fixed several documentation errors

modules/contrib/doc/facerec.rst

@@ -13,7 +13,9 @@ All face recognition models in OpenCV are derived from the abstract base
 class :ocv:class:`FaceRecognizer`, which provides a unified access to all face
 recongition algorithms in OpenCV.
 
-.. ocv:class:: FaceRecognizer
+.. ocv:class:: FaceRecognizer : public Algorithm
+
+.. code-block:: cpp
 
   class FaceRecognizer : public Algorithm
   {
@@ -135,12 +137,12 @@ FaceRecognizer::load
 Loads a :ocv:class:`FaceRecognizer` and its model state.
 
 .. ocv:function:: void FaceRecognizer::load(const string& filename)
-.. ocv:function:: void FaceRecognizer::load(FileStorage& fs)
+.. ocv:function:: void FaceRecognizer::load(const FileStorage& fs)
 
 Loads a persisted model and state from a given XML or YAML file . Every
 :ocv:class:`FaceRecognizer` has overwrites ``FaceRecognizer::load(FileStorage& fs)``
 to enable loading the internal model state. ``FaceRecognizer::load(const string& filename)``
- eases saving a model, so you just need to call it on the filename.
+eases saving a model, so you just need to call it on the filename.
 
 createEigenFaceRecognizer
 -------------------------
@@ -151,13 +153,13 @@ Creates an Eigenfaces model with given number of components (if given) and thres
 
 This model implements the Eigenfaces method as described in [TP91]_.
 
-* ``num_components`` (default 0) number of components are kept for classification. If no number of 
-components is given, it is automatically determined from given data in 
-:ocv:func:`FaceRecognizer::train`. If (and only if) ``num_components`` <= 0, then 
-``num_components`` is set to (N-1) in ocv:func:`Eigenfaces::train`, with *N* being the 
-total number of samples in ``src``.
+ * ``num_components`` (default 0) number of components are kept for classification. If no number of
+   components is given, it is automatically determined from given data in
+   :ocv:func:`FaceRecognizer::train`. If (and only if) ``num_components`` <= 0, then
+   ``num_components`` is set to (N-1) in :ocv:func:`Eigenfaces::train`, with *N* being the
+   total number of samples in ``src``.
 
-* ``threshold`` (default DBL_MAX) 
+ * ``threshold`` (default DBL_MAX)
 
 Internal model data, which can be accessed through cv::Algorithm:
 
@@ -184,13 +186,13 @@ Creates a Fisherfaces model for given a given number of components and threshold
 
 This model implements the Fisherfaces method as described in [BHK97]_.
 
-* ``num_components`` number of components are kept for classification. If no number 
-of components is given (default 0), it is automatically determined from given data 
-in :ocv:func:`Fisherfaces::train` (model implementation). If (and only if) 
-``num_components`` <= 0, then ``num_components`` is set to (C-1) in 
-ocv:func:`train`, with *C* being the number of unique classes in ``labels``.
+ * ``num_components`` number of components are kept for classification. If no number
+   of components is given (default 0), it is automatically determined from given data
+   in :ocv:func:`Fisherfaces::train` (model implementation). If (and only if)
+   ``num_components`` <= 0, then ``num_components`` is set to (C-1) in
+   :ocv:func:`train`, with *C* being the number of unique classes in ``labels``.
 
-* ``threshold`` (default DBL_MAX) 
+ * ``threshold`` (default DBL_MAX)
 
 Internal model data, which can be accessed through cv::Algorithm:
 
@@ -213,7 +215,7 @@ createLBPHFaceRecognizer
 
 Implements face recognition with Local Binary Patterns Histograms as described in [Ahonen04]_.
 
-.. ocv:function:: Ptr<FaceRecognizer> createLBPHFaceRecognizer(int radius=1, int neighbors=8, int grid_x=8, int grid_y=8, double threshold = DBL_MAX);
+.. ocv:function:: Ptr<FaceRecognizer> createLBPHFaceRecognizer(int radius=1, int neighbors=8, int grid_x=8, int grid_y=8, double threshold = DBL_MAX)
 
 Internal model data, which can be accessed through cv::Algorithm:
 

modules/core/doc/dynamic_structures.rst

@@ -588,11 +588,11 @@ GetSetElem
 ----------
 Finds a set element by its index.
 
-.. ocv:cfunction:: CvSetElem* cvGetSetElem( const CvSet* set_header, int index )
+.. ocv:cfunction:: CvSetElem* cvGetSetElem( const CvSet* set_header, int idx )
 
     :param set_header: Set
 
-    :param index: Index of the set element within a sequence
+    :param idx: Index of the set element within a sequence
 
 The function finds a set element by its index. The function returns the pointer to it or 0 if the index is invalid or the corresponding node is free. The function supports negative indices as it uses
 :ocv:cfunc:`GetSeqElem`

modules/core/doc/xml_yaml_persistence.rst

@@ -199,7 +199,7 @@ FileStorage::release
 --------------------
 Closes the file and releases all the memory buffers.
 
-.. ocv:function:: string FileStorage::release()
+.. ocv:function:: void FileStorage::release()
 
 Call this method after all I/O operations with the storage are finished. If the storage was opened for writing data and ``FileStorage::WRITE`` was specified
 

modules/features2d/doc/feature_detection_and_description.rst

@@ -94,9 +94,9 @@ Finds keypoints in an image and computes their descriptors
 
     :param useProvidedKeypoints: If it is true, then the method will use the provided vector of keypoints instead of detecting them.
 
-    FREAK
+FREAK
 -----
-.. ocv:class:: FREAK
+.. ocv:class:: FREAK : public DescriptorExtractor
 
 Class implementing the FREAK (*Fast Retina Keypoint*) keypoint descriptor, described in [AOV12]_. The algorithm propose a novel keypoint descriptor inspired by the human visual system and more precisely the retina, coined Fast Retina Key- point (FREAK). A cascade of binary strings is computed by efficiently comparing image intensities over a retinal sampling pattern. FREAKs are in general faster to compute with lower memory load and also more robust than SIFT, SURF or BRISK. They are competitive alternatives to existing keypoints in particular for embedded applications.
 
@@ -106,12 +106,12 @@ FREAK::FREAK
 ------------
 The FREAK constructor
 
-.. ocv:function:: FREAK::FREAK(bool orientationNormalized = true, bool scaleNormalized = true, float patternScale = 22.0f, int nbOctave = 4, const vector<int>& selectedPairs = vector<int>())
+.. ocv:function:: FREAK::FREAK( bool orientationNormalized=true, bool scaleNormalized=true, float patternScale=22.0f, int nOctaves=4, const vector<int>& selectedPairs=vector<int>() )
 
     :param orientationNormalized: Enable orientation normalization.
     :param scaleNormalized: Enable scale normalization.
     :param patternScale: Scaling of the description pattern.
-    :param nbOctave: Number of octaves covered by the detected keypoints.
+    :param nOctaves: Number of octaves covered by the detected keypoints.
     :param selectedPairs: (Optional) user defined selected pairs indexes,
 
 FREAK::selectPairs
@@ -126,4 +126,3 @@ We notice that for keypoint matching applications, image content has little effe
     :param keypoints: Set of detected keypoints
     :param corrThresh: Correlation threshold.
     :param verbose: Prints pair selection informations.
-        
\ No newline at end of file

modules/gpu/doc/video.rst

@@ -324,9 +324,9 @@ Class used for background/foreground segmentation. ::
         std::vector< std::vector<cv::Point> > foreground_regions;
     };
 
-The class discriminates between foreground and background pixels by building and maintaining a model of the background. Any pixel which does not fit this model is then deemed to be foreground. The class implements algorithm described in [FGD2003]_.
+  The class discriminates between foreground and background pixels by building and maintaining a model of the background. Any pixel which does not fit this model is then deemed to be foreground. The class implements algorithm described in [FGD2003]_.
 
-The results are available through the class fields:
+  The results are available through the class fields:
 
     .. ocv:member:: cv::gpu::GpuMat background
 
@@ -383,7 +383,7 @@ gpu::FGDStatModel::update
 --------------------------
 Updates the background model and returns foreground regions count.
 
-.. ocv:function:: int gpu::FGDStatModel::update(const cv::gpu::GpuMat& curFrame);
+.. ocv:function:: int gpu::FGDStatModel::update(const cv::gpu::GpuMat& curFrame)
 
     :param curFrame: Next video frame.
 
@@ -615,7 +615,7 @@ Class for reading video from files.
 gpu::VideoReader_GPU::Codec
 ---------------------------
 
-Video codecs supported by ocv:class:`gpu::VideoReader_GPU` . ::
+Video codecs supported by :ocv:class:`gpu::VideoReader_GPU` . ::
 
     enum Codec
     {
@@ -640,7 +640,7 @@ Video codecs supported by ocv:class:`gpu::VideoReader_GPU` . ::
 gpu::VideoReader_GPU::ChromaFormat
 ----------------------------------
 
-Chroma formats supported by ocv:class:`gpu::VideoReader_GPU` . ::
+Chroma formats supported by :ocv:class:`gpu::VideoReader_GPU` . ::
 
     enum ChromaFormat
     {
@@ -783,7 +783,7 @@ Starts processing.
 
 .. ocv:function:: virtual void gpu::VideoReader_GPU::VideoSource::start() = 0
 
-Implementation must create own thread with video processing and call periodic ocv:func:`gpu::VideoReader_GPU::VideoSource::parseVideoData` .
+Implementation must create own thread with video processing and call periodic :ocv:func:`gpu::VideoReader_GPU::VideoSource::parseVideoData` .