Fixed bugs in facerec documentation

modules/contrib/doc/facerec/facerec_api.rst

@@ -46,7 +46,7 @@ I'll go a bit more into detail explaining :ocv:class:`FaceRecognizer`, because i
 
     * So called “virtual constructor”. That is, each Algorithm derivative is registered at program start and you can get the list of registered algorithms and create instance of a particular algorithm by its name (see :ocv:func:`Algorithm::create`). If you plan to add your own algorithms, it is good practice to add a unique prefix to your algorithms to distinguish them from other algorithms.
 
-    * Setting/Retrieving algorithm parameters by name. If you used video capturing functionality from OpenCV highgui module, you are probably familar with :ocv:cfunc:`cvSetCaptureProperty`, :ocv:cfunc:`cvGetCaptureProperty`, :ocv:func:`VideoCapture::set` and :ocv:func:`VideoCapture::get`. :ocv:class:`Algorithm` provides similar method where instead of integer id's you specify the parameter names as text strings. See :ocv:func:`Algorithm::set` and :ocv:func:`Algorithm::get for details.
+    * Setting/Retrieving algorithm parameters by name. If you used video capturing functionality from OpenCV highgui module, you are probably familar with :ocv:cfunc:`cvSetCaptureProperty`, :ocv:cfunc:`cvGetCaptureProperty`, :ocv:func:`VideoCapture::set` and :ocv:func:`VideoCapture::get`. :ocv:class:`Algorithm` provides similar method where instead of integer id's you specify the parameter names as text strings. See :ocv:func:`Algorithm::set` and :ocv:func:`Algorithm::get` for details.
 
     * Reading and writing parameters from/to XML or YAML files. Every Algorithm derivative can store all its parameters and then read them back. There is no need to re-implement it each time.
 
@@ -209,7 +209,7 @@ Saves a :ocv:class:`FaceRecognizer` and its model state.
 
 Every :ocv:class:`FaceRecognizer` overwrites ``FaceRecognizer::save(FileStorage& fs)``
 to save the internal model state. ``FaceRecognizer::save(const string& filename)`` saves
- the state of a model to the given filename.
+the state of a model to the given filename.
 
 The suffix ``const`` means that prediction does not affect the internal model
 state, so the method can be safely called from within different threads.
@@ -255,7 +255,7 @@ Model internal data:
     * ``labels`` The threshold applied in the prediction. If the distance to the nearest neighbor is larger than the threshold, this method returns -1.
 
 createFisherFaceRecognizer
--------------------------
+--------------------------
 
 .. ocv:function:: Ptr<FaceRecognizer> createFisherFaceRecognizer(int num_components = 0, double threshold = DBL_MAX)
 
@@ -284,7 +284,7 @@ Model internal data:
 createLBPHFaceRecognizer
 -------------------------
 
-.. 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)
 
     :param radius: The radius used for building the Circular Local Binary Pattern. The greater the radius, the
     :param neighbors: The number of sample points to build a Circular Local Binary Pattern from. An appropriate value is to use `` 8`` sample points. Keep in mind: the more sample points you include, the higher the computational cost.

modules/contrib/doc/facerec/tutorial/facerec_save_load.rst

@@ -11,7 +11,7 @@ The task of saving and loading a FaceRecognizer is easy with :ocv:class:`FaceRec
 call :ocv:func:`FaceRecognizer::load` for loading and :ocv:func:`FaceRecognizer::save` for saving a
 :ocv:class:`FaceRecognizer`.
 
-I'll adapt the Eigenfaces example from the :doc:`/facerec_tutorial`: Imagine we want to learn the Eigenfaces
+I'll adapt the Eigenfaces example from the :doc:`../facerec_tutorial`: Imagine we want to learn the Eigenfaces
  of the `AT&T Facedatabase <http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html>`_ store the
  model to a YAML file and then load it again.
 

modules/contrib/doc/facerec/tutorial/facerec_video_recognition.rst

@@ -24,7 +24,7 @@ I encourage you to experiment with the application. Play around with the availab
 Prerequisites
 --------------
 
-You want to do face recognition, so you need some face images to learn a :ocv:class:`FaceRecognizer` on. I have decided to reuse the images from the gender classification example: :doc:`../facerec_gender_classification`.
+You want to do face recognition, so you need some face images to learn a :ocv:class:`FaceRecognizer` on. I have decided to reuse the images from the gender classification example: :doc:`facerec_gender_classification`.
 
 I have the following celebrities in my training data set: