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gpu docs minor changes

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This commit is contained in:
Alexey Spizhevoy 2011-01-17 11:34:20 +00:00
parent cb63046dcf
commit 47b6f19766
4 changed files with 24 additions and 23 deletions
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26
doc/gpu_image_processing.tex
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@ -19,7 +19,7 @@ Performs mean-shift filtering.
\cvCppFunc{gpu::meanShiftProc}
Performs mean-shift procedure and stores information about converged points in two images..
Performs mean-shift procedure and stores information about converged points in two images.
\cvdefCpp{void meanShiftProc(const GpuMat\& src, GpuMat\& dstr, GpuMat\& dstsp,\par
int sp, int sr,\par
@ -55,7 +55,7 @@ Performs mean-shift segmentation of the source image and eleminates small segmen
\cvCppFunc{gpu::integral}
Computes the integral image and squared integral image.
Computes integral image and squared integral image.
\cvdefCpp{void integral(const GpuMat\& src, GpuMat\& sum);\newline
void integral(const GpuMat\& src, GpuMat\& sum, GpuMat\& sqsum);}
@ -172,15 +172,15 @@ Performs a forward or inverse discrete Fourier transform (1D or 2D) of floating
\cvdefCpp{void dft(const GpuMat\& src, GpuMat\& dst, Size dft\_size, int flags=0);}
\begin{description}
\cvarg{src}{Real of complex source matrix.}
\cvarg{dst}{Real or complex destination matrix.}
\cvarg{src}{Source matrix (real or complex).}
\cvarg{dst}{Destination matrix (real or complex).}
\cvarg{dft\_size}{Size of discrete Fourier transform.}
\cvarg{flags}{Optional flags:
\begin{description}
\cvarg{DFT\_ROWS}{Transform each individual row of the source matrix.}
\cvarg{DFT\_SCALE}{Scale the result: divide it by the number of elements in the transform (it's obtained from \texttt{dft\_size}).
\cvarg{DFT\_INVERSE}{Inverse DFT must be perfromed for complex-complex case (real-complex and complex-real cases are respectively forward and inverse always).}}
\cvarg{DFT\_REAL\_OUTPUT}{The source matrix is the result of real-complex transform and the destination matrix must be real.}
\cvarg{DFT\_INVERSE}{Inverse DFT must be perfromed for complex-complex case (real-complex and complex-real cases are respectively forward and inverse always).}}
\cvarg{DFT\_REAL\_OUTPUT}{The source matrix is the result of real-complex transform, so the destination matrix must be real.}
\end{description}}
\end{description}
@ -231,14 +231,14 @@ private:
\cvCppFunc{gpu::ConvolveBuf::ConvolveBuf}
\cvdefCpp{ConvolveBuf();}
Construct empty buffer which will be properly resized after first call of the convolve function.
Constructs an empty buffer which will be properly resized after first call of the convolve function.
\cvdefCpp{ConvolveBuf(Size image\_size, Size templ\_size);}
Construct buffer for the convolve function with respectively arguments.
Constructs a 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.
Computes a proximity map for a raster template and an image where the template is searched for.
\cvdefCpp{void matchTemplate(const GpuMat\& image, const GpuMat\& templ,\par
GpuMat\& result, int method);}
@ -246,15 +246,15 @@ Computes the proximity map for the raster template and the image where the templ
\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
\cvarg{result}{Map containing 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.}
\cvarg{method}{Specifies the way which the template must be compared with the image.}
\end{description}
Following methods are supported for 8U images for now:
Following methods are supported for the 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}
Following methods are supported for 32F images for now:
Following methods are supported for the 32F images for now:
\begin{itemize}
\item CV\_TM\_SQDIFF \item CV\_TM\_CCORR
\end{itemize}

6
doc/gpu_initialization.tex
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@ -42,7 +42,7 @@ Returns number of Streaming Multiprocessors for given device.
\cvCppFunc{gpu::getGpuMemInfo}
Returns free and total memory for current device.
Returns free and total memory for the current device.
\cvdefCpp{void getGpuMemInfo(size\_t\& free, size\_t\& total);}
\begin{description}
@ -52,7 +52,7 @@ Returns free and total memory for current device.
\cvCppFunc{gpu::hasNativeDoubleSupport}
Returns true if current GPU has native double support, false otherwise.
Returns true if the specified GPU has native double support, false otherwise.
\cvdefCpp{bool hasNativeDoubleSupport(int device);}
\begin{description}
@ -61,7 +61,7 @@ Returns true if current GPU has native double support, false otherwise.
\cvCppFunc{gpu::hasAtomicsSupport}
Returns true if current GPU has atomics support, false otherwise.
Returns true if the specified GPU has atomics support, false otherwise.
\cvdefCpp{bool hasAtomicsSupport(int device);}
\begin{description}

12
doc/gpu_matrix_operations.tex
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@ -2,7 +2,7 @@
\cvCppFunc{gpu::transpose}
Transposes the matrix.
Transposes a matrix.
\cvdefCpp{void transpose(const GpuMat\& src, GpuMat\& dst);}
\begin{description}
@ -32,7 +32,7 @@ See also: \cvCppCross{flip}.
\cvCppFunc{gpu::LUT}
Transforms source matrix into destination matrix using given look-up table: \texttt{dst(I) = lut(src(I))}.
Transforms the source matrix into the destination matrix using given look-up table: \texttt{dst(I) = lut(src(I))}.
\cvdefCpp{void LUT(const GpuMat\& src, const Mat\& lut, GpuMat\& dst);}
\begin{description}
@ -45,7 +45,7 @@ See also: \cvCppCross{LUT}.
\cvCppFunc{gpu::merge}
Makes multi-channel matrix out of several single-channel matrices.
Makes a multi-channel matrix out of several single-channel matrices.
\cvdefCpp{void merge(const GpuMat* src, size\_t n, GpuMat\& dst);\newline
void merge(const GpuMat* src, size\_t n, GpuMat\& dst,\par
@ -93,7 +93,7 @@ See also: \cvCppCross{split}.
\cvCppFunc{gpu::magnitude}
Computes magnitude of complex vector.
Computes magnitudes of complex matrix elements.
\cvdefCpp{void magnitude(const GpuMat\& x, GpuMat\& magnitude);}
\begin{description}
@ -115,7 +115,7 @@ See also: \cvCppCross{magnitude}.
\cvCppFunc{gpu::magnitudeSqr}
Computes squared magnitude of complex vector.
Computes squared magnitudes of complex matrix elements.
\cvdefCpp{void magnitudeSqr(const GpuMat\& x, GpuMat\& magnitude);}
\begin{description}
@ -135,7 +135,7 @@ void magnitudeSqr(const GpuMat\& x, const GpuMat\& y, GpuMat\& magnitude,\par
\cvCppFunc{gpu::phase}
Computes polar angle of each complex value.
Computes polar angles of complex matrix elements.
\cvdefCpp{void phase(const GpuMat\& x, const GpuMat\& y, GpuMat\& angle,\par
bool angleInDegrees=false);\newline

3
doc/gpu_matrix_reductions.tex
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@ -23,7 +23,8 @@ Returns norm of matrix (or of two matrices difference).
\cvarg{normType}{Norm type. \texttt{NORM\_L1}, \texttt{NORM\_L2} and \texttt{NORM\_INF} are supported for now.}
\end{description}
\cvdefCpp{double norm(const GpuMat\& src1, const GpuMat\& src2, int normType=NORM\_L2);}
\cvdefCpp{double norm(const GpuMat\& src1, const GpuMat\& src2,\par
int normType=NORM\_L2);}
\begin{description}
\cvarg{src1}{First source matrix. 8UC1 matrices are supported for now.}
\cvarg{src2}{Second source matrix. Must have the same size and type as \texttt{src1}}.