Documentation build warning fixes.

Invalid links and refences fixed.
SpaeseMat class documentation updated.

doc/tutorials/highgui/video-input-psnr-ssim/video-input-psnr-ssim.rst

@@ -16,7 +16,7 @@ Today it is common to have a digital video recording system at your disposal. Th
 The source code
 ===============
 
-As a test case where to show off these using OpenCV I've created a small program that reads in two video files and performs a similarity check between them. This is something you could use to check just how well a new video compressing algorithms works. Let there be a reference (original) video like :download:`this small Megamind clip <../../../../samples/cpp/tutorial_code/highgui/video-input-psnr-ssim/video/Megamind.avi>` and :download:`a compressed version of it <../../../../samples/cpp/tutorial_code/highgui/video-input-psnr-ssim/video/Megamind_bugy.avi>`. You may also find the source code and these video file in the :file:`samples/cpp/tutorial_code/highgui/video-input-psnr-ssim/` folder of the OpenCV source library.
+As a test case where to show off these using OpenCV I've created a small program that reads in two video files and performs a similarity check between them. This is something you could use to check just how well a new video compressing algorithms works. Let there be a reference (original) video like :download:`this small Megamind clip <../../../../samples/cpp/tutorial_code/HighGUI/video-input-psnr-ssim/video/Megamind.avi>` and :download:`a compressed version of it <../../../../samples/cpp/tutorial_code/HighGUI/video-input-psnr-ssim/video/Megamind_bugy.avi>`. You may also find the source code and these video file in the :file:`samples/cpp/tutorial_code/HighGUI/video-input-psnr-ssim/` folder of the OpenCV source library.
 
 .. literalinclude:: ../../../../samples/cpp/tutorial_code/HighGUI/video-input-psnr-ssim/video-input-psnr-ssim.cpp
    :language: cpp

modules/contrib/doc/retina/index.rst

@@ -208,7 +208,7 @@ Retina::getMagno
 Retina::getParameters
 +++++++++++++++++++++
 
-.. ocv:function:: struct Retina::RetinaParameters Retina::getParameters()
+.. ocv:function:: Retina::RetinaParameters Retina::getParameters()
 
     Retrieve the current parameters values in a *Retina::RetinaParameters* structure
 
@@ -325,7 +325,7 @@ Retina::RetinaParameters
 .. ocv:struct:: Retina::RetinaParameters
 
   This structure merges all the parameters that can be adjusted threw the **Retina::setup()**, **Retina::setupOPLandIPLParvoChannel** and **Retina::setupIPLMagnoChannel** setup methods
-Parameters structure for better clarity, check explenations on the comments of methods : setupOPLandIPLParvoChannel and setupIPLMagnoChannel. ::
+  Parameters structure for better clarity, check explenations on the comments of methods : setupOPLandIPLParvoChannel and setupIPLMagnoChannel. ::
 
     class RetinaParameters{
         struct OPLandIplParvoParameters{ // Outer Plexiform Layer (OPL) and Inner Plexiform Layer Parvocellular (IplParvo) parameters

modules/contrib/include/opencv2/contrib/retina.hpp

@@ -115,7 +115,7 @@ class CV_EXPORTS Retina {
 public:
 
     // parameters structure for better clarity, check explenations on the comments of methods : setupOPLandIPLParvoChannel and setupIPLMagnoChannel
-        struct RetinaParameters{
+    struct RetinaParameters{
         struct OPLandIplParvoParameters{ // Outer Plexiform Layer (OPL) and Inner Plexiform Layer Parvocellular (IplParvo) parameters
                OPLandIplParvoParameters():colorMode(true),
                                  normaliseOutput(true),
@@ -166,14 +166,14 @@ public:
     virtual ~Retina();
 
     /**
-        * retreive retina input buffer size
-        */
-        Size inputSize();
+    * retreive retina input buffer size
+    */
+    Size inputSize();
 
     /**
-        * retreive retina output buffer size
-        */
-        Size outputSize();
+    * retreive retina output buffer size
+    */
+    Size outputSize();
 
     /**
      * try to open an XML retina parameters file to adjust current retina instance setup
@@ -190,9 +190,9 @@ public:
      * => if the xml file does not exist, then default setup is applied
      * => warning, Exceptions are thrown if read XML file is not valid
      * @param fs : the open Filestorage which contains retina parameters
-         * @param applyDefaultSetupOnFailure : set to true if an error must be thrown on error
+     * @param applyDefaultSetupOnFailure : set to true if an error must be thrown on error
      */
-        void setup(cv::FileStorage &fs, const bool applyDefaultSetupOnFailure=true);
+    void setup(cv::FileStorage &fs, const bool applyDefaultSetupOnFailure=true);
 
     /**
      * try to open an XML retina parameters file to adjust current retina instance setup
@@ -206,7 +206,7 @@ public:
     /**
      * @return the current parameters setup
      */
-    struct Retina::RetinaParameters getParameters();
+    Retina::RetinaParameters getParameters();
 
     /**
      * parameters setup display method
@@ -305,17 +305,17 @@ public:
      */
     void clearBuffers();
 
-        /**
-        * Activate/desactivate the Magnocellular pathway processing (motion information extraction), by default, it is activated
-        * @param activate: true if Magnocellular output should be activated, false if not
-        */
-        void activateMovingContoursProcessing(const bool activate);
-
-        /**
-        * Activate/desactivate the Parvocellular pathway processing (contours information extraction), by default, it is activated
-        * @param activate: true if Parvocellular (contours information extraction) output should be activated, false if not
-        */
-        void activateContoursProcessing(const bool activate);
+    /**
+    * Activate/desactivate the Magnocellular pathway processing (motion information extraction), by default, it is activated
+    * @param activate: true if Magnocellular output should be activated, false if not
+    */
+    void activateMovingContoursProcessing(const bool activate);
+
+    /**
+    * Activate/desactivate the Parvocellular pathway processing (contours information extraction), by default, it is activated
+    * @param activate: true if Parvocellular (contours information extraction) output should be activated, false if not
+    */
+    void activateContoursProcessing(const bool activate);
 
 protected:
     // Parameteres setup members

modules/core/doc/dynamic_structures.rst

@@ -166,6 +166,12 @@ field of the set is the total number of nodes both occupied and free. When an oc
 
 ``CvSet`` is used to represent graphs (:ocv:struct:`CvGraph`), sparse multi-dimensional arrays (:ocv:struct:`CvSparseMat`), and planar subdivisions (:ocv:struct:`CvSubdiv2D`).
 
+CvSetElem
+---------
+
+.. ocv:struct:: CvSetElem
+
+The structure is represent single element of :ocv:struct:`CvSet`. It consists of two fields: element data pointer and flags.
 
 CvGraph
 -------
@@ -174,6 +180,24 @@ CvGraph
 The structure ``CvGraph`` is a base for graphs used in OpenCV 1.x. It inherits from
 :ocv:struct:`CvSet`, that is, it is considered as a set of vertices. Besides, it contains another set as a member, a set of graph edges. Graphs in OpenCV are represented using adjacency lists format.
 
+CvGraphVtx
+----------
+.. ocv:struct:: CvGraphVtx
+
+The structure represents single vertex in :ocv:struct:`CvGraph`. It consists of two filds: pointer to first edge and flags.
+
+CvGraphEdge
+-----------
+.. ocv:struct:: CvGraphEdge
+
+The structure represents edge in :ocv:struct:`CvGraph`.  Each edge consists of:
+
+- Two pointers to the starting and ending vertices (vtx[0] and vtx[1] respectively);
+- Two pointers to next edges for the starting and ending vertices, where
+  next[0] points to the next edge in the vtx[0] adjacency list and
+  next[1] points to the next edge in the vtx[1] adjacency list;
+- Weight;
+- Flags.
 
 CvGraphScanner
 --------------

modules/core/doc/operations_on_arrays.rst

@@ -3243,7 +3243,7 @@ The constructors.
 
         * **SVD::NO_UV** indicates that only a vector of singular values ``w`` is to be processed, while ``u`` and ``vt`` will be set to empty matrices.
 
-        * **SVD::FULL_UV** when the matrix is not square, by default the algorithm produces ``u`` and ``vt`` matrices of sufficiently large size for the further ``A`` reconstruction; if, however, ``FULL_UV`` flag is specified, ``u`` and ``vt``will be full-size square orthogonal matrices.
+        * **SVD::FULL_UV** when the matrix is not square, by default the algorithm produces ``u`` and ``vt`` matrices of sufficiently large size for the further ``A`` reconstruction; if, however,   ``FULL_UV`` flag is specified, ``u`` and ``vt`` will be full-size square orthogonal matrices.
 
 The first constructor initializes an empty ``SVD`` structure. The second constructor initializes an empty ``SVD`` structure and then calls
 :ocv:funcx:`SVD::operator()` .

modules/features2d/doc/common_interfaces_of_descriptor_extractors.rst

@@ -41,7 +41,7 @@ Abstract base class for computing descriptors for image keypoints. ::
 
 
 In this interface, a keypoint descriptor can be represented as a
-dense, fixed-dimension vector of a basic type. Most descriptors 
+dense, fixed-dimension vector of a basic type. Most descriptors
 follow this pattern as it simplifies computing
 distances between descriptors. Therefore, a collection of
 descriptors is represented as

modules/features2d/doc/common_interfaces_of_feature_detectors.rst

@@ -113,7 +113,7 @@ Detects keypoints in an image (first variant) or image set (second variant).
     :param masks: Masks for each input image specifying where to look for keypoints (optional). ``masks[i]`` is a mask for ``images[i]``.
 
 FeatureDetector::create
----------------------------
+-----------------------
 Creates a feature detector by its name.
 
 .. ocv:function:: Ptr<FeatureDetector> FeatureDetector::create( const string& detectorType )
@@ -219,8 +219,7 @@ StarFeatureDetector
 -------------------
 .. ocv:class:: StarFeatureDetector : public FeatureDetector
 
-Wrapping class for feature detection using the
-:ocv:class:`StarDetector` class. ::
+The class implements the keypoint detector introduced by K. Konolige, synonym of ``StarDetector``.  ::
 
     class StarFeatureDetector : public FeatureDetector
     {
@@ -412,7 +411,7 @@ Example of creating ``DynamicAdaptedFeatureDetector`` : ::
 
 
 DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector
-----------------------------------------------------------------
+------------------------------------------------------------
 The constructor
 
 .. ocv:function:: DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector( const Ptr<AdjusterAdapter>& adjuster, int min_features=400, int max_features=500, int max_iters=5 )
@@ -484,7 +483,7 @@ Example: ::
 
 
 AdjusterAdapter::good
--------------------------
+---------------------
 Returns false if the detector parameters cannot be adjusted any more.
 
 .. ocv:function:: bool AdjusterAdapter::good() const
@@ -497,7 +496,7 @@ Example: ::
         }
 
 AdjusterAdapter::create
--------------------------
+-----------------------
 Creates an adjuster adapter by name
 
 .. ocv:function:: Ptr<AdjusterAdapter> AdjusterAdapter::create( const string& detectorType )
@@ -528,3 +527,23 @@ StarAdjuster
                 StarAdjuster(double initial_thresh = 30.0);
                 ...
         };
+
+SurfAdjuster
+------------
+.. ocv:class:: SurfAdjuster: public AdjusterAdapter
+
+:ocv:class:`AdjusterAdapter` for ``SurfFeatureDetector``.  ::
+
+    class CV_EXPORTS SurfAdjuster: public AdjusterAdapter
+    {
+    public:
+        SurfAdjuster( double initial_thresh=400.f, double min_thresh=2, double max_thresh=1000 );
+
+        virtual void tooFew(int minv, int n_detected);
+        virtual void tooMany(int maxv, int n_detected);
+        virtual bool good() const;
+
+        virtual Ptr<AdjusterAdapter> clone() const;
+
+        ...
+    };

modules/flann/doc/flann_clustering.rst

@@ -10,11 +10,11 @@ Clusters features using hierarchical k-means algorithm.
 .. ocv:function:: template<typename Distance> int flann::hierarchicalClustering(const Mat& features, Mat& centers, const cvflann::KMeansIndexParams& params, Distance d = Distance())
 
     :param features: The points to be clustered. The matrix must have elements of type ``Distance::ElementType``.
-    
-    :param centers: The centers of the clusters obtained. The matrix must have type ``Distance::ResultType``. The number of rows in this matrix represents the number of clusters desired, however, because of the way the cut in the hierarchical tree is chosen, the number of clusters computed will be the highest number of the form  ``(branching-1)*k+1``  that's lower than the number of clusters desired, where  ``branching``  is the tree's branching factor (see description of the KMeansIndexParams). 
-    
+
+    :param centers: The centers of the clusters obtained. The matrix must have type ``Distance::ResultType``. The number of rows in this matrix represents the number of clusters desired, however, because of the way the cut in the hierarchical tree is chosen, the number of clusters computed will be the highest number of the form  ``(branching-1)*k+1``  that's lower than the number of clusters desired, where  ``branching``  is the tree's branching factor (see description of the KMeansIndexParams).
+
     :param params: Parameters used in the construction of the hierarchical k-means tree.
 
     :param d: Distance to be used for clustering.
-    
+
 The method clusters the given feature vectors by constructing a hierarchical k-means tree and choosing a cut in the tree that minimizes the cluster's variance. It returns the number of clusters found.

modules/gpu/doc/initalization_and_information.rst

@@ -6,7 +6,7 @@ Initalization and Information
 
 
 gpu::getCudaEnabledDeviceCount
-----------------------------------
+------------------------------
 Returns the number of installed CUDA-enabled devices.
 
 .. ocv:function:: int gpu::getCudaEnabledDeviceCount()
@@ -16,7 +16,7 @@ Use this function before any other GPU functions calls. If OpenCV is compiled wi
 
 
 gpu::setDevice
-------------------
+--------------
 Sets a device and initializes it for the current thread.
 
 .. ocv:function:: void gpu::setDevice(int device)
@@ -28,7 +28,7 @@ If the call of this function is omitted, a default device is initialized at the
 
 
 gpu::getDevice
-------------------
+--------------
 Returns the current device index set by :ocv:func:`gpu::setDevice` or initialized by default.
 
 .. ocv:function:: int gpu::getDevice()
@@ -36,7 +36,7 @@ Returns the current device index set by :ocv:func:`gpu::setDevice` or initialize
 
 
 gpu::resetDevice
-------------------
+----------------
 Explicitly destroys and cleans up all resources associated with the current device in the current process.
 
 .. ocv:function:: void gpu::resetDevice()
@@ -47,8 +47,7 @@ Any subsequent API call to this device will reinitialize the device.
 
 gpu::FeatureSet
 ---------------
-
-Class providing GPU computing features. ::
+Enumeration providing GPU computing features. ::
 
     enum FeatureSet
     {
@@ -64,7 +63,6 @@ Class providing GPU computing features. ::
     };
 
 
-
 gpu::TargetArchs
 ----------------
 .. ocv:class:: gpu::TargetArchs
@@ -132,7 +130,7 @@ Class providing functionality for querying the specified GPU properties. ::
 
 
 gpu::DeviceInfo::DeviceInfo
--------------------------------
+---------------------------
 The constructors.
 
 .. ocv:function:: gpu::DeviceInfo::DeviceInfo()
@@ -146,7 +144,7 @@ Constructs the ``DeviceInfo`` object for the specified device. If ``device_id``
 
 
 gpu::DeviceInfo::name
--------------------------
+---------------------
 Returns the device name.
 
 .. ocv:function:: string gpu::DeviceInfo::name() const
@@ -154,7 +152,7 @@ Returns the device name.
 
 
 gpu::DeviceInfo::majorVersion
----------------------------------
+-----------------------------
 Returns the major compute capability version.
 
 .. ocv:function:: int gpu::DeviceInfo::majorVersion()
@@ -162,7 +160,7 @@ Returns the major compute capability version.
 
 
 gpu::DeviceInfo::minorVersion
----------------------------------
+-----------------------------
 Returns the minor compute capability version.
 
 .. ocv:function:: int gpu::DeviceInfo::minorVersion()
@@ -170,7 +168,7 @@ Returns the minor compute capability version.
 
 
 gpu::DeviceInfo::multiProcessorCount
-----------------------------------------
+------------------------------------
 Returns the number of streaming multiprocessors.
 
 .. ocv:function:: int gpu::DeviceInfo::multiProcessorCount()
@@ -178,7 +176,7 @@ Returns the number of streaming multiprocessors.
 
 
 gpu::DeviceInfo::freeMemory
--------------------------------
+---------------------------
 Returns the amount of free memory in bytes.
 
 .. ocv:function:: size_t gpu::DeviceInfo::freeMemory()
@@ -186,7 +184,7 @@ Returns the amount of free memory in bytes.
 
 
 gpu::DeviceInfo::totalMemory
---------------------------------
+----------------------------
 Returns the amount of total memory in bytes.
 
 .. ocv:function:: size_t gpu::DeviceInfo::totalMemory()
@@ -194,7 +192,7 @@ Returns the amount of total memory in bytes.
 
 
 gpu::DeviceInfo::supports
------------------------------
+-------------------------
 Provides information on GPU feature support.
 
 .. ocv:function:: bool gpu::DeviceInfo::supports( FeatureSet feature_set ) const
@@ -206,7 +204,7 @@ This function returns ``true`` if the device has the specified GPU feature. Othe
 
 
 gpu::DeviceInfo::isCompatible
----------------------------------
+-----------------------------
 Checks the GPU module and device compatibility.
 
 .. ocv:function:: bool gpu::DeviceInfo::isCompatible()
@@ -216,7 +214,7 @@ This function returns ``true`` if the GPU module can be run on the specified dev
 
 
 gpu::DeviceInfo::deviceID
----------------------------------
+-------------------------
 Returns system index of the GPU device starting with 0.
 
 .. ocv:function:: int gpu::DeviceInfo::deviceID()

modules/gpu/doc/video.rst

@@ -785,7 +785,7 @@ Constructors.
 
     :param fps: Framerate of the created video stream.
 
-    :param params: Encoder parameters. See :ocv:class:`gpu::VideoWriter_GPU::EncoderParams` .
+    :param params: Encoder parameters. See :ocv:struct:`gpu::VideoWriter_GPU::EncoderParams` .
 
     :param format: Surface format of input frames ( ``SF_UYVY`` , ``SF_YUY2`` , ``SF_YV12`` , ``SF_NV12`` , ``SF_IYUV`` , ``SF_BGR`` or ``SF_GRAY``). BGR or gray frames will be converted to YV12 format before encoding, frames with other formats will be used as is.
 

modules/ml/doc/boosting.rst

@@ -124,7 +124,7 @@ CvBoostTree
 -----------
 .. ocv:class:: CvBoostTree : public CvDTree
 
-The weak tree classifier, a component of the boosted tree classifier :ocv:class:`CvBoost`, is a derivative of :ocv:class:`CvDTree`. Normally, there is no need to use the weak classifiers directly. However, they can be accessed as elements of the sequence :ocv:member:`CvBoost::weak`, retrieved by :ocv:func:`CvBoost::get_weak_predictors`.
+The weak tree classifier, a component of the boosted tree classifier :ocv:class:`CvBoost`, is a derivative of :ocv:class:`CvDTree`. Normally, there is no need to use the weak classifiers directly. However, they can be accessed as elements of the sequence ``CvBoost::weak``, retrieved by :ocv:func:`CvBoost::get_weak_predictors`.
 
 .. note:: In case of LogitBoost and Gentle AdaBoost, each weak predictor is a regression tree, rather than a classification tree. Even in case of Discrete AdaBoost and Real AdaBoost, the ``CvBoostTree::predict`` return value (:ocv:member:`CvDTreeNode::value`) is not an output class label. A negative value "votes" for class #0, a positive value - for class #1. The votes are weighted. The weight of each individual tree may be increased or decreased using the method ``CvBoostTree::scale``.
 
@@ -233,4 +233,3 @@ CvBoost::get_data
 Returns used train data of the boosted tree classifier.
 
 .. ocv:function:: const CvDTreeTrainData* CvBoost::get_data() const
-

modules/ml/doc/statistical_models.rst

@@ -156,7 +156,7 @@ CvStatModel::predict
 --------------------
 Predicts the response for a sample.
 
-.. ocv:function:: float CvStatModel::predict( const Mat& sample, <prediction_params> ) const
+.. ocv:function:: float CvStatModel::predict( const Mat& sample, ... ) const
 
 The method is used to predict the response for a new sample. In case of a classification, the method returns the class label. In case of a regression, the method returns the output function value. The input sample must have as many components as the ``train_data`` passed to ``train`` contains. If the ``var_idx`` parameter is passed to ``train``, it is remembered and then is used to extract only the necessary components from the input sample in the method ``predict``.
 

modules/ocl/doc/feature_detection_and_description.rst

@@ -148,7 +148,7 @@ Brute-force descriptor matcher. For each descriptor in the first set, this match
 
 The class ``BruteForceMatcher_OCL_base`` has an interface similar to the class :ocv:class:`DescriptorMatcher`. It has two groups of ``match`` methods: for matching descriptors of one image with another image or with an image set. Also, all functions have an alternative to save results either to the GPU memory or to the CPU memory. ``BruteForceMatcher_OCL_base`` supports only the ``L1<float>``, ``L2<float>``, and ``Hamming`` distance types.
 
-.. seealso:: :ocv:class:`DescriptorMatcher`, :ocv:class:`BruteForceMatcher`
+.. seealso:: :ocv:class:`DescriptorMatcher`, :ocv:class:`BFMatcher`
 
 
 

modules/ocl/doc/object_detection.rst

@@ -56,7 +56,7 @@ Class providing memory buffers for :ocv:func:`ocl::matchTemplate` function, plus
 You can use field `user_block_size` to set specific block size for :ocv:func:`ocl::matchTemplate` function. If you leave its default value `Size(0,0)` then automatic estimation of block size will be used (which is optimized for speed). By varying `user_block_size` you can reduce memory requirements at the cost of speed.
 
 ocl::matchTemplate
-----------------------
+------------------
 Computes a proximity map for a raster template and an image where the template is searched for.
 
 .. ocv:function:: void ocl::matchTemplate(const oclMat& image, const oclMat& templ, oclMat& result, int method)
@@ -71,7 +71,7 @@ Computes a proximity map for a raster template and an image where the template i
 
     :param method: Specifies the way to compare the template with the image.
 
-    :param buf: Optional buffer to avoid extra memory allocations and to adjust some specific parameters. See :ocv:class:`ocl::MatchTemplateBuf`.
+    :param buf: Optional buffer to avoid extra memory allocations and to adjust some specific parameters. See :ocv:struct:`ocl::MatchTemplateBuf`.
 
     The following methods are supported for the ``CV_8U`` depth images for now:
 

modules/stitching/doc/motion_estimation.rst

@@ -221,6 +221,7 @@ Implementation of the camera parameters refinement algorithm which minimizes sum
 
 detail::WaveCorrectKind
 -----------------------
+.. ocv:class:: detail::WaveCorrectKind
 
 Wave correction kind. ::
 

modules/video/doc/motion_analysis_and_object_tracking.rst

@@ -287,7 +287,7 @@ The function finds all of the motion segments and marks them in ``segmask`` with
 
 
 CamShift
-------------
+--------
 Finds an object center, size, and orientation.
 
 .. ocv:function:: RotatedRect CamShift( InputArray probImage, Rect& window, TermCriteria criteria )
@@ -316,7 +316,7 @@ See the OpenCV sample ``camshiftdemo.c`` that tracks colored objects.
 
 
 meanShift
--------------
+---------
 Finds an object on a back projection image.
 
 .. ocv:function:: int meanShift( InputArray probImage, Rect& window, TermCriteria criteria )