Normalize whitespace in documentation and text files

modules/core/doc/clustering.rst

@@ -66,8 +66,8 @@ Splits an element set into equivalency classes.
 
     :param vec: Set of elements stored as a vector.
 
-    :param labels: Output vector of labels. It contains as many elements as  ``vec``. Each label  ``labels[i]``  is a 0-based cluster index of  ``vec[i]`` .   
-    
+    :param labels: Output vector of labels. It contains as many elements as  ``vec``. Each label  ``labels[i]``  is a 0-based cluster index of  ``vec[i]`` .
+
     :param predicate: Equivalence predicate (pointer to a boolean function of two arguments or an instance of the class that has the method  ``bool operator()(const _Tp& a, const _Tp& b)`` ). The predicate returns ``true`` when the elements are certainly in the same class, and returns ``false`` if they may or may not be in the same class.
 
 The generic function ``partition`` implements an

modules/core/doc/command_line_parser.rst

@@ -12,30 +12,30 @@ The CommandLineParser class is designed for command line arguments parsing
 
     .. ocv:function:: CommandLineParser::CommandLineParser(int argc, const char * const argv[], const std::string keys)
 
-        :param argc: 
-        :param argv: 
-        :param keys: 
+        :param argc:
+        :param argv:
+        :param keys:
 
     .. ocv:function:: T CommandLineParser::get<T>(const std::string& name, bool space_delete = true)
 
-        :param name: 
-        :param space_delete: 
+        :param name:
+        :param space_delete:
 
     .. ocv:function:: T CommandLineParser::get<T>(int index, bool space_delete = true)
 
-        :param index: 
-        :param space_delete:  
+        :param index:
+        :param space_delete:
 
     .. ocv:function:: bool CommandLineParser::has(const std::string& name)
 
-        :param name: 
+        :param name:
 
     .. ocv:function:: bool CommandLineParser::check()
 
 
     .. ocv:function:: void CommandLineParser::about(std::string message)
-    
-        :param message: 
+
+        :param message:
 
     .. ocv:function:: void CommandLineParser::printMessage()
 
@@ -78,7 +78,7 @@ Syntax:
 
 ::
 
-    const std::string keys = 
+    const std::string keys =
         "{help h usage ? |      | print this message   }"
         "{@image1        |      | image1 for compare   }"
         "{@image2        |      | image2 for compare   }"

modules/core/doc/drawing_functions.rst

@@ -405,8 +405,8 @@ The number of pixels along the line is stored in ``LineIterator::count`` . The m
 
     for(int i = 0; i < it.count; i++, ++it)
         buf[i] = *(const Vec3b)*it;
-    
-    // alternative way of iterating through the line    
+
+    // alternative way of iterating through the line
     for(int i = 0; i < it2.count; i++, ++it2)
     {
         Vec3b val = img.at<Vec3b>(it2.pos());

modules/core/doc/intro.rst

@@ -91,8 +91,8 @@ you can use::
 
    Ptr<T> ptr = new T(...);
 
-That is, ``Ptr<T> ptr`` encapsulates a pointer to a ``T`` instance and a reference counter associated with the pointer. See the 
-:ocv:class:`Ptr` 
+That is, ``Ptr<T> ptr`` encapsulates a pointer to a ``T`` instance and a reference counter associated with the pointer. See the
+:ocv:class:`Ptr`
 description for details.
 
 .. _AutomaticAllocation:

modules/core/doc/operations_on_arrays.rst

@@ -2283,7 +2283,7 @@ PCA constructors
         * **CV_PCA_DATA_AS_COL** indicates that the input samples are stored as matrix columns.
 
     :param maxComponents: maximum number of components that PCA should retain; by default, all the components are retained.
-    
+
     :param retainedVariance: Percentage of variance that PCA should retain. Using this parameter will let the PCA decided how many components to retain but it will always keep at least 2.
 
 The default constructor initializes an empty PCA structure. The other constructors initialize the structure and call
@@ -2312,7 +2312,7 @@ Performs Principal Component Analysis of the supplied dataset.
         * **CV_PCA_DATA_AS_COL** indicates that the input samples are stored as matrix columns.
 
     :param maxComponents: maximum number of components that PCA should retain; by default, all the components are retained.
-    
+
     :param retainedVariance: Percentage of variance that PCA should retain. Using this parameter will let the PCA decided how many components to retain but it will always keep at least 2.
 
 The operator performs PCA of the supplied dataset. It is safe to reuse the same PCA structure for multiple datasets. That is, if the  structure has been previously used with another dataset, the existing internal data is reclaimed and the new ``eigenvalues``, ``eigenvectors`` , and ``mean`` are allocated and computed.