fixed #1140 and made some other updates of features2d docs

doc/check_docs_whitelist.txt

@@ -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)

modules/features2d/doc/common_interfaces_of_descriptor_extractors.rst

@@ -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.
 

modules/features2d/doc/common_interfaces_of_feature_detectors.rst

@@ -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. ::
@@ -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 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

modules/features2d/doc/object_categorization.rst

@@ -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
+    To understand constructor parameters, see :ref:`kmeans` function arguments.
-:ref:`kmeans` function
-arguments.
-
-.. index:: BOWImgDescriptorExtractor
-
-.. _BOWImgDescriptorExtractor:
 
 BOWImgDescriptorExtractor
 -------------------------