Honor resently added functionality in hdr_parser and rst_parser; minor fixes in documentation

doc/_themes/blue/static/default.css_t

@@ -179,6 +179,10 @@ div.body p, div.body dd, div.body li {
     margin-bottom: 1em;
 }
 
+div.toctree-wrapper li, ul.simple li {
+    margin:0;
+}
+
 div.body h1,
 div.body h2,
 div.body h3,

doc/check_docs2.py

@@ -31,7 +31,7 @@ doc_signatures_whitelist = [
 # templates
 "Matx", "Vec", "SparseMat_", "Scalar_", "Mat_", "Ptr", "Size_", "Point_", "Rect_", "Point3_",
 "DataType", "detail::RotationWarperBase", "flann::Index_", "CalonderDescriptorExtractor",
-"gpu::DevMem2D_", "gpu::PtrStep_", "gpu::PtrElemStep_",
+"gpu::PtrStepSz", "gpu::PtrStep", "gpu::PtrElemStep_",
 # black boxes
 "CvArr", "CvFileStorage",
 # other
@@ -191,7 +191,7 @@ def process_module(module, path):
             hdrlist.append(os.path.join(root, filename))
 
     if module == "gpu":
-        hdrlist.append(os.path.join(path, "..", "core", "include", "opencv2", "core", "devmem2d.hpp"))
+        hdrlist.append(os.path.join(path, "..", "core", "include", "opencv2", "core", "cuda_devptrs.hpp"))
         hdrlist.append(os.path.join(path, "..", "core", "include", "opencv2", "core", "gpumat.hpp"))
 
     decls = []

modules/contrib/doc/facerec/facerec_api.rst

@@ -19,19 +19,19 @@ a unified access to all face recongition algorithms in OpenCV. ::
 
       // Trains a FaceRecognizer.
       virtual void train(InputArray src, InputArray labels) = 0;
-      
+
       // Updates a FaceRecognizer.
       virtual void update(InputArrayOfArrays src, InputArray labels);
-      
+
       // Gets a prediction from a FaceRecognizer.
       virtual int predict(InputArray src) const = 0;
-      
+
       // Predicts the label and confidence for a given sample.
       virtual void predict(InputArray src, int &label, double &confidence) const = 0;
 
       // Serializes this object to a given filename.
       virtual void save(const string& filename) const;
-      
+
       // Deserializes this object from a given filename.
       virtual void load(const string& filename);
 
@@ -58,7 +58,7 @@ I'll go a bit more into detail explaining :ocv:class:`FaceRecognizer`, because i
 
 Moreover every :ocv:class:`FaceRecognizer` supports the:
 
-* **Training** of a :ocv:class:`FaceRecognizer` with :ocv:func:`FaceRecognizer::train` on a given set of images (your face database!). 
+* **Training** of a :ocv:class:`FaceRecognizer` with :ocv:func:`FaceRecognizer::train` on a given set of images (your face database!).
 
 * **Prediction** of a given sample image, that means a face. The image is given as a :ocv:class:`Mat`.
 
@@ -111,7 +111,7 @@ Since every :ocv:class:`FaceRecognizer` is a :ocv:class:`Algorithm`, you can use
 .. code-block:: cpp
 
     // Create a FaceRecognizer:
-    Ptr<FaceRecognizer> model = createEigenFaceRecognizer();        
+    Ptr<FaceRecognizer> model = createEigenFaceRecognizer();
     // And here's how to get its name:
     std::string name = model->name();
 
@@ -121,7 +121,7 @@ FaceRecognizer::train
 
 Trains a FaceRecognizer with given data and associated labels.
 
-.. ocv:function:: void FaceRecognizer::train(InputArray src, InputArray labels)
+.. ocv:function:: void FaceRecognizer::train( InputArrayOfArrays src, InputArray labels ) = 0
 
     :param src: The training images, that means the faces you want to learn. The data has to be given as a ``vector<Mat>``.
 
@@ -166,7 +166,7 @@ FaceRecognizer::update
 
 Updates a FaceRecognizer with given data and associated labels.
 
-.. ocv:function:: void FaceRecognizer::update(InputArray src, InputArray labels)
+.. ocv:function:: void FaceRecognizer::update( InputArrayOfArrays src, InputArray labels )
 
     :param src: The training images, that means the faces you want to learn. The data has to be given as a ``vector<Mat>``.
 
@@ -193,7 +193,7 @@ This method updates a (probably trained) :ocv:class:`FaceRecognizer`, but only i
     //
     // Now updating the model is as easy as calling:
     model->update(newImages,newLabels);
-    // This will preserve the old model data and extend the existing model 
+    // This will preserve the old model data and extend the existing model
     // with the new features extracted from newImages!
 
 Calling update on an Eigenfaces model (see :ocv:func:`createEigenFaceRecognizer`), which doesn't support updating, will throw an error similar to:
@@ -203,8 +203,8 @@ Calling update on an Eigenfaces model (see :ocv:func:`createEigenFaceRecognizer`
     OpenCV Error: The function/feature is not implemented (This FaceRecognizer (FaceRecognizer.Eigenfaces) does not support updating, you have to use FaceRecognizer::train to update it.) in update, file /home/philipp/git/opencv/modules/contrib/src/facerec.cpp, line 305
     terminate called after throwing an instance of 'cv::Exception'
 
-Please note: The :ocv:class:`FaceRecognizer` does not store your training images, because this would be very memory intense and it's not the responsibility of te :ocv:class:`FaceRecognizer` to do so. The caller is responsible for maintaining the dataset, he want to work with. 
- 
+Please note: The :ocv:class:`FaceRecognizer` does not store your training images, because this would be very memory intense and it's not the responsibility of te :ocv:class:`FaceRecognizer` to do so. The caller is responsible for maintaining the dataset, he want to work with.
+
 FaceRecognizer::predict
 -----------------------
 

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

@@ -222,7 +222,7 @@ protected:
     void getLikelihoods(const Mat& queryImgDescriptor, const vector<
             Mat>& testImgDescriptors, vector<IMatch>& matches);
 
-    //procomputed data
+    //precomputed data
     int (*table)[8];
 
     //data precision

modules/gpu/doc/image_processing.rst

@@ -818,23 +818,23 @@ Performs linear blending of two images.
     :param result: Destination image.
 
     :param stream: Stream for the asynchronous version.
-    
-    
+
+
 gpu::bilateralFilter
--------------------
+--------------------
 Performs bilateral filtering of passed image
 
-.. ocv:function:: void gpu::bilateralFilter(const GpuMat& src, GpuMat& dst, int kernel_size, float sigma_color, float sigma_spatial, int borderMode, Stream& stream = Stream::Null());
-    
+.. ocv:function:: void gpu::bilateralFilter(const GpuMat& src, GpuMat& dst, int kernel_size, float sigma_color, float sigma_spatial, int borderMode, Stream& stream = Stream::Null())
+
     :param src: Source image. Supports only (channles != 2 && depth() != CV_8S && depth() != CV_32S && depth() != CV_64F).
 
     :param dst: Destination imagwe.
 
     :param kernel_size: Kernel window size.
 
-    :param sigma_color: Filter sigma in the color space. 
-    
-    :param sigma_spatial:  Filter sigma in the coordinate space. 
+    :param sigma_color: Filter sigma in the color space.
+
+    :param sigma_spatial:  Filter sigma in the coordinate space.
 
     :param borderMode:  Border type. See :ocv:func:`borderInterpolate` for details. ``BORDER_REFLECT101`` , ``BORDER_REPLICATE`` , ``BORDER_CONSTANT`` , ``BORDER_REFLECT`` and ``BORDER_WRAP`` are supported for now.
 
@@ -843,24 +843,24 @@ Performs bilateral filtering of passed image
 .. seealso::
 
     :ocv:func:`bilateralFilter`,
-    
-    
+
+
 gpu::nonLocalMeans
 -------------------
 Performs pure non local means denoising without any simplification, and thus it is not fast.
 
-.. ocv:function:: void nonLocalMeans(const GpuMat& src, GpuMat& dst, float h, int search_widow_size = 11, int block_size = 7, int borderMode = BORDER_DEFAULT, Stream& s = Stream::Null());
-    
+.. ocv:function:: void nonLocalMeans(const GpuMat& src, GpuMat& dst, float h, int search_widow_size = 11, int block_size = 7, int borderMode = BORDER_DEFAULT, Stream& s = Stream::Null())
+
     :param src: Source image. Supports only CV_8UC1, CV_8UC3.
 
     :param dst: Destination imagwe.
 
-    :param h: Filter sigma regulating filter strength for color. 
-    
+    :param h: Filter sigma regulating filter strength for color.
+
     :param search_widow_size: Size of search window.
 
-    :param block_size: Size of block used for computing weights. 
-        
+    :param block_size: Size of block used for computing weights.
+
     :param borderMode:  Border type. See :ocv:func:`borderInterpolate` for details. ``BORDER_REFLECT101`` , ``BORDER_REPLICATE`` , ``BORDER_CONSTANT`` , ``BORDER_REFLECT`` and ``BORDER_WRAP`` are supported for now.
 
     :param stream: Stream for the asynchronous version.
@@ -868,7 +868,7 @@ Performs pure non local means denoising without any simplification, and thus it
 .. seealso::
 
     :ocv:func:`fastNlMeansDenoising`
-    
+
 gpu::alphaComp
 -------------------
 Composites two images using alpha opacity values contained in each image.

modules/java/generator/rst_parser.py

 import os, sys, re, string, fnmatch
-allmodules = ["core", "flann", "imgproc", "ml", "highgui", "video", "features2d", "calib3d", "objdetect", "legacy", "contrib", "gpu", "androidcamera", "java", "python", "stitching", "ts", "photo", "nonfree", "videostab"]
+allmodules = ["core", "flann", "imgproc", "ml", "highgui", "video", "features2d", "calib3d", "objdetect", "legacy", "contrib", "gpu", "androidcamera", "java", "python", "stitching", "ts", "photo", "nonfree", "videostab", "ocl"]
 verbose = False
 show_warnings = True
 show_errors = True
@@ -342,7 +342,7 @@ class RstParser(object):
                 continue
 
             ll = l.rstrip()
-            if len(prev_line) > 0 and len(ll) >= len(prev_line) and (ll == "-" * len(ll) or ll == "+" * len(ll)):
+            if len(prev_line) > 0 and len(ll) >= len(prev_line) and (ll == "-" * len(ll) or 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])

modules/python/src2/hdr_parser.py

@@ -155,6 +155,8 @@ class CppHeaderParser(object):
             elif angle_stack:
                 arg_type += w
                 angle_stack[-1] += 1
+            elif arg_type == "struct":
+                arg_type += " " + w
             elif arg_type and arg_type != "~":
                 arg_name = " ".join(word_list[wi:])
                 break
@@ -429,7 +431,7 @@ class CppHeaderParser(object):
                 decl_start = decl_start[0:-2].rstrip() + " ()"
 
         # constructor/destructor case
-        if bool(re.match(r'(\w+::)*(?P<x>\w+)::~?(?P=x)', decl_start)):
+        if bool(re.match(r'^(\w+::)*(?P<x>\w+)::~?(?P=x)$', decl_start)):
             decl_start = "void " + decl_start
 
         rettype, funcname, modlist, argno = self.parse_arg(decl_start, -1)
@@ -441,10 +443,14 @@ class CppHeaderParser(object):
             else:
                 if bool(re.match('\w+\s+\(\*\w+\)\s*\(.*\)', decl_str)):
                     return [] # function typedef
+                elif bool(re.match('\w+\s+\(\w+::\*\w+\)\s*\(.*\)', decl_str)):
+                    return [] # class method typedef
                 elif bool(re.match('[A-Z_]+', decl_start)):
                     return [] # it seems to be a macro instantiation
                 elif "__declspec" == decl_start:
                     return []
+                elif bool(re.match(r'\w+\s+\(\*\w+\)\[\d+\]', decl_str)):
+                    return [] # exotic - dynamic 2d array
                 else:
                     #print rettype, funcname, modlist, argno
                     print "Error at %s:%d the function/method name is missing: '%s'" % (self.hname, self.lineno, decl_start)
@@ -799,6 +805,10 @@ class CppHeaderParser(object):
                 stmt = " ".join(stmt.split()) # normalize the statement
                 stack_top = self.block_stack[-1]
 
+                if stmt.startswith("@"):
+                    # Objective C ?
+                    break
+
                 decl = None
                 if stack_top[self.PROCESS_FLAG]:
                     # even if stack_top[PUBLIC_SECTION] is False, we still try to process the statement,
@@ -850,5 +860,7 @@ if __name__ == '__main__':
     decls = []
     for hname in opencv_hdr_list:
         decls += parser.parse(hname)
+    #for hname in sys.argv[1:]:
+        #decls += parser.parse(hname, wmode=False)
     parser.print_decls(decls)
     print len(decls)