updated gpu module docs

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Alexey Spizhevoy 2011-01-13 12:26:15 +00:00
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\ifCpp \ifCpp
\section{Initalization and Info}
\cvCppFunc{gpu::hasNativeDoubleSupport}
Returns true if current GPU has native double support, false otherwise.
\cvdefCpp{bool hasNativeDoubleSupport(int device);}
\cvCppFunc{gpu::hasAtomicsSupport}
Returns true if current GPU has atomics support, false otherwise.
\cvdefCpp{bool hasAtomicsSupport(int device);}
\section{Data Structures}
\cvCppFunc{gpu::createContinuous}
Creates continuous matrix in GPU memory.
\cvdefCpp{void createContinuous(int rows, int cols, int type, GpuMat\& m);}
\begin{description}
\cvarg{rows}{Row count.}
\cvarg{cols}{Column count.}
\cvarg{type}{Type of the matrix.}
\cvarg{m}{Destionation matrix. Will do only reshape if \texttt{m} has proper type and area ($rows \times cols$).}
\end{description}
\section{Per-element Operations} \section{Per-element Operations}
@ -312,6 +342,49 @@ Construct empty buffer which will be properly resized after first call of the co
Construct buffer for the convolve function with respectively arguments. Construct buffer for the convolve function with respectively arguments.
\cvCppFunc{gpu::matchTemplate}
Computes the proximity map for the raster template and the image where the template is searched for.
\cvdefCpp{void matchTemplate(const GpuMat\& image, const GpuMat\& templ,\par
GpuMat\& result, int method);}
\begin{description}
\cvarg{image}{Source image. 32F and 8U images (1..4 channels) are supported for now.}
\cvarg{templ}{Template image. Must have the same size and type as \texttt{image}.}
\cvarg{result}{A map of comparison results (32FC1). If \texttt{image} is $W \times H$ and
\texttt{templ} is $w \times h$ then \texttt{result} must be $(W-w+1) \times (H-h+1)$.}
\cvarg{method}{Specifies the way the template must be compared with the image.}
\end{description}
Following methods are supported for 8U images for now:
\begin{itemize}
\item CV\_TM\_SQDIFF \item CV\_TM\_SQDIFF\_NORMED \item CV\_TM\_CCORR \item CV\_TM\_CCORR\_NORMED \item CV\_TM\_CCOEFF \item CV\_TM\_CCOEFF\_NORMED
\end{itemize}\par
Following methods are supported for 32F images for now:
\begin{itemize}
\item CV\_TM\_SQDIFF \item CV\_TM\_CCORR
\end{itemize}
See also: \cvCppCross{matchTemplate}.
\section{Matrix Reductions}
\cvCppFunc{gpu::sum}
Computes sum of array elements.
\cvdefCpp{Scalar sum(const GpuMat\& src);\newline
Scalar sum(const GpuMat\& src, GpuMat\& buf);}
\begin{description}
\cvarg{src}{Source image of any depth excepting 64F, single-channel.}
\cvarg{buf}{Optional buffer. It's resized automatically.}
\end{description}
See also: \cvCppCross{sum}.
\section{Object Detection} \section{Object Detection}

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