started work on API & doc synchronization (in particular, Mat& => Input/OutputArray in the descriptions)

2011-06-07 22:51:31 +00:00
parent 927b5c88ea
commit c7a42e9682
52 changed files with 1782 additions and 2048 deletions
--- a/modules/gpu/doc/camera_calibration_and_3d_reconstruction.rst
+++ b/modules/gpu/doc/camera_calibration_and_3d_reconstruction.rst
@@ -490,7 +490,7 @@ gpu::reprojectImageTo3D

    :param stream: Stream for the asynchronous version.

-See Also: :c:func:`reprojectImageTo3D` .
+See Also: :c:cpp:func:`reprojectImageTo3D` .

 .. index:: gpu::solvePnPRansac

@@ -507,7 +507,7 @@ gpu::solvePnPRansac
    
    :param camera_mat: 3x3 matrix of intrinsic camera parameters.
    
-    :param dist_coef: Distortion coefficients. See :c:func:`undistortPoints` for details.
+    :param dist_coef: Distortion coefficients. See :c:cpp:func:`undistortPoints` for details.
    
    :param rvec: Output 3D rotation vector.
    
@@ -523,5 +523,5 @@ gpu::solvePnPRansac
    
    :param inliers: Output vector of inlier indices.   

-See Also :c:func:`solvePnPRansac`.
+See Also :c:cpp:func:`solvePnPRansac`.
  
--- a/modules/gpu/doc/data_structures.rst
+++ b/modules/gpu/doc/data_structures.rst
@@ -148,7 +148,7 @@ In contrast with :c:type:`Mat`, in most cases ``GpuMat::isContinuous() == false`
 You are not recommended to leave static or global ``GpuMat`` variables allocated, that is to rely on its destructor. The destruction order of such variables and CUDA context is undefined. GPU memory release function returns error if the CUDA context has been destroyed before.

 See Also:
-:func:`Mat`
+:cpp:func:`Mat`

 .. index:: gpu::CudaMem

@@ -157,7 +157,7 @@ gpu::CudaMem
 .. cpp:class:: gpu::CudaMem

 This class with reference counting wraps special memory type allocation functions from CUDA. Its interface is also
-:func:`Mat`-like but with additional memory type parameters.
+:cpp:func:`Mat`-like but with additional memory type parameters.
    
 *
    ``ALLOC_PAGE_LOCKED``:  Sets a page locked memory type, used commonly for fast and asynchronous uploading/downloading data from/to GPU.
--- a/modules/gpu/doc/feature_detection_and_description.rst
+++ b/modules/gpu/doc/feature_detection_and_description.rst
@@ -195,7 +195,7 @@ gpu::BruteForceMatcher_GPU::match
    Finds the best match for each descriptor from a query set with train descriptors.

 See Also:
-:c:func:`DescriptorMatcher::match` 
+:c:cpp:func:`DescriptorMatcher::match` 

 .. index:: gpu::BruteForceMatcher_GPU::matchSingle

@@ -264,10 +264,10 @@ gpu::BruteForceMatcher_GPU::knnMatch

    Finds the k best matches for each descriptor from a query set with train descriptors. The function returns detected k (or less if not possible) matches in the increasing order by distance.

-.. c:function:: void knnMatch(const GpuMat& queryDescs, std::vector< std::vector<DMatch> >&matches, int k, const std::vector<GpuMat>&masks = std::vector<GpuMat>(), bool compactResult = false )
+.. cpp:function:: void knnMatch(const GpuMat& queryDescs, std::vector< std::vector<DMatch> >&matches, int k, const std::vector<GpuMat>&masks = std::vector<GpuMat>(), bool compactResult = false )

 See Also:
-:func:`DescriptorMatcher::knnMatch` 
+:cpp:func:`DescriptorMatcher::knnMatch` 

 .. index:: gpu::BruteForceMatcher_GPU::knnMatch

@@ -308,7 +308,7 @@ gpu::BruteForceMatcher_GPU::radiusMatch
    This function works only on devices with the compute capability  :math:`>=` 1.1.

 See Also:
-:func:`DescriptorMatcher::radiusMatch` 
+:cpp:func:`DescriptorMatcher::radiusMatch` 

 .. index:: gpu::BruteForceMatcher_GPU::radiusMatch

--- a/modules/gpu/doc/image_filtering.rst
+++ b/modules/gpu/doc/image_filtering.rst
@@ -93,7 +93,7 @@ This is a base class for Filter Engine. ::


 The class can be used to apply an arbitrary filtering operation to an image. It contains all the necessary intermediate buffers. Pointers to the initialized ``FilterEngine_GPU`` instances are returned by various ``create*Filter_GPU`` functions (see below), and they are used inside high-level functions such as
-:func:`gpu::filter2D`, :func:`gpu::erode`, :func:`gpu::Sobel` , and others.
+:cpp:func:`gpu::filter2D`, :cpp:func:`gpu::erode`, :cpp:func:`gpu::Sobel` , and others.

 By using ``FilterEngine_GPU`` instead of functions you can avoid unnecessary memory allocation for intermediate buffers and get much better performance: 
 ::
@@ -224,7 +224,7 @@ gpu::createBoxFilter_GPU
 	
 	This filter does not check out-of-border accesses, so only a proper sub-matrix of a bigger matrix has to be passed to it.

-See Also: :c:func:`boxFilter`
+See Also: :c:cpp:func:`boxFilter`

 .. index:: gpu::boxFilter

@@ -248,7 +248,7 @@ gpu::boxFilter
 	
 	This filter does not check out-of-border accesses, so only a proper sub-matrix of a bigger matrix has to be passed to it.

-See Also: :c:func:`boxFilter`
+See Also: :c:cpp:func:`boxFilter`

 .. index:: gpu::blur

@@ -270,7 +270,7 @@ gpu::blur
 	
 	This filter does not check out-of-border accesses, so only a proper sub-matrix of a bigger matrix has to be passed to it.

-See Also: :c:func:`blur`, :cpp:func:`gpu::boxFilter`
+See Also: :c:cpp:func:`blur`, :cpp:func:`gpu::boxFilter`

 .. index:: gpu::createMorphologyFilter_GPU

@@ -296,7 +296,7 @@ gpu::createMorphologyFilter_GPU
 	
 	This filter does not check out-of-border accesses, so only a proper sub-matrix of a bigger matrix has to be passed to it.

-See Also: :c:func:`createMorphologyFilter`
+See Also: :c:cpp:func:`createMorphologyFilter`

 .. index:: gpu::erode

@@ -320,7 +320,7 @@ gpu::erode
 	
 	This filter does not check out-of-border accesses, so only a proper sub-matrix of a bigger matrix has to be passed to it.

-See Also: :c:func:`erode`
+See Also: :c:cpp:func:`erode`

 .. index:: gpu::dilate

@@ -344,7 +344,7 @@ gpu::dilate
 	
 	This filter does not check out-of-border accesses, so only a proper sub-matrix of a bigger matrix has to be passed to it.

-See Also: :c:func:`dilate`
+See Also: :c:cpp:func:`dilate`

 .. index:: gpu::morphologyEx

@@ -381,7 +381,7 @@ gpu::morphologyEx
 	
 	This filter does not check out-of-border accesses, so only a proper sub-matrix of a bigger matrix has to be passed to it.

-See Also: :c:func:`morphologyEx` 
+See Also: :c:cpp:func:`morphologyEx` 

 .. index:: gpu::createLinearFilter_GPU

@@ -407,7 +407,7 @@ gpu::createLinearFilter_GPU
 	
 	This filter does not check out-of-border accesses, so only a proper sub-matrix of a bigger matrix has to be passed to it.

-See Also: :c:func:`createLinearFilter`
+See Also: :c:cpp:func:`createLinearFilter`

 .. index:: gpu::filter2D

@@ -431,7 +431,7 @@ gpu::filter2D
 	
 	This filter does not check out-of-border accesses, so only a proper sub-matrix of a bigger matrix has to be passed to it.

-See Also: :c:func:`filter2D`
+See Also: :c:cpp:func:`filter2D`

 .. index:: gpu::Laplacian

@@ -447,15 +447,15 @@ gpu::Laplacian

    :param ddepth: Desired depth of the destination image. It supports only the same depth as the source image depth.

-    :param ksize: Aperture size used to compute the second-derivative filters (see :c:func:`getDerivKernels`). It must be positive and odd. Only  ``ksize``  = 1 and  ``ksize``  = 3 are supported.
+    :param ksize: Aperture size used to compute the second-derivative filters (see :c:cpp:func:`getDerivKernels`). It must be positive and odd. Only  ``ksize``  = 1 and  ``ksize``  = 3 are supported.

-    :param scale: Optional scale factor for the computed Laplacian values. By default, no scaling is applied (see  :c:func:`getDerivKernels` ).
+    :param scale: Optional scale factor for the computed Laplacian values. By default, no scaling is applied (see  :c:cpp:func:`getDerivKernels` ).

 	**Note:**
 	
 	This filter does not check out-of-border accesses, so only a proper sub-matrix of a bigger matrix has to be passed to it.

-See Also: :c:func:`Laplacian`,:func:`gpu::filter2D` .
+See Also: :c:cpp:func:`Laplacian`,:cpp:func:`gpu::filter2D` .

 .. index:: gpu::getLinearRowFilter_GPU

@@ -473,13 +473,13 @@ gpu::getLinearRowFilter_GPU

    :param anchor: Anchor position within the kernel. Negative values mean that the anchor is positioned at the aperture center.

-    :param borderType: Pixel extrapolation method. For details, see :c:func:`borderInterpolate`. For details on limitations, see below.
+    :param borderType: Pixel extrapolation method. For details, see :c:cpp:func:`borderInterpolate`. For details on limitations, see below.

 	There are two versions of the algorithm: NPP and OpenCV.
 	* NPP version is called when ``srcType == CV_8UC1`` or ``srcType == CV_8UC4`` and ``bufType == srcType`` . Otherwise, the OpenCV version is called. NPP supports only ``BORDER_CONSTANT`` border type and does not check indices outside the image. 
 	* OpenCV version supports only ``CV_32F`` buffer depth and ``BORDER_REFLECT101``,``BORDER_REPLICATE``, and ``BORDER_CONSTANT`` border types. It checks indices outside the image.

-See Also:,:func:`createSeparableLinearFilter` .
+See Also:,:cpp:func:`createSeparableLinearFilter` .

 .. index:: gpu::getLinearColumnFilter_GPU

@@ -497,13 +497,13 @@ gpu::getLinearColumnFilter_GPU

    :param anchor: Anchor position within the kernel. Negative values mean that the anchor is positioned at the aperture center.

-    :param borderType: Pixel extrapolation method. For details, see  :c:func:`borderInterpolate` . For details on limitations, see below.
+    :param borderType: Pixel extrapolation method. For details, see  :c:cpp:func:`borderInterpolate` . For details on limitations, see below.

 	There are two versions of the algorithm: NPP and OpenCV.
 	* NPP version is called when ``dstType == CV_8UC1`` or ``dstType == CV_8UC4`` and ``bufType == dstType`` . Otherwise, the OpenCV version is called. NPP supports only ``BORDER_CONSTANT`` border type and does not check indices outside the image. 
 	* OpenCV version supports only ``CV_32F`` buffer depth and ``BORDER_REFLECT101``, ``BORDER_REPLICATE``, and ``BORDER_CONSTANT`` border types. It checks indices outside image.
 	
-See Also: :cpp:func:`gpu::getLinearRowFilter_GPU`, :c:func:`createSeparableLinearFilter`
+See Also: :cpp:func:`gpu::getLinearRowFilter_GPU`, :c:cpp:func:`createSeparableLinearFilter`

 .. index:: gpu::createSeparableLinearFilter_GPU

@@ -521,10 +521,10 @@ gpu::createSeparableLinearFilter_GPU

    :param anchor: Anchor position within the kernel. Negative values mean that anchor is positioned at the aperture center.

-    :param rowBorderType, columnBorderType: Pixel extrapolation method in the horizontal and vertical directions For details, see  :c:func:`borderInterpolate`. For details on limitations, see :cpp:func:`gpu::getLinearRowFilter_GPU`, cpp:func:`gpu::getLinearColumnFilter_GPU`.
+    :param rowBorderType, columnBorderType: Pixel extrapolation method in the horizontal and vertical directions For details, see  :c:cpp:func:`borderInterpolate`. For details on limitations, see :cpp:func:`gpu::getLinearRowFilter_GPU`, cpp:cpp:func:`gpu::getLinearColumnFilter_GPU`.


-See Also: :cpp:func:`gpu::getLinearRowFilter_GPU`, :cpp:func:`gpu::getLinearColumnFilter_GPU`, :c:func:`createSeparableLinearFilter`
+See Also: :cpp:func:`gpu::getLinearRowFilter_GPU`, :cpp:func:`gpu::getLinearColumnFilter_GPU`, :c:cpp:func:`createSeparableLinearFilter`

 .. index:: gpu::sepFilter2D

@@ -544,9 +544,9 @@ gpu::sepFilter2D

    :param anchor: Anchor position within the kernel. The default value ``(-1, 1)`` means that the anchor is at the kernel center.

-    :param rowBorderType, columnBorderType: Pixel extrapolation method. For details, see  :c:func:`borderInterpolate`.
+    :param rowBorderType, columnBorderType: Pixel extrapolation method. For details, see  :c:cpp:func:`borderInterpolate`.

-See Also: :cpp:func:`gpu::createSeparableLinearFilter_GPU`, :c:func:`sepFilter2D`
+See Also: :cpp:func:`gpu::createSeparableLinearFilter_GPU`, :c:cpp:func:`sepFilter2D`

 .. index:: gpu::createDerivFilter_GPU

@@ -564,11 +564,11 @@ gpu::createDerivFilter_GPU

    :param dy: Derivative order in respect of y.

-    :param ksize: Aperture size. See  :c:func:`getDerivKernels` for details.
+    :param ksize: Aperture size. See  :c:cpp:func:`getDerivKernels` for details.

-    :param rowBorderType, columnBorderType: Pixel extrapolation method. See  :c:func:`borderInterpolate` for details.
+    :param rowBorderType, columnBorderType: Pixel extrapolation method. See  :c:cpp:func:`borderInterpolate` for details.

-See Also: :cpp:func:`gpu::createSeparableLinearFilter_GPU`, :c:func:`createDerivFilter`
+See Also: :cpp:func:`gpu::createSeparableLinearFilter_GPU`, :c:cpp:func:`createDerivFilter`

 .. index:: gpu::Sobel

@@ -590,11 +590,11 @@ gpu::Sobel

    :param ksize: Size of the extended Sobel kernel. Possible valies are 1, 3, 5 or 7.

-    :param scale: Optional scale factor for the computed derivative values. By default, no scaling is applied. For details, see  :c:func:`getDerivKernels` .
+    :param scale: Optional scale factor for the computed derivative values. By default, no scaling is applied. For details, see  :c:cpp:func:`getDerivKernels` .

-    :param rowBorderType, columnBorderType: Pixel extrapolation method. See  :c:func:`borderInterpolate` for details.
+    :param rowBorderType, columnBorderType: Pixel extrapolation method. See  :c:cpp:func:`borderInterpolate` for details.

-See Also: :cpp:func:`gpu::createSeparableLinearFilter_GPU`, :c:func:`Sobel`
+See Also: :cpp:func:`gpu::createSeparableLinearFilter_GPU`, :c:cpp:func:`Sobel`

 .. index:: gpu::Scharr

@@ -614,11 +614,11 @@ gpu::Scharr

    :param yorder: Order of the derivative y.

-    :param scale: Optional scale factor for the computed derivative values. By default, no scaling is applied. See  :c:func:`getDerivKernels`  for details.
+    :param scale: Optional scale factor for the computed derivative values. By default, no scaling is applied. See  :c:cpp:func:`getDerivKernels`  for details.

-    :param rowBorderType, columnBorderType: Pixel extrapolation method. For details, see  :c:func:`borderInterpolate`  and :c:func:`Scharr` .
+    :param rowBorderType, columnBorderType: Pixel extrapolation method. For details, see  :c:cpp:func:`borderInterpolate`  and :c:cpp:func:`Scharr` .

-See Also: :cpp:func:`gpu::createSeparableLinearFilter_GPU`, :c:func:`Scharr`
+See Also: :cpp:func:`gpu::createSeparableLinearFilter_GPU`, :c:cpp:func:`Scharr`

 .. index:: gpu::createGaussianFilter_GPU

@@ -630,15 +630,15 @@ gpu::createGaussianFilter_GPU

    :param type: Source and destination image type.  ``CV_8UC1``, ``CV_8UC4``, ``CV_16SC1``, ``CV_16SC2``, ``CV_32SC1``, ``CV_32FC1`` are supported.

-    :param ksize: Aperture size. See  :c:func:`getGaussianKernel` for details.
+    :param ksize: Aperture size. See  :c:cpp:func:`getGaussianKernel` for details.

-    :param sigmaX: Gaussian sigma in the horizontal direction. See  :c:func:`getGaussianKernel` for details.
+    :param sigmaX: Gaussian sigma in the horizontal direction. See  :c:cpp:func:`getGaussianKernel` for details.

    :param sigmaY: Gaussian sigma in the vertical direction. If 0, then  :math:`\texttt{sigmaY}\leftarrow\texttt{sigmaX}` .

-    :param rowBorderType, columnBorderType: Border type to use. See  :c:func:`borderInterpolate` for details.
+    :param rowBorderType, columnBorderType: Border type to use. See  :c:cpp:func:`borderInterpolate` for details.

-See Also: :cpp:func:`gpu::createSeparableLinearFilter_GPU`, :c:func:`createGaussianFilter`
+See Also: :cpp:func:`gpu::createSeparableLinearFilter_GPU`, :c:cpp:func:`createGaussianFilter`

 .. index:: gpu::GaussianBlur

@@ -654,11 +654,11 @@ gpu::GaussianBlur

    :param ksize: Gaussian kernel size.  ``ksize.width``  and  ``ksize.height``  can differ but they both must be positive and odd. If they are zeros, they are computed from  ``sigmaX``  and  ``sigmaY`` .

-    :param sigmaX, sigmaY: Gaussian kernel standard deviations in X and Y direction. If  ``sigmaY``  is zero, it is set to be equal to  ``sigmaX`` . If they are both zeros, they are computed from  ``ksize.width``  and  ``ksize.height``, respectively. See  :c:func:`getGaussianKernel` for details. To fully control the result regardless of possible future modification of all this semantics, you are recommended to specify all of  ``ksize``, ``sigmaX``, and  ``sigmaY`` .
+    :param sigmaX, sigmaY: Gaussian kernel standard deviations in X and Y direction. If  ``sigmaY``  is zero, it is set to be equal to  ``sigmaX`` . If they are both zeros, they are computed from  ``ksize.width``  and  ``ksize.height``, respectively. See  :c:cpp:func:`getGaussianKernel` for details. To fully control the result regardless of possible future modification of all this semantics, you are recommended to specify all of  ``ksize``, ``sigmaX``, and  ``sigmaY`` .

-    :param rowBorderType, columnBorderType: Pixel extrapolation method. See  :c:func:`borderInterpolate` for details.
+    :param rowBorderType, columnBorderType: Pixel extrapolation method. See  :c:cpp:func:`borderInterpolate` for details.

-See Also: :cpp:func:`gpu::createGaussianFilter_GPU`, :c:func:`GaussianBlur`
+See Also: :cpp:func:`gpu::createGaussianFilter_GPU`, :c:cpp:func:`GaussianBlur`

 .. index:: gpu::getMaxFilter_GPU

--- a/modules/gpu/doc/image_processing.rst
+++ b/modules/gpu/doc/image_processing.rst
@@ -42,7 +42,7 @@ gpu::meanShiftProc
    :param criteria: Termination criteria. See :cpp:class:`TermCriteria`.

 See Also:
-:c:func:`gpu::meanShiftFiltering` 
+:c:cpp:func:`gpu::meanShiftFiltering` 

 .. index:: gpu::meanShiftSegmentation

@@ -81,7 +81,7 @@ gpu::integral
    :param sqsum: Squared integral image of the  ``CV_32FC1`` type.

 See Also:
-:c:func:`integral` 
+:c:cpp:func:`integral` 

 .. index:: gpu::sqrIntegral

@@ -128,7 +128,7 @@ gpu::cornerHarris
    :param borderType: Pixel extrapolation method. Only  ``BORDER_REFLECT101`` and  ``BORDER_REPLICATE`` are supported for now.

 See Also:
-:c:func:`cornerHarris` 
+:c:cpp:func:`cornerHarris` 

 .. index:: gpu::cornerMinEigenVal

@@ -150,7 +150,7 @@ gpu::cornerMinEigenVal

    :param borderType: Pixel extrapolation method. Only ``BORDER_REFLECT101`` and ``BORDER_REPLICATE`` are supported for now.

-See also: :c:func:`cornerMinEigenVal`
+See also: :c:cpp:func:`cornerMinEigenVal`

 .. index:: gpu::mulSpectrums

@@ -173,7 +173,7 @@ gpu::mulSpectrums
    Only full (not packed) ``CV_32FC2`` complex spectrums in the interleaved format are supported for now.

 See Also:
-:c:func:`mulSpectrums` 
+:c:cpp:func:`mulSpectrums` 

 .. index:: gpu::mulAndScaleSpectrums

@@ -198,7 +198,7 @@ gpu::mulAndScaleSpectrums
    Only full (not packed) ``CV_32FC2`` complex spectrums in the interleaved format are supported for now.

 See Also:
-:c:func:`mulSpectrums` 
+:c:cpp:func:`mulSpectrums` 

 .. index:: gpu::dft

@@ -237,7 +237,7 @@ gpu::dft
        If the source matrix is real (its type is ``CV_32FC1``    ), forward DFT is performed. The result of the DFT is packed into complex ( ``CV_32FC2``    ) matrix. So, the width of the destination matrix is ``dft_size.width / 2 + 1``    . But if the source is a single column, the height is reduced instead of the width.

 See Also:
-:c:func:`dft` 
+:c:cpp:func:`dft` 

 .. index:: gpu::convolve

@@ -268,7 +268,7 @@ gpu::ConvolveBuf
 .. cpp:class:: gpu::ConvolveBuf

 This class provides a memory buffer for the
-    :c:func:`gpu::convolve` function. 
+    :c:cpp:func:`gpu::convolve` function. 
 ::

    struct CV_EXPORTS ConvolveBuf
@@ -290,12 +290,12 @@ gpu::ConvolveBuf::ConvolveBuf
 .. cpp:function:: ConvolveBuf::ConvolveBuf()

    Constructs an empty buffer that is properly resized after the first call of the 
-    :c:func:`convolve` function.
+    :c:cpp:func:`convolve` function.

 .. cpp:function:: ConvolveBuf::ConvolveBuf(Size image_size, Size templ_size)

    Constructs a buffer for the 
-    :c:func:`convolve` function with respective arguments.
+    :c:cpp:func:`convolve` function with respective arguments.

 .. index:: gpu::matchTemplate

@@ -328,7 +328,7 @@ gpu::matchTemplate
    * ``CV_TM_CCORR``

 See Also:
-:c:func:`matchTemplate` 
+:c:cpp:func:`matchTemplate` 

 .. index:: gpu::remap

@@ -354,7 +354,7 @@ gpu::remap

    Values of pixels with non-integer coordinates are computed using bilinear the interpolation.

-See Also: :c:func:`remap` 
+See Also: :c:cpp:func:`remap` 

 .. index:: gpu::cvtColor

@@ -370,7 +370,7 @@ gpu::cvtColor

    :param dst: Destination image with the same size and depth as  ``src`` .

-    :param code: Color space conversion code. For details, see  :func:`cvtColor` . Conversion to/from Luv and Bayer color spaces is not supported.
+    :param code: Color space conversion code. For details, see  :cpp:func:`cvtColor` . Conversion to/from Luv and Bayer color spaces is not supported.

    :param dcn: Number of channels in the destination image. If the parameter is 0, the number of the channels is derived automatically from  ``src`` and the  ``code`` .

@@ -379,7 +379,7 @@ gpu::cvtColor
    3-channel color spaces (like ``HSV``, ``XYZ``, and so on) can be stored in a 4-channel image for better perfomance.

 See Also:
-:func:`cvtColor` 
+:cpp:func:`cvtColor` 

 .. index:: gpu::threshold

@@ -399,12 +399,12 @@ gpu::threshold

    :param maxVal: Maximum value to use with  ``THRESH_BINARY`` and  ``THRESH_BINARY_INV`` threshold types.

-    :param thresholdType: Threshold type. For details, see  :func:`threshold` . The ``THRESH_OTSU`` threshold type is not supported.
+    :param thresholdType: Threshold type. For details, see  :cpp:func:`threshold` . The ``THRESH_OTSU`` threshold type is not supported.

    :param stream: Stream for the asynchronous version.

 See Also:
-:func:`threshold` 
+:cpp:func:`threshold` 

 .. index:: gpu::resize

@@ -439,7 +439,7 @@ gpu::resize

    :param interpolation: Interpolation method. Only  ``INTER_NEAREST`` and  ``INTER_LINEAR`` are supported.

-See Also: :func:`resize` 
+See Also: :cpp:func:`resize` 

 .. index:: gpu::warpAffine

@@ -457,10 +457,10 @@ gpu::warpAffine

    :param dsize: Size of the destination image.

-    :param flags: Combination of interpolation methods (see  :func:`resize`) and the optional flag  ``WARP_INVERSE_MAP`` specifying that  ``M`` is an inverse transformation (``dst=>src``). Only ``INTER_NEAREST``, ``INTER_LINEAR``, and  ``INTER_CUBIC`` interpolation methods are supported.
+    :param flags: Combination of interpolation methods (see  :cpp:func:`resize`) and the optional flag  ``WARP_INVERSE_MAP`` specifying that  ``M`` is an inverse transformation (``dst=>src``). Only ``INTER_NEAREST``, ``INTER_LINEAR``, and  ``INTER_CUBIC`` interpolation methods are supported.

 See Also:
-:func:`warpAffine` 
+:cpp:func:`warpAffine` 

 .. index:: gpu::warpPerspective

@@ -478,10 +478,10 @@ gpu::warpPerspective

    :param dsize: Size of the destination image.

-    :param flags: Combination of interpolation methods (see  :func:`resize` ) and the optional flag  ``WARP_INVERSE_MAP`` specifying that  ``M`` is the inverse transformation (``dst => src``). Only  ``INTER_NEAREST``, ``INTER_LINEAR``, and  ``INTER_CUBIC`` interpolation methods are supported.
+    :param flags: Combination of interpolation methods (see  :cpp:func:`resize` ) and the optional flag  ``WARP_INVERSE_MAP`` specifying that  ``M`` is the inverse transformation (``dst => src``). Only  ``INTER_NEAREST``, ``INTER_LINEAR``, and  ``INTER_CUBIC`` interpolation methods are supported.

 See Also:
-:func:`warpPerspective` 
+:cpp:func:`warpPerspective` 

 .. index:: gpu::rotate

@@ -506,7 +506,7 @@ gpu::rotate
    :param interpolation: Interpolation method. Only  ``INTER_NEAREST``, ``INTER_LINEAR``, and  ``INTER_CUBIC`` are supported.

 See Also:
-:func:`gpu::warpAffine` 
+:cpp:func:`gpu::warpAffine` 

 .. index:: gpu::copyMakeBorder

@@ -525,7 +525,7 @@ gpu::copyMakeBorder
    :param value: Border value.

 See Also:
-:func:`copyMakeBorder`
+:cpp:func:`copyMakeBorder`

 .. index:: gpu::rectStdDev

--- a/modules/gpu/doc/introduction.rst
+++ b/modules/gpu/doc/introduction.rst
@@ -15,9 +15,9 @@ The GPU module depends on the CUDA Toolkit and NVIDIA Performance Primitives lib
 The OpenCV GPU module is designed for ease of use and does not require any knowledge of CUDA. Though, such a knowledge will certainly be useful to handle non-trivial cases or achieve the highest performance. It is helpful to understand the cost of various operations, what the GPU does, what the preferred data formats are, and so on. The GPU module is an effective instrument for quick implementation of GPU-accelerated computer vision algorithms. However, if your algorithm involves many simple operations, then, for the best possible performance, you may still need to write your own kernels to avoid extra write and read operations on the intermediate results.

 To enable CUDA support, configure OpenCV using ``CMake`` with ``WITH_CUDA=ON`` . When the flag is set and if CUDA is installed, the full-featured OpenCV GPU module is built. Otherwise, the module is still built, but at runtime all functions from the module throw
-:func:`Exception` with ``CV_GpuNotSupported`` error code, except for
-:func:`gpu::getCudaEnabledDeviceCount()`. The latter function returns zero GPU count in this case. Building OpenCV without CUDA support does not perform device code compilation, so it does not require the CUDA Toolkit installed. Therefore, using the
-:func:`gpu::getCudaEnabledDeviceCount()` function, you can implement a high-level algorithm that will detect GPU presence at runtime and choose an appropriate implementation (CPU or GPU) accordingly.
+:cpp:func:`Exception` with ``CV_GpuNotSupported`` error code, except for
+:cpp:func:`gpu::getCudaEnabledDeviceCount()`. The latter function returns zero GPU count in this case. Building OpenCV without CUDA support does not perform device code compilation, so it does not require the CUDA Toolkit installed. Therefore, using the
+:cpp:func:`gpu::getCudaEnabledDeviceCount()` function, you can implement a high-level algorithm that will detect GPU presence at runtime and choose an appropriate implementation (CPU or GPU) accordingly.

 Compilation for Different NVIDIA* Platforms
 -------------------------------------------
@@ -34,12 +34,12 @@ By default, the OpenCV GPU module includes:
    PTX code for compute capabilities 1.1 and 1.3 (controlled by ``CUDA_ARCH_PTX``     in ``CMake``)

 This means that for devices with CC 1.3 and 2.0 binary images are ready to run. For all newer platforms, the PTX code for 1.3 is JIT'ed to a binary image. For devices with CC 1.1 and 1.2, the PTX for 1.1 is JIT'ed. For devices with CC 1.0, no code is available and the functions throw
-:func:`Exception`. For platforms where JIT compilation is performed first, the run is slow.
+:cpp:func:`Exception`. For platforms where JIT compilation is performed first, the run is slow.

 On a GPU with CC 1.0, you can still compile the GPU module and most of the functions will run flawlessly. To achieve this, add "1.0" to the list of binaries, for example, ``CUDA_ARCH_BIN="1.0 1.3 2.0"`` . The functions that cannot be run on CC 1.0 GPUs throw an exception.

 You can always determine at runtime whether the OpenCV GPU-built binaries (or PTX code) are compatible with your GPU. The function
-:func:`gpu::DeviceInfo::isCompatible` returns the compatibility status (true/false).
+:cpp:func:`gpu::DeviceInfo::isCompatible` returns the compatibility status (true/false).

 Threading and Multi-threading
 ------------------------------
@@ -57,7 +57,7 @@ In the current version, each of the OpenCV GPU algorithms can use only a single

 *
    If you use only synchronous functions, create several CPU threads (one per each GPU) and from within each thread create a CUDA context for the corresponding GPU using
-    :func:`gpu::setDevice()`     or Driver API. Each of the threads will use the associated GPU.
+    :cpp:func:`gpu::setDevice()`     or Driver API. Each of the threads will use the associated GPU.

 *
    If you use asynchronous functions, you can use the Driver API to create several CUDA contexts associated with different GPUs but attached to one CPU thread. Within the thread you can switch from one GPU to another by making the corresponding context "current". With non-blocking GPU calls, managing algorithm is clear.
--- a/modules/gpu/doc/matrix_reductions.rst
+++ b/modules/gpu/doc/matrix_reductions.rst
@@ -17,7 +17,7 @@ gpu::meanStdDev

    :param stddev: Standard deviation value.

-See Also: :c:func:`meanStdDev` 
+See Also: :c:cpp:func:`meanStdDev` 

 .. index:: gpu::norm

@@ -37,7 +37,7 @@ gpu::norm

    :param buf: Optional buffer to avoid extra memory allocations. It is resized automatically.

-See Also: :c:func:`norm`
+See Also: :c:cpp:func:`norm`

 .. index:: gpu::sum

@@ -53,7 +53,7 @@ gpu::sum

    :param buf: Optional buffer to avoid extra memory allocations. It is resized automatically.

-See Also: :c:func:`sum` 
+See Also: :c:cpp:func:`sum` 

 .. index:: gpu::absSum

@@ -105,7 +105,7 @@ gpu::minMax

 The function does not work with ``CV_64F`` images on GPUs with the compute capability < 1.3.
 	
-See Also: :c:func:`minMaxLoc` 
+See Also: :c:cpp:func:`minMaxLoc` 

 .. index:: gpu::minMaxLoc

@@ -135,7 +135,7 @@ gpu::minMaxLoc

 	The function does not work with ``CV_64F`` images on GPU with the compute capability < 1.3.

-See Also: :c:func:`minMaxLoc` 
+See Also: :c:cpp:func:`minMaxLoc` 

 .. index:: gpu::countNonZero

@@ -153,4 +153,4 @@ gpu::countNonZero

 	The function does not work with ``CV_64F`` images on GPUs with the compute capability < 1.3.
 	
-	See Also: :c:func:`countNonZero` 
+	See Also: :c:cpp:func:`countNonZero` 
--- a/modules/gpu/doc/object_detection.rst
+++ b/modules/gpu/doc/object_detection.rst
@@ -173,11 +173,11 @@ gpu::HOGDescriptor::detectMultiScale

 	Performs object detection with a multi-scale window.

-    :param img: Source image. See  :func:`gpu::HOGDescriptor::detect`  for type limitations.
+    :param img: Source image. See  :cpp:func:`gpu::HOGDescriptor::detect`  for type limitations.

    :param found_locations: Detected objects boundaries.

-    :param hit_threshold: Threshold for the distance between features and SVM classifying plane. See  :func:`gpu::HOGDescriptor::detect`  for details.
+    :param hit_threshold: Threshold for the distance between features and SVM classifying plane. See  :cpp:func:`gpu::HOGDescriptor::detect`  for details.

    :param win_stride: Window stride. It must be a multiple of block stride.

@@ -185,7 +185,7 @@ gpu::HOGDescriptor::detectMultiScale

    :param scale0: Coefficient of the detection window increase.

-    :param group_threshold: Coefficient to regulate the similarity threshold. When detected, some objects can be covered by many rectangles. 0 means not to perform grouping. See  :func:`groupRectangles` .
+    :param group_threshold: Coefficient to regulate the similarity threshold. When detected, some objects can be covered by many rectangles. 0 means not to perform grouping. See  :cpp:func:`groupRectangles` .

 .. index:: gpu::HOGDescriptor::getDescriptors

@@ -197,7 +197,7 @@ gpu::HOGDescriptor::getDescriptors

    Returns block descriptors computed for the whole image. The function is mainly used to learn the classifier.

-    :param img: Source image. See  :func:`gpu::HOGDescriptor::detect`  for type limitations.
+    :param img: Source image. See  :cpp:func:`gpu::HOGDescriptor::detect`  for type limitations.

    :param win_stride: Window stride. It must be a multiple of block stride.

@@ -324,5 +324,5 @@ gpu::CascadeClassifier_GPU::detectMultiScale
    imshow("Faces", image_cpu);


-See Also: :c:func:`CascadeClassifier::detectMultiScale` 
+See Also: :c:cpp:func:`CascadeClassifier::detectMultiScale` 

--- a/modules/gpu/doc/operations_on_matrices.rst
+++ b/modules/gpu/doc/operations_on_matrices.rst
@@ -16,7 +16,7 @@ gpu::transpose
    :param dst: Destination matrix.

 See Also:
-:c:func:`transpose` 
+:c:cpp:func:`transpose` 

 .. index:: gpu::flip

@@ -40,7 +40,7 @@ gpu::flip
            

 See Also:
-:c:func:`flip` 
+:c:cpp:func:`flip` 

 .. index:: gpu::LUT

@@ -57,7 +57,7 @@ gpu::LUT
    :param dst: Destination matrix with the same depth as  ``lut``  and the same number of channels as  ``src``.
            

-See Also: :c:func:`LUT` 
+See Also: :c:cpp:func:`LUT` 

 .. index:: gpu::merge

@@ -81,7 +81,7 @@ gpu::merge

    :param stream: Stream for the asynchronous version.

-See Also: :c:func:`merge` 
+See Also: :c:cpp:func:`merge` 

 .. index:: gpu::split

@@ -103,7 +103,7 @@ gpu::split

    :param stream: Stream for the asynchronous version.

-See Also: :c:func:`split`
+See Also: :c:cpp:func:`split`

 .. index:: gpu::magnitude

@@ -128,7 +128,7 @@ gpu::magnitude
    :param stream: Stream for the asynchronous version.

 See Also:
-:c:func:`magnitude` 
+:c:cpp:func:`magnitude` 

 .. index:: gpu::magnitudeSqr

@@ -173,7 +173,7 @@ gpu::phase
    :param stream: Stream for the asynchronous version.

 See Also:
-:c:func:`phase` 
+:c:cpp:func:`phase` 

 .. index:: gpu::cartToPolar

@@ -198,7 +198,7 @@ gpu::cartToPolar
    :param stream: Stream for the asynchronous version.

 See Also:
-:c:func:`cartToPolar` 
+:c:cpp:func:`cartToPolar` 

 .. index:: gpu::polarToCart

@@ -223,4 +223,4 @@ gpu::polarToCart
    :param stream: Stream for the asynchronous version.

 See Also:
-:c:func:`polarToCart` 
+:c:cpp:func:`polarToCart` 
--- a/modules/gpu/doc/per_element_operations.rst
+++ b/modules/gpu/doc/per_element_operations.rst
@@ -21,7 +21,7 @@ gpu::add

    :param dst: Destination matrix with the same size and type as ``src1``.

-See Also: :c:func:`add`
+See Also: :c:cpp:func:`add`

 .. index:: gpu::subtract

@@ -39,7 +39,7 @@ gpu::subtract

    :param dst: Destination matrix with the same size and type as ``src1``.

-See Also: :c:func:`subtract`
+See Also: :c:cpp:func:`subtract`



@@ -59,7 +59,7 @@ gpu::multiply

    :param dst: Destination matrix with the same size and type as ``src1``.

-See Also: :c:func:`multiply`
+See Also: :c:cpp:func:`multiply`


 .. index:: gpu::divide
@@ -78,9 +78,9 @@ gpu::divide

    :param dst: Destination matrix with the same size and type as ``src1``.

-	This function, in contrast to :c:func:`divide`, uses a round-down rounding mode.
+	This function, in contrast to :c:cpp:func:`divide`, uses a round-down rounding mode.

-See Also: :c:func:`divide`
+See Also: :c:cpp:func:`divide`



@@ -96,7 +96,7 @@ gpu::exp

    :param dst: Destination matrix with the same size and type as ``src``.

-See Also: :c:func:`exp`
+See Also: :c:cpp:func:`exp`



@@ -112,7 +112,7 @@ gpu::log

    :param dst: Destination matrix with the same size and type as ``src``.

-See Also: :c:func:`log`
+See Also: :c:cpp:func:`log`



@@ -132,7 +132,7 @@ gpu::absdiff

    :param dst: Destination matrix with the same size and type as ``src1``.

-See Also: :c:func:`absdiff`
+See Also: :c:cpp:func:`absdiff`

 .. index:: gpu::compare

@@ -157,7 +157,7 @@ gpu::compare
            * **CMP_LE:** ``src1(.) <= src2(.)``
            * **CMP_NE:** ``src1(.) != src2(.)``

-See Also: :c:func:`compare`
+See Also: :c:cpp:func:`compare`


 .. index:: gpu::bitwise_not
@@ -268,7 +268,7 @@ gpu::min

    :param stream: Stream for the asynchronous version.

-See Also: :c:func:`min`
+See Also: :c:cpp:func:`min`



@@ -294,4 +294,4 @@ gpu::max

    :param stream: Stream for the asynchronous version.

-See Also: :c:func:`max`
+See Also: :c:cpp:func:`max`