read( const FileNode& fn )
@ -133,8 +119,6 @@ FeatureDetector::read
:param fn: File node from which the detector is read. :param fn: File node from which the detector is read.
.. index:: FeatureDetector::write
FeatureDetector::write FeatureDetector::write
-------------------------- --------------------------
.. ocv:function:: void FeatureDetector::write( FileStorage& fs ) const .. ocv:function:: void FeatureDetector::write( FileStorage& fs ) const
@ -143,8 +127,6 @@ FeatureDetector::write
:param fs: File storage where the detector is written. :param fs: File storage where the detector is written.
.. index:: FeatureDetector::create
FeatureDetector::create FeatureDetector::create
--------------------------- ---------------------------
.. ocv:function:: Ptr<FeatureDetector> FeatureDetector::create( const string& detectorType ) .. ocv:function:: Ptr<FeatureDetector> FeatureDetector::create( const string& detectorType )
@ -169,10 +151,6 @@ Also a combined format is supported: feature detector adapter name ( ``"Grid"``
:ref:`PyramidAdaptedFeatureDetector` ) + feature detector name (see above), :ref:`PyramidAdaptedFeatureDetector` ) + feature detector name (see above),
for example: ``"GridFAST"``, ``"PyramidSTAR"`` . for example: ``"GridFAST"``, ``"PyramidSTAR"`` .
.. index:: FastFeatureDetector
.. _FastFeatureDetector:
FastFeatureDetector FastFeatureDetector
------------------- -------------------
.. ocv:class:: FastFeatureDetector .. ocv:class:: FastFeatureDetector
@ -190,11 +168,6 @@ Wrapping class for feature detection using the
... ...
}; };
.. index:: GoodFeaturesToTrackDetector
.. _GoodFeaturesToTrackDetector:
GoodFeaturesToTrackDetector GoodFeaturesToTrackDetector
--------------------------- ---------------------------
.. ocv:class:: GoodFeaturesToTrackDetector .. ocv:class:: GoodFeaturesToTrackDetector
@ -233,11 +206,6 @@ Wrapping class for feature detection using the
... ...
}; };
.. index:: MserFeatureDetector
.. _MserFeatureDetector:
MserFeatureDetector MserFeatureDetector
------------------- -------------------
.. ocv:class:: MserFeatureDetector .. ocv:class:: MserFeatureDetector
@ -260,10 +228,6 @@ Wrapping class for feature detection using the
}; };
.. index:: StarFeatureDetector
.. _StarFeatureDetector:
StarFeatureDetector StarFeatureDetector
------------------- -------------------
.. ocv:class:: StarFeatureDetector .. ocv:class:: StarFeatureDetector
@ -283,11 +247,6 @@ Wrapping class for feature detection using the
... ...
}; };
.. index:: SiftFeatureDetector
.. _SiftFeatureDetector:
SiftFeatureDetector SiftFeatureDetector
------------------- -------------------
.. ocv:class:: SiftFeatureDetector .. ocv:class:: SiftFeatureDetector
@ -312,11 +271,6 @@ Wrapping class for feature detection using the
... ...
}; };
.. index:: SurfFeatureDetector
.. _SurfFeatureDetector:
SurfFeatureDetector SurfFeatureDetector
------------------- -------------------
.. ocv:class:: SurfFeatureDetector .. ocv:class:: SurfFeatureDetector
@ -336,10 +290,6 @@ Wrapping class for feature detection using the
}; };
.. index:: OrbFeatureDetector
.. _OrbFeatureDetector:
OrbFeatureDetector OrbFeatureDetector
------------------- -------------------
.. ocv:class:: OrbFeatureDetector .. ocv:class:: OrbFeatureDetector
@ -357,11 +307,6 @@ Wrapping class for feature detection using the
... ...
}; };
.. index:: SimpleBlobDetector
.. _SimpleBlobDetector:
SimpleBlobDetector SimpleBlobDetector
------------------- -------------------
.. ocv:class:: SimpleBlobDetector .. ocv:class:: SimpleBlobDetector
@ -419,11 +364,6 @@ This class performs several filtrations of returned blobs. You should set ``filt
Default values of parameters are tuned to extract dark circular blobs. Default values of parameters are tuned to extract dark circular blobs.
.. index:: GridAdaptedFeatureDetector
.. _GridAdaptedFeatureDetector:
GridAdaptedFeatureDetector GridAdaptedFeatureDetector
-------------------------- --------------------------
.. ocv:class:: GridAdaptedFeatureDetector .. ocv:class:: GridAdaptedFeatureDetector
@ -449,11 +389,6 @@ Class adapting a detector to partition the source image into a grid and detect p
... ...
}; };
.. index:: PyramidAdaptedFeatureDetector
.. _PyramidAdaptedFeatureDetector:
PyramidAdaptedFeatureDetector PyramidAdaptedFeatureDetector
----------------------------- -----------------------------
.. ocv:class:: PyramidAdaptedFeatureDetector .. ocv:class:: PyramidAdaptedFeatureDetector
@ -472,11 +407,8 @@ Class adapting a detector to detect points over multiple levels of a Gaussian py
}; };
.. index:: DynamicAdaptedFeatureDetector
DynamicAdaptedFeatureDetector DynamicAdaptedFeatureDetector
----------------------------- -----------------------------
.. ocv:class:: DynamicAdaptedFeatureDetector .. ocv:class:: DynamicAdaptedFeatureDetector
Adaptively adjusting detector that iteratively detects features until the desired number is found :: Adaptively adjusting detector that iteratively detects features until the desired number is found ::
@ -516,10 +448,6 @@ Example of creating ``DynamicAdaptedFeatureDetector`` : ::
Ptr<FeatureDetector> detector(new DynamicAdaptedFeatureDetector (100, 110, 10, Ptr<FeatureDetector> detector(new DynamicAdaptedFeatureDetector (100, 110, 10,
new FastAdjuster(20,true))); new FastAdjuster(20,true)));
.. index:: DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector
DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector
---------------------------------------------------------------- ----------------------------------------------------------------
.. ocv: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 )
@ -534,11 +462,8 @@ DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector
:param max_iters: Maximum number of times to try adjusting the feature detector parameters. For :ref:`FastAdjuster` , this number can be high, but with ``Star`` or ``Surf`` many iterations can be time-comsuming. At each iteration the detector is rerun. :param max_iters: Maximum number of times to try adjusting the feature detector parameters. For :ref:`FastAdjuster` , this number can be high, but with ``Star`` or ``Surf`` many iterations can be time-comsuming. At each iteration the detector is rerun.
.. index:: AdjusterAdapter
AdjusterAdapter AdjusterAdapter
--------------- ---------------
.. ocv: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. :: 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. ::
@ -550,6 +475,8 @@ Class providing an interface for adjusting parameters of a feature detector. Thi
virtual void tooFew(int min, int n_detected) = 0; virtual void tooFew(int min, int n_detected) = 0;
virtual void tooMany(int max, int n_detected) = 0; virtual void tooMany(int max, int n_detected) = 0;
virtual bool good() const = 0; virtual bool good() const = 0;
virtual Ptr<AdjusterAdapter> clone() const = 0;
static Ptr<AdjusterAdapter> create( const string& detectorType );
}; };
@ -558,9 +485,6 @@ See
:ref:`StarAdjuster`, :ref:`StarAdjuster`,
:ref:`SurfAdjuster` for concrete implementations. :ref:`SurfAdjuster` for concrete implementations.
.. index:: AdjusterAdapter::tooFew
AdjusterAdapter::tooFew AdjusterAdapter::tooFew
--------------------------- ---------------------------
.. ocv:function:: void AdjusterAdapter::tooFew(int min, int n_detected) .. ocv:function:: void AdjusterAdapter::tooFew(int min, int n_detected)
@ -578,9 +502,6 @@ Example: ::
thresh_--; thresh_--;
} }
.. index:: AdjusterAdapter::tooMany
AdjusterAdapter::tooMany AdjusterAdapter::tooMany
---------------------------- ----------------------------
.. ocv:function:: void AdjusterAdapter::tooMany(int max, int n_detected) .. ocv:function:: void AdjusterAdapter::tooMany(int max, int n_detected)
@ -599,8 +520,6 @@ Example: ::
} }
.. index:: AdjusterAdapter::good
AdjusterAdapter::good AdjusterAdapter::good
------------------------- -------------------------
.. ocv:function:: bool AdjusterAdapter::good() const .. ocv:function:: bool AdjusterAdapter::good() const
@ -614,12 +533,14 @@ Example: ::
return (thresh_ > 1) && (thresh_ < 200); return (thresh_ > 1) && (thresh_ < 200);
} }
AdjusterAdapter::create
-------------------------
.. ocv:function:: Ptr<AdjusterAdapter> AdjusterAdapter::create( const string& detectorType )
.. index:: FastAdjuster Creates adjuster adapter by name ``detectorType``. The detector name is the same as in :ocv:func:`FeatureDetector::create`, but now supported ``"FAST"``, ``"STAR"`` and ``"SURF"`` only.
FastAdjuster FastAdjuster
------------ ------------
.. ocv:class:: FastAdjuster .. ocv:class:: FastAdjuster
:ref:`AdjusterAdapter` for :ref:`FastFeatureDetector`. This class decreases or increases the threshold value by 1. :: :ref:`AdjusterAdapter` for :ref:`FastFeatureDetector`. This class decreases or increases the threshold value by 1. ::
@ -631,11 +552,8 @@ FastAdjuster
... ...
}; };
.. index:: StarAdjuster
StarAdjuster StarAdjuster
------------ ------------
.. ocv:class:: StarAdjuster .. ocv:class:: StarAdjuster
:ref:`AdjusterAdapter` for :ref:`StarFeatureDetector`. This class adjusts the ``responseThreshhold`` of ``StarFeatureDetector``. :: :ref:`AdjusterAdapter` for :ref:`StarFeatureDetector`. This class adjusts the ``responseThreshhold`` of ``StarFeatureDetector``. ::
@ -646,11 +564,8 @@ StarAdjuster
... ...
}; };
.. index:: SurfAdjuster
SurfAdjuster SurfAdjuster
------------ ------------
.. ocv:class:: SurfAdjuster .. ocv:class:: SurfAdjuster
:ref:`AdjusterAdapter` for :ref:`SurfFeatureDetector`. This class adjusts the ``hessianThreshold`` of ``SurfFeatureDetector``. :: :ref:`AdjusterAdapter` for :ref:`SurfFeatureDetector`. This class adjusts the ``hessianThreshold`` of ``SurfFeatureDetector``. ::
@ -661,8 +576,6 @@ SurfAdjuster
... ...
}; };
.. index:: FeatureDetector
FeatureDetector FeatureDetector
--------------- ---------------
.. ocv:class:: FeatureDetector .. ocv:class:: FeatureDetector

@ -5,10 +5,6 @@ Object Categorization
This section describes approaches based on local 2D features and used to categorize objects. This section describes approaches based on local 2D features and used to categorize objects.
.. index:: BOWTrainer
.. _BOWTrainer:
BOWTrainer BOWTrainer
---------- ----------
.. ocv:class:: BOWTrainer .. ocv:class:: BOWTrainer
@ -36,9 +32,6 @@ Lixin Fan, Jutta Willamowski, Cedric Bray, 2004. ::
... ...
}; };
.. index:: BOWTrainer::add
BOWTrainer::add BOWTrainer::add
------------------- -------------------
.. ocv:function:: void BOWTrainer::add( const Mat& descriptors ) .. ocv:function:: void BOWTrainer::add( const Mat& descriptors )
@ -47,7 +40,6 @@ BOWTrainer::add
:param descriptors: Descriptors to add to a training set. Each row of the ``descriptors`` matrix is a descriptor. :param descriptors: Descriptors to add to a training set. Each row of the ``descriptors`` matrix is a descriptor.
.. index:: BOWTrainer::getDescriptors
BOWTrainer::getDescriptors BOWTrainer::getDescriptors
------------------------------ ------------------------------
@ -83,7 +75,8 @@ BOWKMeansTrainer
---------------- ----------------
.. ocv:class:: BOWKMeansTrainer .. ocv:class:: BOWKMeansTrainer
:ref:`kmeans` -based class to train visual vocabulary using the *bag of visual words* approach :: :ref:`kmeans` -based class to train visual vocabulary using the *bag of visual words* approach.
::
class BOWKMeansTrainer : public BOWTrainer class BOWKMeansTrainer : public BOWTrainer
{ {
@ -100,14 +93,11 @@ BOWKMeansTrainer
... ...
}; };
BOWKMeansTrainer::BOWKMeansTrainer
----------------
.. ocv:function:: BOWKMeansTrainer::BOWKMeansTrainer( int clusterCount, const TermCriteria& termcrit=TermCriteria(), int attempts=3, int flags=KMEANS_PP_CENTERS );
To understand constructor parameters, see To understand constructor parameters, see :ref:`kmeans` function arguments.
:ref:`kmeans` function
arguments.
.. index:: BOWImgDescriptorExtractor
.. _BOWImgDescriptorExtractor:
BOWImgDescriptorExtractor BOWImgDescriptorExtractor
------------------------- -------------------------

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