Documentation: fixed about 100 cross-referencing errors.

modules/gpu/doc/camera_calibration_and_3d_reconstruction.rst

@@ -193,7 +193,7 @@ gpu::StereoBeliefPropagation::StereoBeliefPropagation
 
 For more details, see [Felzenszwalb2006]_.
 
-By default, :ocv:class:`StereoBeliefPropagation` uses floating-point arithmetics and the ``CV_32FC1`` type for messages. But it can also use fixed-point arithmetics and the ``CV_16SC1`` message type for better performance. To avoid an overflow in this case, the parameters must satisfy the following requirement:
+By default, :ocv:class:`gpu::StereoBeliefPropagation` uses floating-point arithmetics and the ``CV_32FC1`` type for messages. But it can also use fixed-point arithmetics and the ``CV_16SC1`` message type for better performance. To avoid an overflow in this case, the parameters must satisfy the following requirement:
 
 .. math::
 

modules/gpu/doc/data_structures.rst

@@ -48,7 +48,7 @@ gpu::PtrStep\_
 .. ocv:class:: gpu::PtrStep\_
 
 Structure similar to 
-:ocv:class:`DevMem2D_` but containing only a pointer and row step. Width and height fields are excluded due to performance reasons. The structure is intended for internal use or for users who write device code. 
+:ocv:class:`gpu::DevMem2D_` but containing only a pointer and row step. Width and height fields are excluded due to performance reasons. The structure is intended for internal use or for users who write device code. 
 ::
 
     template<typename T> struct PtrStep_
@@ -79,7 +79,7 @@ gpu::PtrElemStrp\_
 .. ocv:class:: gpu::PtrElemStrp\_
 
 Structure similar to 
-:ocv:class:`DevMem2D_` but containing only a pointer and a row step in elements. Width and height fields are excluded due to performance reasons. This class can only be constructed if ``sizeof(T)`` is a multiple of 256. The structure is intended for internal use or for users who write device code. 
+:ocv:class:`gpu::DevMem2D_` but containing only a pointer and a row step in elements. Width and height fields are excluded due to performance reasons. This class can only be constructed if ``sizeof(T)`` is a multiple of 256. The structure is intended for internal use or for users who write device code. 
 ::
 
     template<typename T> struct PtrElemStep_ : public PtrStep_<T>
@@ -97,7 +97,7 @@ gpu::GpuMat
 .. ocv:class:: gpu::GpuMat
 
 Base storage class for GPU memory with reference counting. Its interface matches the
-:c:type:`Mat` interface with the following limitations:
+:ocv:class:`Mat` interface with the following limitations:
 
 *   
     no arbitrary dimensions support (only 2D)

modules/gpu/doc/image_filtering.rst

@@ -541,7 +541,7 @@ gpu::sepFilter2D
 
 gpu::createDerivFilter_GPU
 ------------------------------
-.. ocv:function:: Ptr<FilterEngine_GPU> createDerivFilter_GPU(int srcType, int dstType, int dx, int dy, int ksize, int rowBorderType = BORDER_DEFAULT, int columnBorderType = -1)
+.. ocv:function:: Ptr<FilterEngine_GPU> gpu::createDerivFilter_GPU(int srcType, int dstType, int dx, int dy, int ksize, int rowBorderType = BORDER_DEFAULT, int columnBorderType = -1)
 
     Creates a filter engine for the generalized Sobel operator.
 

modules/gpu/doc/image_processing.rst

@@ -278,12 +278,12 @@ gpu::ConvolveBuf::ConvolveBuf
 .. ocv:function:: ConvolveBuf::ConvolveBuf()
 
     Constructs an empty buffer that is properly resized after the first call of the 
-    :ocv:func:`convolve` function.
+    :ocv:func:`gpu::convolve` function.
 
 .. ocv:function:: ConvolveBuf::ConvolveBuf(Size image_size, Size templ_size)
 
     Constructs a buffer for the 
-    :ocv:func:`convolve` function with respective arguments.
+    :ocv:func:`gpu::convolve` function with respective arguments.
 
 
 

modules/gpu/doc/initalization_and_information.rst

@@ -7,7 +7,7 @@ Initalization and Information
 gpu::getCudaEnabledDeviceCount
 ----------------------------------
 
-.. ocv:function:: int getCudaEnabledDeviceCount()
+.. ocv:function:: int gpu::getCudaEnabledDeviceCount()
 
     Returns the number of installed CUDA-enabled devices. Use this function before any other GPU functions calls. If OpenCV is compiled without GPU support, this function returns 0.
 
@@ -15,7 +15,7 @@ gpu::getCudaEnabledDeviceCount
 
 gpu::setDevice
 ------------------
-.. ocv:function:: void setDevice(int device)
+.. ocv:function:: void gpu::setDevice(int device)
 
     Sets a device and initializes it for the current thread. If the call of this function is omitted, a default device is initialized at the fist GPU usage.
 
@@ -25,7 +25,7 @@ gpu::setDevice
 
 gpu::getDevice
 ------------------
-.. ocv:function:: int getDevice()
+.. ocv:function:: int gpu::getDevice()
 
     Returns the current device index set by ``{gpu::getDevice}`` or initialized by default.
 

modules/gpu/doc/introduction.rst

@@ -15,7 +15,7 @@ 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
-:ocv:func:`Exception` with ``CV_GpuNotSupported`` error code, except for
+:ocv:class:`Exception` with ``CV_GpuNotSupported`` error code, except for
 :ocv: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
 :ocv: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.