generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

fixed #1140 and made some other updates of features2d docs

Browse Source
This commit is contained in:
Maria Dimashova 2011-06-17 13:23:28 +00:00
parent 3be51ded5d
commit 4f86b30abc
5 changed files with 25 additions and 116 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
doc/check_docs_whitelist.txt
View File

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

2
modules/features2d/doc/common_interfaces_of_descriptor_extractors.rst
View File

@ -57,7 +57,7 @@ DescriptorExtractor::compute
: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.

4
modules/features2d/doc/common_interfaces_of_descriptor_matchers.rst
View File

@ -158,9 +158,9 @@ DescriptorMatcher::train
DescriptorMatcher::match
----------------------------
.. ocv: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
.. ocv: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.

107
modules/features2d/doc/common_interfaces_of_feature_detectors.rst
View File

@ -8,10 +8,6 @@ between different algorithms solving the same problem. All objects that implemen
inherit the
:ref:`FeatureDetector` interface.
.. index:: KeyPoint
.. KeyPoint:
KeyPoint
--------
.. ocv:class:: KeyPoint
@ -68,11 +64,6 @@ Data structure for salient point detectors ::
..
.. index:: FeatureDetector
.. _FeatureDetector:
FeatureDetector
---------------
.. ocv:class:: FeatureDetector
@ -100,9 +91,6 @@ Abstract base class for 2D image feature detectors ::
...
};
.. index:: FeatureDetector::detect
FeatureDetector::detect
---------------------------
.. 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.
.. index:: FeatureDetector::read
FeatureDetector::read
-------------------------
.. ocv:function:: void FeatureDetector::read( const FileNode& fn )
@ -133,8 +119,6 @@ FeatureDetector::read
:param fn: File node from which the detector is read.
.. index:: FeatureDetector::write
FeatureDetector::write
--------------------------
.. ocv:function:: void FeatureDetector::write( FileStorage& fs ) const
@ -143,8 +127,6 @@ FeatureDetector::write
:param fs: File storage where the detector is written.
.. index:: FeatureDetector::create
FeatureDetector::create
---------------------------
.. 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),
for example: ``"GridFAST"``, ``"PyramidSTAR"`` .
.. index:: FastFeatureDetector
.. _FastFeatureDetector:
FastFeatureDetector
-------------------
.. ocv:class:: FastFeatureDetector
@ -190,11 +168,6 @@ Wrapping class for feature detection using the
...
};
.. index:: GoodFeaturesToTrackDetector
.. _GoodFeaturesToTrackDetector:
GoodFeaturesToTrackDetector
---------------------------
.. ocv:class:: GoodFeaturesToTrackDetector
@ -233,11 +206,6 @@ Wrapping class for feature detection using the
...
};
.. index:: MserFeatureDetector
.. _MserFeatureDetector:
MserFeatureDetector
-------------------
.. ocv:class:: MserFeatureDetector
@ -260,10 +228,6 @@ Wrapping class for feature detection using the
};
.. index:: StarFeatureDetector
.. _StarFeatureDetector:
StarFeatureDetector
-------------------
.. ocv:class:: StarFeatureDetector
@ -283,11 +247,6 @@ Wrapping class for feature detection using the
...
};
.. index:: SiftFeatureDetector
.. _SiftFeatureDetector:
SiftFeatureDetector
-------------------
.. ocv:class:: SiftFeatureDetector
@ -312,11 +271,6 @@ Wrapping class for feature detection using the
...
};
.. index:: SurfFeatureDetector
.. _SurfFeatureDetector:
SurfFeatureDetector
-------------------
.. ocv:class:: SurfFeatureDetector
@ -336,10 +290,6 @@ Wrapping class for feature detection using the
};
.. index:: OrbFeatureDetector
.. _OrbFeatureDetector:
OrbFeatureDetector
-------------------
.. ocv:class:: OrbFeatureDetector
@ -357,11 +307,6 @@ Wrapping class for feature detection using the
...
};
.. index:: SimpleBlobDetector
.. _SimpleBlobDetector:
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.
.. index:: GridAdaptedFeatureDetector
.. _GridAdaptedFeatureDetector:
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
-----------------------------
.. ocv:class:: PyramidAdaptedFeatureDetector
@ -472,11 +407,8 @@ Class adapting a detector to detect points over multiple levels of a Gaussian py
};
.. index:: DynamicAdaptedFeatureDetector
DynamicAdaptedFeatureDetector
-----------------------------
.. ocv:class:: DynamicAdaptedFeatureDetector
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,
new FastAdjuster(20,true)));
.. index:: DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector
DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector
----------------------------------------------------------------
.. 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.
.. index:: AdjusterAdapter
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. ::
@ -546,10 +471,12 @@ Class providing an interface for adjusting parameters of a feature detector. Thi
class AdjusterAdapter: public FeatureDetector
{
public:
virtual ~AdjusterAdapter() {}
virtual void tooFew(int min, int n_detected) = 0;
virtual void tooMany(int max, int n_detected) = 0;
virtual bool good() const = 0;
virtual ~AdjusterAdapter() {}
virtual void tooFew(int min, int n_detected) = 0;
virtual void tooMany(int max, int n_detected) = 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:`SurfAdjuster` for concrete implementations.
.. index:: AdjusterAdapter::tooFew
AdjusterAdapter::tooFew
---------------------------
.. ocv:function:: void AdjusterAdapter::tooFew(int min, int n_detected)
@ -578,9 +502,6 @@ Example: ::
thresh_--;
}
.. index:: AdjusterAdapter::tooMany
AdjusterAdapter::tooMany
----------------------------
.. ocv:function:: void AdjusterAdapter::tooMany(int max, int n_detected)
@ -599,8 +520,6 @@ Example: ::
}
.. index:: AdjusterAdapter::good
AdjusterAdapter::good
-------------------------
.. ocv:function:: bool AdjusterAdapter::good() const
@ -614,12 +533,14 @@ Example: ::
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
------------
.. ocv:class:: FastAdjuster
:ref:`AdjusterAdapter` for :ref:`FastFeatureDetector`. This class decreases or increases the threshold value by 1. ::
@ -631,11 +552,8 @@ FastAdjuster
...
};
.. index:: StarAdjuster
StarAdjuster
------------
.. ocv:class:: StarAdjuster
:ref:`AdjusterAdapter` for :ref:`StarFeatureDetector`. This class adjusts the ``responseThreshhold`` of ``StarFeatureDetector``. ::
@ -646,11 +564,8 @@ StarAdjuster
...
};
.. index:: SurfAdjuster
SurfAdjuster
------------
.. ocv:class:: SurfAdjuster
:ref:`AdjusterAdapter` for :ref:`SurfFeatureDetector`. This class adjusts the ``hessianThreshold`` of ``SurfFeatureDetector``. ::
@ -661,8 +576,6 @@ SurfAdjuster
...
};
.. index:: FeatureDetector
FeatureDetector
---------------
.. ocv:class:: FeatureDetector

22
modules/features2d/doc/object_categorization.rst
View File

@ -5,10 +5,6 @@ Object Categorization
This section describes approaches based on local 2D features and used to categorize objects.
.. index:: BOWTrainer
.. _BOWTrainer:
BOWTrainer
----------
.. ocv:class:: BOWTrainer
@ -36,9 +32,6 @@ Lixin Fan, Jutta Willamowski, Cedric Bray, 2004. ::
...
};
.. index:: BOWTrainer::add
BOWTrainer::add
-------------------
.. 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.
.. index:: BOWTrainer::getDescriptors
BOWTrainer::getDescriptors
------------------------------
@ -83,7 +75,8 @@ 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
{
@ -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
:ref:`kmeans` function
arguments.
.. index:: BOWImgDescriptorExtractor
.. _BOWImgDescriptorExtractor:
To understand constructor parameters, see :ref:`kmeans` function arguments.
BOWImgDescriptorExtractor
-------------------------