Merged the trunk r8467:8507 (inclusive) (big bunch of documentation fixes)

doc/conf.py

@@ -231,9 +231,9 @@ latex_documents = [
   ('modules/refman', 'opencv2refman.tex', u'The OpenCV Reference Manual',
    u'', 'manual'),
   ('doc/user_guide/user_guide', 'opencv_user.tex', u'The OpenCV User Guide',
-   u'', 'manual'), 
+   u'', 'manual'),
   ('doc/tutorials/tutorials', 'opencv_tutorials.tex', u'The OpenCV Tutorials',
-   u'', 'manual'), 
+   u'', 'manual'),
 ]
 
 preamble ="""
@@ -303,7 +303,7 @@ extlinks = {
             'calib3d' : ('http://opencv.itseez.com/trunk/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html#%s', None ),
             'feature2d' : ('http://opencv.itseez.com/trunk/modules/imgproc/doc/feature_detection.html#%s', None ),
             'imgproc_geometric' : ('http://opencv.itseez.com/trunk/modules/imgproc/doc/geometric_transformations.html#%s', None ),
-            
+
             'opencv_group' : ('http://tech.groups.yahoo.com/group/OpenCV/%s', None),
 
             'cvt_color': ('http://opencv.itseez.com/modules/imgproc/doc/miscellaneous_transformations.html?highlight=cvtcolor#cvtcolor%s', None),

modules/androidcamera/camera_wrapper/camera_wrapper.cpp

@@ -199,7 +199,7 @@ protected:
     int is_supported(const char* supp_modes_key, const char* mode)
     {
         const char* supported_modes = params.get(supp_modes_key);
-        return strstr(supported_modes, mode) > 0;
+        return (supported_modes && mode && (strstr(supported_modes, mode) > 0));
     }
 
     float getFocusDistance(int focus_distance_type)

modules/contrib/doc/contrib.rst

@@ -3,3 +3,8 @@ contrib. Contributed/Experimental Stuff
 ***************************************
 
 The module contains some recently added functionality that has not been stabilized, or functionality that is considered optional.
+
+.. toctree::
+    :maxdepth: 2
+
+    stereo
\ No newline at end of file

modules/contrib/doc/stereo.rst

+Stereo Correspondence
+========================================
+
+.. highlight:: cpp
+
+StereoVar
+----------
+
+.. ocv:class:: StereoVar
+
+Class for computing stereo correspondence using the variational matching algorithm ::
+
+    class StereoVar
+    {
+        StereoVar();
+        StereoVar(    int levels, double pyrScale,
+                                        int nIt, int minDisp, int maxDisp,
+                                        int poly_n, double poly_sigma, float fi,
+                                        float lambda, int penalization, int cycle,
+                                        int flags);
+        virtual ~StereoVar();
+
+        virtual void operator()(InputArray left, InputArray right, OutputArray disp);
+
+        int        levels;
+        double    pyrScale;
+        int        nIt;
+        int        minDisp;
+        int        maxDisp;
+        int        poly_n;
+        double    poly_sigma;
+        float    fi;
+        float    lambda;
+        int        penalization;
+        int        cycle;
+        int        flags;
+
+        ...
+    };
+
+The class implements the modified S. G. Kosov algorithm [Publication] that differs from the original one as follows:
+
+ * The automatic initialization of method's parameters is added.
+
+ * The method of Smart Iteration Distribution (SID) is implemented.
+
+ * The support of Multi-Level Adaptation Technique (MLAT) is not included.
+
+ * The method of dynamic adaptation of method's parameters is not included.
+
+StereoVar::StereoVar
+--------------------------
+
+.. ocv:function:: StereoVar::StereoVar()
+
+.. ocv:function:: StereoVar::StereoVar( int levels, double pyrScale, int nIt, int minDisp, int maxDisp, int poly_n, double poly_sigma, float fi, float lambda, int penalization, int cycle, int flags )
+
+    The constructor
+
+    :param levels: The number of pyramid layers, including the initial image. levels=1 means that no extra layers are created and only the original images are used. This parameter is ignored if flag USE_AUTO_PARAMS is set.
+
+    :param pyrScale: Specifies the image scale (<1) to build the pyramids for each image. pyrScale=0.5 means the classical pyramid, where each next layer is twice smaller than the previous. (This parameter is ignored if flag USE_AUTO_PARAMS is set).
+
+    :param nIt: The number of iterations the algorithm does at each pyramid level. (If the flag USE_SMART_ID is set, the number of iterations will be redistributed in such a way, that more iterations will be done on more coarser levels.)
+
+    :param minDisp: Minimum possible disparity value. Could be negative in case the left and right input images change places.
+
+    :param maxDisp: Maximum possible disparity value.
+
+    :param poly_n: Size of the pixel neighbourhood used to find polynomial expansion in each pixel. The larger values mean that the image will be approximated with smoother surfaces, yielding more robust algorithm and more blurred motion field. Typically, poly_n = 3, 5 or 7
+
+    :param poly_sigma: Standard deviation of the Gaussian that is used to smooth derivatives that are used as a basis for the polynomial expansion. For poly_n=5 you can set poly_sigma=1.1 , for poly_n=7 a good value would be poly_sigma=1.5
+
+    :param fi: The smoothness parameter, ot the weight coefficient for the smoothness term.
+
+    :param lambda: The threshold parameter for edge-preserving smoothness. (This parameter is ignored if PENALIZATION_CHARBONNIER or PENALIZATION_PERONA_MALIK is used.)
+
+    :param penalization: Possible values: PENALIZATION_TICHONOV - linear smoothness; PENALIZATION_CHARBONNIER - non-linear edge preserving smoothness; PENALIZATION_PERONA_MALIK - non-linear edge-enhancing smoothness. (This parameter is ignored if flag USE_AUTO_PARAMS is set).
+
+    :param cycle: Type of the multigrid cycle. Possible values: CYCLE_O and CYCLE_V for null- and v-cycles respectively. (This parameter is ignored if flag USE_AUTO_PARAMS is set).
+
+    :param flags: The operation flags; can be a combination of the following:
+
+        * USE_INITIAL_DISPARITY: Use the input flow as the initial flow approximation.
+
+        * USE_EQUALIZE_HIST: Use the histogram equalization in the pre-processing phase.
+
+        * USE_SMART_ID: Use the smart iteration distribution (SID).
+
+        * USE_AUTO_PARAMS: Allow the method to initialize the main parameters.
+
+        * USE_MEDIAN_FILTERING: Use the median filer of the solution in the post processing phase.
+
+The first constructor initializes ``StereoVar`` with all the default parameters. So, you only have to set ``StereoVar::maxDisp`` and / or ``StereoVar::minDisp`` at minimum. The second constructor enables you to set each parameter to a custom value.
+
+
+
+StereoVar::operator ()
+-----------------------
+
+.. ocv:function:: void StereoVar::operator()( const Mat& left, const Mat& right, Mat& disp )
+
+    Computes disparity using the variational algorithm for a rectified stereo pair.
+
+    :param left: Left 8-bit single-channel or 3-channel image.
+
+    :param right: Right image of the same size and the same type as the left one.
+
+    :param disp: Output disparity map. It is a 8-bit signed single-channel image of the same size as the input image.
+
+The method executes the variational algorithm on a rectified stereo pair. See ``stereo_match.cpp`` OpenCV sample on how to prepare images and call the method.
+
+**Note**:
+
+The method is not constant, so you should not use the same ``StereoVar`` instance from different threads simultaneously.
+
+

modules/core/doc/clustering.rst

@@ -7,17 +7,17 @@ kmeans
 ------
 Finds centers of clusters and groups input samples around the clusters.
 
-.. ocv:function:: double kmeans( InputArray samples, int clusterCount, InputOutputArray labels, TermCriteria criteria, int attempts, int flags, OutputArray centers=noArray() )
+.. ocv:function:: double kmeans( InputArray data, int K, InputOutputArray bestLabels, TermCriteria criteria, int attempts, int flags, OutputArray centers=noArray() )
 
 .. ocv:pyfunction:: cv2.kmeans(data, K, criteria, attempts, flags[, bestLabels[, centers]]) -> retval, bestLabels, centers
 
-.. ocv:cfunction:: int cvKMeans2(const CvArr* samples, int clusterCount, CvArr* labels, CvTermCriteria criteria, int attempts=1, CvRNG* rng=0, int flags=0, CvArr* centers=0, double* compactness=0)
+.. ocv:cfunction:: int cvKMeans2( const CvArr* samples, int cluster_count, CvArr* labels, CvTermCriteria termcrit, int attempts=1, CvRNG* rng=0, int flags=0, CvArr* _centers=0, double* compactness=0 )
 
-.. ocv:pyoldfunction:: cv.KMeans2(samples, clusterCount, labels, criteria)-> None
+.. ocv:pyoldfunction:: cv.KMeans2(samples, nclusters, labels, termcrit, attempts=1, flags=0, centers=None) -> float
 
     :param samples: Floating-point matrix of input samples, one row per sample.
 
-    :param clusterCount: Number of clusters to split the set by.
+    :param cluster_count: Number of clusters to split the set by.
 
     :param labels: Input/output integer array that stores the cluster indices for every sample.
 
@@ -40,7 +40,7 @@ Finds centers of clusters and groups input samples around the clusters.
     :param compactness: The returned value that is described below.
 
 The function ``kmeans`` implements a k-means algorithm that finds the
-centers of ``clusterCount`` clusters and groups the input samples
+centers of ``cluster_count`` clusters and groups the input samples
 around the clusters. As an output,
 :math:`\texttt{labels}_i` contains a 0-based cluster index for
 the sample stored in the

modules/core/doc/utility_and_system_functions_and_macros.rst

@@ -93,9 +93,9 @@ Computes the cube root of an argument.
 
 .. ocv:pyfunction:: cv2.cubeRoot(val) -> retval
 
-.. ocv:cfunction:: float cvCbrt(float val)
+.. ocv:cfunction:: float cvCbrt( float value )
 
-.. ocv:pyoldfunction:: cv.Cbrt(val)-> float
+.. ocv:pyoldfunction:: cv.Cbrt(value)-> float
 
     :param val: A function argument.
 
@@ -151,7 +151,7 @@ Determines if the argument is Infinity.
 .. ocv:cfunction:: int cvIsInf(double value)
 .. ocv:pyoldfunction:: cv.IsInf(value)-> int
 
-        :param value: The input floating-point value 
+        :param value: The input floating-point value
 
 The function returns 1 if the argument is a plus or minus infinity (as defined by IEEE754 standard) and 0 otherwise.
 
@@ -162,7 +162,7 @@ Determines if the argument is Not A Number.
 .. ocv:cfunction:: int cvIsNaN(double value)
 .. ocv:pyoldfunction:: cv.IsNaN(value)-> int
 
-        :param value: The input floating-point value 
+        :param value: The input floating-point value
 
 The function returns 1 if the argument is Not A Number (as defined by IEEE754 standard), 0 otherwise.
 
@@ -182,12 +182,12 @@ Signals an error and raises an exception.
 
 .. ocv:function:: void error( const Exception& exc )
 
-.. ocv:cfunction:: int cvError( int status, const char* funcName, const char* err_msg, const char* filename, int line )
+.. ocv:cfunction:: void cvError( int status, const char* func_name, const char* err_msg, const char* file_name, int line )
 
     :param exc: Exception to throw.
 
-    :param status: Error code. Normally, it is a negative value. The list of pre-defined error codes can be found in  ``cxerror.h`` .   
-    
+    :param status: Error code. Normally, it is a negative value. The list of pre-defined error codes can be found in  ``cxerror.h`` .
+
     :param err_msg: Text of the error message.
 
     :param args: ``printf`` -like formatted error message in parentheses.
@@ -209,7 +209,7 @@ The macro ``CV_Error_`` can be used to construct an error message on-fly to incl
 
 Exception
 ---------
-.. ocv:class:: Exception
+.. ocv:class:: Exception : public std::exception
 
 Exception class passed to an error. ::
 
@@ -244,7 +244,8 @@ fastMalloc
 --------------
 Allocates an aligned memory buffer.
 
-.. ocv:function:: void* fastMalloc(size_t size)
+.. ocv:function:: void* fastMalloc( size_t bufSize )
+
 .. ocv:cfunction:: void* cvAlloc( size_t size )
 
     :param size: Allocated buffer size.
@@ -261,7 +262,7 @@ Deallocates a memory buffer.
 .. ocv:cfunction:: void cvFree( void** pptr )
 
     :param ptr: Pointer to the allocated buffer.
-    
+
     :param pptr: Double pointer to the allocated buffer
 
 The function deallocates the buffer allocated with :ocv:func:`fastMalloc` . If NULL pointer is passed, the function does nothing. C version of the function clears the pointer ``*pptr`` to avoid problems with double memory deallocation.
@@ -276,7 +277,7 @@ Returns a text string formatted using the ``printf``\ -like expression.
     :param fmt: ``printf`` -compatible formatting specifiers.
 
 The function acts like ``sprintf``  but forms and returns an STL string. It can be used to form an error message in the
-:ocv:func:`Exception` constructor.
+:ocv:class:`Exception` constructor.
 
 
 
@@ -286,10 +287,10 @@ Returns true if the specified feature is supported by the host hardware.
 
 .. ocv:function:: bool checkHardwareSupport(int feature)
 .. ocv:cfunction:: int cvCheckHardwareSupport(int feature)
-.. ocv:pyfunction:: checkHardwareSupport(feature) -> Bool
+.. ocv:pyfunction:: cv2.checkHardwareSupport(feature) -> retval
 
     :param feature: The feature of interest, one of:
-    
+
                         * ``CV_CPU_MMX`` - MMX
                         * ``CV_CPU_SSE`` - SSE
                         * ``CV_CPU_SSE2`` - SSE 2
@@ -312,7 +313,7 @@ The function returns the number of threads that is used by OpenCV.
 
 .. seealso::
    :ocv:func:`setNumThreads`,
-   :ocv:func:`getThreadNum` 
+   :ocv:func:`getThreadNum`
 
 
 
@@ -411,7 +412,7 @@ The function sets the number of threads used by OpenCV in parallel OpenMP region
 
 .. seealso::
    :ocv:func:`getNumThreads`,
-   :ocv:func:`getThreadNum` 
+   :ocv:func:`getThreadNum`
 
 
 
@@ -419,13 +420,13 @@ setUseOptimized
 -----------------
 Enables or disables the optimized code.
 
-.. ocv:function:: void setUseOptimized(bool onoff)
+.. ocv:function:: int cvUseOptimized( int on_off )
 
 .. ocv:pyfunction:: cv2.setUseOptimized(onoff) -> None
 
-.. ocv:cfunction:: int cvUseOptimized( int onoff )
+.. ocv:cfunction:: int cvUseOptimized( int on_off )
 
-    :param onoff: The boolean flag specifying whether the optimized code should be used (``onoff=true``) or not (``onoff=false``).
+    :param on_off: The boolean flag specifying whether the optimized code should be used (``on_off=true``) or not (``on_off=false``).
 
 The function can be used to dynamically turn on and off optimized code (code that uses SSE2, AVX, and other instructions on the platforms that support it). It sets a global flag that is further checked by OpenCV functions. Since the flag is not checked in the inner OpenCV loops, it is only safe to call the function on the very top level in your application where you can be sure that no other OpenCV function is currently executed.
 

modules/core/doc/xml_yaml_persistence.rst

@@ -18,9 +18,9 @@ Here is an example: ::
 
     #include "opencv2/opencv.hpp"
     #include <time.h>
-    
+
     using namespace cv;
-    
+
     int main(int, char** argv)
     {
         FileStorage fs("test.yml", FileStorage::WRITE);
@@ -76,18 +76,18 @@ As an exercise, you can replace ".yml" with ".xml" in the sample above and see,
 Several things can be noted by looking at the sample code and the output:
  *
    The produced YAML (and XML) consists of heterogeneous collections that can be nested. There are 2 types of collections: named collections (mappings) and unnamed collections (sequences). In mappings each element has a name and is accessed by name. This is similar to structures and ``std::map`` in C/C++ and dictionaries in Python. In sequences elements do not have names, they are accessed by indices. This is similar to arrays and ``std::vector`` in C/C++ and lists, tuples in Python. "Heterogeneous" means that elements of each single collection can have different types.
- 
+
    Top-level collection in YAML/XML is a mapping. Each matrix is stored as a mapping, and the matrix elements are stored as a sequence. Then, there is a sequence of features, where each feature is represented a mapping, and lbp value in a nested sequence.
-   
+
  *
    When you write to a mapping (a structure), you write element name followed by its value. When you write to a sequence, you simply write the elements one by one. OpenCV data structures (such as cv::Mat) are written in absolutely the same way as simple C data structures - using **``<<``** operator.
-   
+
  *
    To write a mapping, you first write the special string **"{"** to the storage, then write the elements as pairs (``fs << <element_name> << <element_value>``) and then write the closing **"}"**.
-   
+
  *
    To write a sequence, you first write the special string **"["**, then write the elements, then write the closing **"]"**.
- 
+
  *
    In YAML (but not XML), mappings and sequences can be written in a compact Python-like inline form. In the sample above matrix elements, as well as each feature, including its lbp value, is stored in such inline form. To store a mapping/sequence in a compact form, put ":" after the opening character, e.g. use **"{:"** instead of **"{"** and **"[:"** instead of **"["**. When the data is written to XML, those extra ":" are ignored.
 
@@ -99,38 +99,38 @@ To read the previously written XML or YAML file, do the following:
 
  #.
    Open the file storage using :ocv:func:`FileStorage::FileStorage` constructor or :ocv:func:`FileStorage::open` method. In the current implementation the whole file is parsed and the whole representation of file storage is built in memory as a hierarchy of file nodes (see :ocv:class:`FileNode`)
-   
+
  #.
    Read the data you are interested in. Use :ocv:func:`FileStorage::operator []`, :ocv:func:`FileNode::operator []` and/or :ocv:class:`FileNodeIterator`.
-   
+
  #.
-   Close the storage using :ocv:func:`FileStorage::release`.  
-     
+   Close the storage using :ocv:func:`FileStorage::release`.
+
 Here is how to read the file created by the code sample above: ::
 
     FileStorage fs2("test.yml", FileStorage::READ);
-    
+
     // first method: use (type) operator on FileNode.
     int frameCount = (int)fs2["frameCount"];
-    
+
     std::string date;
     // second method: use FileNode::operator >>
     fs2["calibrationDate"] >> date;
-    
+
     Mat cameraMatrix2, distCoeffs2;
     fs2["cameraMatrix"] >> cameraMatrix2;
     fs2["distCoeffs"] >> distCoeffs2;
-    
+
     cout << "frameCount: " << frameCount << endl
          << "calibration date: " << date << endl
          << "camera matrix: " << cameraMatrix2 << endl
          << "distortion coeffs: " << distCoeffs2 << endl;
-    
+
     FileNode features = fs2["features"];
     FileNodeIterator it = features.begin(), it_end = features.end();
     int idx = 0;
     std::vector<uchar> lbpval;
-    
+
     // iterate through a sequence using FileNodeIterator
     for( ; it != it_end; ++it, idx++ )
     {
@@ -189,7 +189,7 @@ Checks whether the file is opened.
 .. ocv:function:: bool FileStorage::isOpened() const
 
     :returns: ``true`` if the object is associated with the current file and ``false`` otherwise.
-   
+
 It is a good practice to call this method after you tried to open a file.
 
 
@@ -254,22 +254,22 @@ Writes multiple numbers.
 
      :param fmt: Specification of each array element that has the following format  ``([count]{'u'|'c'|'w'|'s'|'i'|'f'|'d'})...`` where the characters correspond to fundamental C++ types:
 
-            * **u** 8-bit unsigned number 
+            * **u** 8-bit unsigned number
+
+            * **c** 8-bit signed number
 
-            * **c** 8-bit signed number 
+            * **w** 16-bit unsigned number
 
-            * **w** 16-bit unsigned number 
+            * **s** 16-bit signed number
 
-            * **s** 16-bit signed number 
+            * **i** 32-bit signed number
 
-            * **i** 32-bit signed number 
+            * **f** single precision floating-point number
 
-            * **f** single precision floating-point number 
+            * **d** double precision floating-point number
 
-            * **d** double precision floating-point number 
+            * **r** pointer, 32 lower bits of which are written as a signed integer. The type can be used to store structures with links between the elements.
 
-            * **r** pointer, 32 lower bits of which are written as a signed integer. The type can be used to store structures with links between the elements. 
-            
             ``count``  is the optional counter of values of a given type. For example,  ``2if``  means that each array element is a structure of 2 integers, followed by a single-precision floating-point number. The equivalent notations of the above specification are ' ``iif`` ', ' ``2i1f`` ' and so forth. Other examples:  ``u``  means that the array consists of bytes, and  ``2d``  means the array consists of pairs  of doubles.
 
      :param vec: Pointer to the written array.
@@ -431,7 +431,7 @@ Checks whether the node is empty.
 
 FileNode::isNone
 ----------------
-Checks whether the node is a "none" object 
+Checks whether the node is a "none" object
 
 .. ocv:function:: bool FileNode::isNone() const
 
@@ -459,7 +459,7 @@ Checks whether the node is a mapping.
 FileNode::isInt
 ---------------
 Checks whether the node is an integer.
-    
+
 .. ocv:function:: bool FileNode::isInt() const
 
     :returns: ``true`` if the node is an integer.
@@ -544,7 +544,7 @@ Returns the node content as text string.
 .. ocv:function:: FileNode::operator string() const
 
     :returns: The node content as a text string.
-        
+
 
 FileNode::operator*
 -------------------
@@ -663,7 +663,7 @@ FileNodeIterator::operator +=
 -----------------------------
 Moves iterator forward by the specified offset.
 
-.. ocv:function:: FileNodeIterator& FileNodeIterator::operator += (int ofs)
+.. ocv:function:: FileNodeIterator& FileNodeIterator::operator +=( int ofs )
 
     :param ofs: Offset (possibly negative) to move the iterator.
 
@@ -672,7 +672,7 @@ FileNodeIterator::operator -=
 -----------------------------
 Moves iterator backward by the specified offset (possibly negative).
 
-.. ocv:function:: FileNodeIterator& FileNodeIterator::operator -= (int ofs)
+.. ocv:function:: FileNodeIterator& FileNodeIterator::operator -=( int ofs )
 
     :param ofs: Offset (possibly negative) to move the iterator.
 

modules/core/include/opencv2/core/types_c.h

@@ -1130,7 +1130,7 @@ CV_INLINE  CvPoint3D64f  cvPoint3D64f( double x, double y, double z )
 
 /******************************** CvSize's & CvBox **************************************/
 
-typedef struct
+typedef struct CvSize
 {
     int width;
     int height;

modules/features2d/doc/common_interfaces_of_descriptor_extractors.rst

@@ -13,7 +13,7 @@ descriptor extractors inherit the
 
 DescriptorExtractor
 -------------------
-.. ocv:class:: DescriptorExtractor
+.. ocv:class:: DescriptorExtractor : public Algorithm
 
 Abstract base class for computing descriptors for image keypoints. ::
 
@@ -65,25 +65,6 @@ Computes the descriptors for a set of keypoints detected in an image (first vari
 
     :param descriptors: Computed descriptors. In the second variant of the method ``descriptors[i]`` are descriptors computed for a ``keypoints[i]`. Row ``j`` is the ``keypoints`` (or ``keypoints[i]``) is the descriptor for keypoint ``j``-th keypoint.
 
-DescriptorExtractor::read
------------------------------
-Reads the object of a descriptor extractor from a file node.
-
-.. ocv:function:: void DescriptorExtractor::read( const FileNode& fn )
-
-    :param fn: File node from which the detector is read.
-
-
-
-DescriptorExtractor::write
-------------------------------
-Writes the object of a descriptor extractor to a file storage.
-
-.. ocv:function:: void DescriptorExtractor::write( FileStorage& fs ) const
-
-    :param fs: File storage where the detector is written.
-
-
 
 DescriptorExtractor::create
 -------------------------------
@@ -107,7 +88,7 @@ for example: ``"OpponentSIFT"`` .
 
 OpponentColorDescriptorExtractor
 --------------------------------
-.. ocv:class:: OpponentColorDescriptorExtractor
+.. ocv:class:: OpponentColorDescriptorExtractor : public DescriptorExtractor
 
 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*).
@@ -132,7 +113,7 @@ them into a single color descriptor. ::
 
 BriefDescriptorExtractor
 ------------------------
-.. ocv:class:: BriefDescriptorExtractor
+.. ocv:class:: BriefDescriptorExtractor : public DescriptorExtractor
 
 Class for computing BRIEF descriptors described in a paper of Calonder M., Lepetit V.,
 Strecha C., Fua P. *BRIEF: Binary Robust Independent Elementary Features* ,

modules/features2d/doc/object_categorization.rst

@@ -54,7 +54,7 @@ BOWTrainer::descripotorsCount
 ---------------------------------
 Returns the count of all descriptors stored in the training set.
 
-.. ocv:function:: const vector<Mat>& BOWTrainer::descripotorsCount() const
+.. ocv:function:: int BOWTrainer::descripotorsCount() const
 
 
 
@@ -72,7 +72,7 @@ The vocabulary consists of cluster centers. So, this method returns the vocabula
 
 BOWKMeansTrainer
 ----------------
-.. ocv:class:: BOWKMeansTrainer
+.. ocv:class:: BOWKMeansTrainer : public BOWTrainer
 
 :ocv:func:`kmeans` -based class to train visual vocabulary using the *bag of visual words* approach.
 ::

modules/gpu/doc/camera_calibration_and_3d_reconstruction.rst

@@ -289,7 +289,7 @@ Enables the :ocv:class:`gpu::StereoConstantSpaceBP` constructors.
 
 .. ocv:function:: gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int ndisp = DEFAULT_NDISP, int iters = DEFAULT_ITERS, int levels = DEFAULT_LEVELS, int nr_plane = DEFAULT_NR_PLANE, int msg_type = CV_32F)
 
-.. ocv:function:: StereoConstantSpaceBP::StereoConstantSpaceBP(int ndisp, int iters, int levels, int nr_plane, float max_data_term, float data_weight, float max_disc_term, float disc_single_jump, int min_disp_th = 0, int msg_type = CV_32F)
+.. ocv:function:: gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int ndisp, int iters, int levels, int nr_plane, float max_data_term, float data_weight, float max_disc_term, float disc_single_jump, int min_disp_th = 0, int msg_type = CV_32F)
 
     :param ndisp: Number of disparities.
 

modules/legacy/doc/legacy.rst

@@ -9,6 +9,7 @@ legacy. Deprecated stuff
 
     motion_analysis
     expectation_maximization
+    histograms
     planar_subdivisions
     feature_detection_and_description
     common_interfaces_of_descriptor_extractors