#1205 fixed more bugs/typos in parameters

modules/features2d/doc/common_interfaces_of_feature_detectors.rst

@@ -15,27 +15,27 @@ KeyPoint
 Data structure for salient point detectors.
 
     .. ocv:member:: Point2f pt
-    
+
         coordinates of the keypoint
-        
+
     .. ocv:member:: float size
-    
+
          diameter of the meaningful keypoint neighborhood
-         
+
     .. ocv:member:: float angle
-    
+
         computed orientation of the keypoint (-1 if not applicable)
-        
+
     .. ocv:member:: float response
-    
+
         the response by which the most strong keypoints have been selected. Can be used for further sorting or subsampling
-        
+
     .. ocv:member:: int octave
-    
+
         octave (pyramid layer) from which the keypoint has been extracted
-        
+
     .. ocv:member:: int class_id
-    
+
         object id that can be used to clustered keypoints by an object they belong to
 
 KeyPoint::KeyPoint
@@ -51,19 +51,19 @@ The keypoint constructors
 .. ocv:pyfunction:: cv2.KeyPoint(x, y, _size[, _angle[, _response[, _octave[, _class_id]]]]) -> <KeyPoint object>
 
     :param x: x-coordinate of the keypoint
-    
+
     :param y: y-coordinate of the keypoint
-    
+
     :param _pt: x & y coordinates of the keypoint
-    
+
     :param _size: keypoint diameter
-    
+
     :param _angle: keypoint orientation
-    
+
     :param _response: keypoint detector response on the keypoint (that is, strength of the keypoint)
-    
+
     :param _octave: pyramid octave in which the keypoint has been detected
-    
+
     :param _class_id: object id
 
 
@@ -309,7 +309,7 @@ Wrapping class for feature detection using the
     protected:
         ...
     };
-    
+
 
 DenseFeatureDetector
 --------------------
@@ -317,18 +317,18 @@ DenseFeatureDetector
 
 Class for generation of image features which are distributed densely and regularly over the image. ::
 
-	class DenseFeatureDetector : public FeatureDetector
-	{
-	public:
-		DenseFeatureDetector( float initFeatureScale=1.f, int featureScaleLevels=1,
+        class DenseFeatureDetector : public FeatureDetector
+        {
+        public:
+                DenseFeatureDetector( float initFeatureScale=1.f, int featureScaleLevels=1,
                               float featureScaleMul=0.1f,
                               int initXyStep=6, int initImgBound=0,
                               bool varyXyStepWithScale=true,
                               bool varyImgBoundWithScale=false );
-	protected:
+        protected:
         ...
     };
-    
+
 The detector generates several levels (in the amount of ``featureScaleLevels``) of features. Features of each level are located in the nodes of a regular grid over the image (excluding the image boundary of given size). The level parameters (a feature scale, a node size, a size of boundary) are multiplied by ``featureScaleMul`` with level index growing depending on input flags, viz.:
 
 * Feature scale is multiplied always.
@@ -380,11 +380,11 @@ Class for extracting blobs from an image. ::
 
 The class implements a simple algorithm for extracting blobs from an image:
 
-#. Convert the source image to binary images by applying thresholding with several thresholds from ``minThreshold`` (inclusive) to ``maxThreshold`` (exclusive) with distance ``thresholdStep`` between neighboring thresholds. 
+#. Convert the source image to binary images by applying thresholding with several thresholds from ``minThreshold`` (inclusive) to ``maxThreshold`` (exclusive) with distance ``thresholdStep`` between neighboring thresholds.
 
-#. Extract connected components from every binary image by  :ocv:func:`findContours`  and calculate their centers. 
+#. Extract connected components from every binary image by  :ocv:func:`findContours`  and calculate their centers.
 
-#. Group centers from several binary images by their coordinates. Close centers form one group that corresponds to one blob, which is controlled by the ``minDistBetweenBlobs`` parameter. 
+#. Group centers from several binary images by their coordinates. Close centers form one group that corresponds to one blob, which is controlled by the ``minDistBetweenBlobs`` parameter.
 
 #. From the groups, estimate final centers of blobs and their radiuses and return as locations and sizes of keypoints.
 
@@ -468,7 +468,7 @@ panorama series.
 ``DynamicAdaptedFeatureDetector``  uses another detector, such as FAST or SURF, to do the dirty work,
 with the help of ``AdjusterAdapter`` .
 If the detected number of features is not large enough,
-``AdjusterAdapter`` adjusts the detection parameters so that the next detection 
+``AdjusterAdapter`` adjusts the detection parameters so that the next detection
 results in a bigger or smaller number of features.  This is repeated until either the number of desired features are found
 or the parameters are maxed out.
 
@@ -500,14 +500,14 @@ The constructor
 
     :param max_features: Maximum desired number of features.
 
-    :param max_iters: Maximum number of times to try adjusting the feature detector parameters. For :ocv:class:`FastAdjuster` , this number can be high, but with ``Star`` or ``Surf``  many iterations can be time-comsuming.  At each iteration the detector is rerun. 
+    :param max_iters: Maximum number of times to try adjusting the feature detector parameters. For :ocv:class:`FastAdjuster` , this number can be high, but with ``Star`` or ``Surf``  many iterations can be time-comsuming.  At each iteration the detector is rerun.
 
 AdjusterAdapter
 ---------------
 .. ocv:class:: AdjusterAdapter
 
 Class providing an interface for adjusting parameters of a feature detector. This interface is used by :ocv:class:`DynamicAdaptedFeatureDetector` . It is a wrapper for :ocv:class:`FeatureDetector` that enables adjusting parameters after feature detection. ::
-  
+
      class AdjusterAdapter: public FeatureDetector
      {
      public:
@@ -562,7 +562,7 @@ Example: ::
 
 AdjusterAdapter::good
 -------------------------
-Returns false if the detector parameters cannot be adjusted any more. 
+Returns false if the detector parameters cannot be adjusted any more.
 
 .. ocv:function:: bool AdjusterAdapter::good() const
 

modules/gpu/doc/feature_detection_and_description.rst

@@ -211,7 +211,7 @@ gpu::FAST_GPU::calcKeyPointsLocation
 -------------------------------------
 Find keypoints and compute it's response if ``nonmaxSupression`` is true.
 
-.. int gpu::FAST_GPU::calcKeyPointsLocation(const GpuMat& image, const GpuMat& mask)
+.. ocv:function:: int gpu::FAST_GPU::calcKeyPointsLocation(const GpuMat& image, const GpuMat& mask)
 
     :param image: Image where keypoints (corners) are detected. Only 8-bit grayscale images are supported.
 

modules/gpu/doc/image_processing.rst

@@ -769,7 +769,7 @@ Performs linear blending of two images.
 
     :param img1: First image. Supports only ``CV_8U`` and ``CV_32F`` depth.
 
-    :param img1: Second image. Must have the same size and the same type as ``img1`` .
+    :param img2: Second image. Must have the same size and the same type as ``img1`` .
 
     :param weights1: Weights for first image. Must have tha same size as ``img1`` . Supports only ``CV_32F`` type.
 
@@ -789,7 +789,7 @@ Composites two images using alpha opacity values contained in each image.
 
     :param img1: First image. Supports ``CV_8UC4`` , ``CV_16UC4`` , ``CV_32SC4`` and ``CV_32FC4`` types.
 
-    :param img1: Second image. Must have the same size and the same type as ``img1`` .
+    :param img2: Second image. Must have the same size and the same type as ``img1`` .
 
     :param dst: Destination image.
 

modules/gpu/doc/per_element_operations.rst

@@ -78,13 +78,11 @@ Computes a matrix-matrix or matrix-scalar per-element product.
 
 
 gpu::divide
----------------
+-----------
 Computes a matrix-matrix or matrix-scalar division.
 
 .. ocv:function:: void gpu::divide(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, double scale = 1, int dtype = -1, Stream& stream = Stream::Null())
 
-.. ocv:function:: void gpu::divide(const GpuMat& src1, const Scalar& src2, GpuMat& dst, double scale = 1, int dtype = -1, Stream& stream = Stream::Null())
-
 .. ocv:function:: void gpu::divide(double src1, const GpuMat& src2, GpuMat& dst, int dtype = -1, Stream& stream = Stream::Null())
 
     :param src1: First source matrix or a scalar.
@@ -104,9 +102,8 @@ This function, in contrast to :ocv:func:`divide`, uses a round-down rounding mod
 .. seealso:: :ocv:func:`divide`
 
 
-
-addWeighted
----------------
+gpu::addWeighted
+----------------
 Computes the weighted sum of two arrays.
 
 .. ocv:function:: void gpu::addWeighted(const GpuMat& src1, double alpha, const GpuMat& src2, double beta, double gamma, GpuMat& dst, int dtype = -1, Stream& stream = Stream::Null())

modules/gpu/doc/video.rst

@@ -47,6 +47,7 @@ Class computing the optical flow for two images using Brox et al Optical Flow al
 
 gpu::GoodFeaturesToTrackDetector_GPU
 ------------------------------------
+.. ocv:class:: gpu::GoodFeaturesToTrackDetector_GPU
 
 Class used for strong corners detection on an image. ::
 
@@ -120,6 +121,8 @@ Releases inner buffers memory.
 
 gpu::FarnebackOpticalFlow
 -------------------------
+.. ocv:class:: gpu::FarnebackOpticalFlow
+
 Class computing a dense optical flow using the Gunnar Farneback’s algorithm. ::
 
     class CV_EXPORTS FarnebackOpticalFlow
@@ -179,6 +182,7 @@ Releases unused auxiliary memory buffers.
 
 gpu::PyrLKOpticalFlow
 ---------------------
+.. ocv:class:: gpu::PyrLKOpticalFlow
 
 Class used for calculating an optical flow. ::
 

modules/objdetect/doc/latent_svm.rst

@@ -76,7 +76,8 @@ Description of the filter, which corresponds to the part of the object.
         vector describes penalty function (d_i in the paper)
         pf[0] * x + pf[1] * y + pf[2] * x^2 + pf[3] * y^2
         
-    .. ocv:member:: int sizeX, sizeY
+    .. ocv:member:: int sizeX
+    .. ocv:member:: int sizeY
         
         Rectangular map (sizeX x sizeY),
         every cell stores feature vector (dimension = p)

modules/stitching/doc/exposure_compensation.rst

@@ -29,15 +29,6 @@ detail::ExposureCompensation::feed
 
 .. ocv:function:: void detail::ExposureCompensation::feed(const std::vector<Point> &corners, const std::vector<Mat> &images, const std::vector<Mat> &masks)
 
-    :param corners: Source image top-left corners
-
-    :param images: Source images
-
-    :param masks: Image masks to update
-
-detail::ExposureCompensation::feed
-----------------------------------
-
 .. ocv:function:: void detail::ExposureCompensation::feed(const std::vector<Point> &corners, const std::vector<Mat> &images, const std::vector<std::pair<Mat,uchar> > &masks)
 
     :param corners: Source image top-left corners

modules/stitching/doc/introduction.rst

@@ -10,7 +10,7 @@ The implemented stitching pipeline is very similar to the one proposed in [BL07]
 .. image:: StitchingPipeline.jpg
 
 References
-----------
+==========
 
 .. [BL07] M. Brown and D. Lowe. Automatic Panoramic Image Stitching using Invariant Features. International Journal of Computer Vision, 74(1), pages 59-73, 2007.
 

modules/stitching/doc/matching.rst

@@ -245,4 +245,4 @@ Constructs a "best of 2 nearest" matcher.
 
     :param num_matches_thresh1: Minimum number of matches required for the 2D projective transform estimation used in the inliers classification step
 
-    :param num_matches_thresh1: Minimum number of matches required for the 2D projective transform re-estimation on inliers
+    :param num_matches_thresh2: Minimum number of matches required for the 2D projective transform re-estimation on inliers

modules/stitching/doc/motion_estimation.rst

@@ -204,6 +204,7 @@ Implementation of the camera parameters refinement algorithm which minimizes sum
 
 detail::BundleAdjusterRay
 -------------------------
+.. ocv:class:: detail::BundleAdjusterRay
 
 Implementation of the camera parameters refinement algorithm which minimizes sum of the distances between the rays passing through the camera center and a feature. ::
 

modules/stitching/doc/warpers.rst

@@ -101,7 +101,7 @@ Projects the image backward.
 
     :param dst_size: Backward-projected image size
 
-    :param dst_size: Backward-projected image
+    :param dst: Backward-projected image
 
 detail::RotationWarper::warpRoi
 -------------------------------