Fixed several mistakes in documentation

doc/check_docs2.py

@@ -312,7 +312,7 @@ def process_module(module, path):
             if namespace:
                 name = name[len(namespace) + 1:]
         #print namespace, parent, name, fn[0]
-        if not namespace and not parent and not name.startswith("cv") and not name.startswith("CV_"):
+        if not namespace and not parent and not name.startswith("cv") and not name.startswith("icv") and not name.startswith("CV_"):
             logerror(ERROR_004_MISSEDNAMESPACE, "function " + name + " from opencv_" + module + " is placed in global namespace but violates C-style naming convention")
         else:
             fdescr = (namespace, parent, name, fn)

modules/contrib/doc/facerec/colormaps.rst

@@ -7,7 +7,7 @@ applyColorMap
 Trains a FaceRecognizer with given data and associated labels.
 
 .. ocv:function:: void applyColorMap(InputArray src, OutputArray dst, int colormap)
-    
+
     :param src: The source image, grayscale or colored does not matter.
     :param dst: The result is the colormapped source image. Note: :ocv:func:`Mat::create` is called on dst.
     :param colormap: The colormap to apply, see the list of available colormaps below.
@@ -55,10 +55,10 @@ In OpenCV 2.4 you only need :ocv:func:`applyColorMap` to apply a colormap on a g
         if (argc > 1) {
             filename = string(argv[1]);
         }
-	    // The following lines show how to apply a colormap on a given image
-	    // and show it with cv::imshow example with an image. An exception is
-	    // thrown if the path to the image is invalid.
-	    if(!filename.empty()) {
+        // The following lines show how to apply a colormap on a given image
+        // and show it with cv::imshow example with an image. An exception is
+        // thrown if the path to the image is invalid.
+        if(!filename.empty()) {
             Mat img0 = imread(filename);
             // Throw an exception, if the image can't be read:
             if(img0.empty()) {
@@ -71,9 +71,9 @@ In OpenCV 2.4 you only need :ocv:func:`applyColorMap` to apply a colormap on a g
             // Show the result:
             imshow("cm_img0", cm_img0);
             waitKey(0);
-	    }
+        }
 
-	    return 0;
+        return 0;
     }
 
 And here are the color scales for each of the available colormaps:

modules/contrib/doc/facerec/facerec_api.rst

@@ -6,7 +6,7 @@ FaceRecognizer
 FaceRecognizer
 --------------
 
-.. ocv:class:: FaceRecognizer
+.. ocv:class:: FaceRecognizer : public Algorithm
 
 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. ::
@@ -143,14 +143,8 @@ And finally train it on the given dataset (the face images and labels):
 FaceRecognizer::predict
 -----------------------
 
-.. ocv:function:: int FaceRecognizer::predict(InputArray src) const
-
-    Predicts a label for a given input image.
-
-    :param src: Sample image to get a prediction from.
-
-
-.. ocv:function:: void predict(InputArray src, int &label, double &confidence) const
+.. ocv:function:: int FaceRecognizer::predict( InputArray src ) const = 0
+.. ocv:function:: void FaceRecognizer::predict( InputArray src, int & label, double & confidence ) const = 0
 
     Predicts a label and associated confidence (e.g. distance) for a given input image.
 
@@ -219,8 +213,8 @@ 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 string& filename )
+.. ocv:function:: void FaceRecognizer::load( const FileStorage& fs ) = 0
 
 Loads a persisted model and state from a given XML or YAML file . Every
 :ocv:class:`FaceRecognizer` has to overwrite ``FaceRecognizer::load(FileStorage& fs)``

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

@@ -931,7 +931,7 @@ namespace cv
         virtual int predict(InputArray src) const = 0;
 
         // Predicts the label and confidence for a given sample.
-        CV_WRAP virtual void predict(InputArray src, CV_OUT int &label, CV_OUT double &dist) const = 0;
+        CV_WRAP virtual void predict(InputArray src, CV_OUT int &label, CV_OUT double &confidence) const = 0;
 
         // Serializes this object to a given filename.
         CV_WRAP virtual void save(const string& filename) const;
@@ -970,7 +970,7 @@ namespace cv
 
     CV_EXPORTS_W void applyColorMap(InputArray src, OutputArray dst, int colormap);
 
-    CV_EXPORTS_W bool initModule_contrib();
+    CV_EXPORTS bool initModule_contrib();
 }
 
 #include "opencv2/contrib/retina.hpp"

modules/imgproc/doc/filtering.rst

@@ -968,7 +968,7 @@ Smoothes an image using a Gaussian filter.
 
 .. ocv:function:: void GaussianBlur( InputArray src, OutputArray dst, Size ksize, double sigmaX, double sigmaY=0, int borderType=BORDER_DEFAULT )
 
-.. ocv:pyfunction:: cv2.GaussianBlur(src, ksize, sigma1[, dst[, sigma2[, borderType]]]) -> dst
+.. ocv:pyfunction:: cv2.GaussianBlur(src, ksize, sigmaX[, dst[, sigmaY[, borderType]]]) -> dst
 
     :param src: Source image. The image can have any number of channels, which are processed independently. The depth should be ``CV_8U``, ``CV_16U``, ``CV_16S``, ``CV_32F`` or ``CV_64F``.
 

modules/java/generator/rst_parser.py

@@ -47,6 +47,8 @@ params_mapping = {
     }
 }
 
+known_text_sections_names = ["Appendix", "Results", "Prerequisites", "Introduction", "Description"]
+
 class DeclarationParser(object):
     def __init__(self, line=None):
         if line is None:
@@ -130,7 +132,7 @@ class RstParser(object):
         for root, dirs, files in os.walk(os.path.join(module_path,"doc")):
             for filename in fnmatch.filter(files, "*.rst"):
                 doclist.append(os.path.join(root, filename))
-            
+
         for doc in doclist:
             self.parse_rst_file(module_name, doc)
 
@@ -146,7 +148,7 @@ class RstParser(object):
         self.sections_total += 1
         # skip sections having whitespace in name
         #if section_name.find(" ") >= 0 and section_name.find("::operator") < 0:
-        if section_name.find(" ") >= 0 and not bool(re.match(r"(\w+::)*operator\s*(\w+|>>|<<|\(\)|->|\+\+|--|=|==|\+=|-=)", section_name)):
+        if (section_name.find(" ") >= 0 and not bool(re.match(r"(\w+::)*operator\s*(\w+|>>|<<|\(\)|->|\+\+|--|=|==|\+=|-=)", section_name)) ) or section_name.endswith(":"):
             if show_errors:
                 print >> sys.stderr, "RST parser warning W%03d:  SKIPPED: \"%s\" File: %s:%s" % (WARNING_002_HDRWHITESPACE, section_name, file_name, lineno)
             self.sections_skipped += 1
@@ -306,7 +308,11 @@ class RstParser(object):
             if verbose:
                 self.print_info(func)
         elif func:
-            if show_errors:
+            if func["name"] in known_text_sections_names:
+                if show_errors:
+                    print >> sys.stderr, "RST parser warning W%03d:  SKIPPED: \"%s\" File: %s:%s" % (WARNING_002_HDRWHITESPACE, section_name, file_name, lineno)
+                self.sections_skipped += 1
+            elif show_errors:
                 self.print_info(func, True, sys.stderr)
 
     def parse_rst_file(self, module_name, doc):
@@ -336,7 +342,7 @@ class RstParser(object):
                 continue
 
             ll = l.rstrip()
-            if len(prev_line) > 0 and len(ll) >= len(prev_line) and ll == "-" * len(ll):
+            if len(prev_line) > 0 and len(ll) >= len(prev_line) and (ll == "-" * len(ll) or ll == "+" * len(ll)):
                 # new function candidate
                 if len(lines) > 1:
                     self.parse_section_safe(module_name, fname, doc, flineno, lines[:len(lines)-1])