\cvarg{src}{Source image. Only 8UC4 images are supported for now.}
\cvarg{dst}{Destination image. Will have the same size and type as \texttt{src}. Each pixel \texttt{(x,y)} of the destination image will contain color of the converged point started from \texttt{(x,y)} pixel of the source image.}
\cvarg{sp}{Spatial window radius.}
\cvarg{sr}{Color window radius.}
\cvarg{criteria}{Termination criteria. See \hyperref[TermCriteria]{cv::TermCriteria}.}
\end{description}
\cvCppFunc{gpu::meanShiftProc}
Performs mean-shift procedure and stores information about converged points in two images..
\cvarg{src}{Source image. Only 8UC4 images are supported for now.}
\cvarg{dstr}{Destination image. Will have the same size and type as \texttt{src}. Each pixel \texttt{(x,y)} of the destination image will contain color of converged point started from \texttt{(x,y)} pixel of the source image.}
\cvarg{dstsp}{16SC2 matrix, which will contain coordinates of converged points and have the same size as \texttt{src}.}
\cvarg{sp}{Spatial window radius.}
\cvarg{sr}{Color window radius.}
\cvarg{criteria}{Termination criteria. See \hyperref[TermCriteria]{cv::TermCriteria}.}
\end{description}
\cvCppFunc{gpu::meanShiftSegmentation}
Performs mean-shift segmentation of the source image and eleminates small segments.
\cvarg{src}{Source image. Only 8UC1 and 32FC1 images are supported for now.}
\cvarg{dst}{Destination image. Will have the same size and 32FC1 type and contain cornerness values.}
\cvarg{blockSize}{Neighborhood size.}
\cvarg{ksize}{Aperture parameter for the Sobel operator.}
\cvarg{k}{Harris detector free parameter.}
\cvarg{borderType}{Pixel extrapolation method. Only \texttt{BORDER\_REFLECT101} and \texttt{BORDER\_REPLICATE} are supported for now.}
\end{description}
See also: \cvCppCross{cornerMinEigenValue}.
\cvCppFunc{gpu::mulSpectrums}
Performs per-element multiplication of two Fourier spectrums.
\cvdefCpp{void mulSpectrums(const GpuMat\& a, const GpuMat\& b,\par
GpuMat\& c, int flags, bool conjB=false);}
\begin{description}
\cvarg{a}{First spectrum.}
\cvarg{b}{Second spectrum. Must have the same size and type as \texttt{a}.}
\cvarg{c}{Destination spectrum.}
\cvarg{flags}{Mock paramter is kept for CPU/GPU interfaces similarity.}
\cvarg{conjB}{Optional flag which indicates the second spectrum must be conjugated before the multiplcation.}
\end{description}
Only full (i.e. not packed) 32FC2 complex spectrums in the interleaved format are supported for now.
See also: \cvCppCross{mulSpectrums}.
\cvCppFunc{gpu::mulAndScaleSpectrums}
Performs per-element multiplication of two Fourier spectrums and scales the result.
\cvdefCpp{void mulAndScaleSpectrums(const GpuMat\& a, const GpuMat\& b,\par
GpuMat\& c, int flags, float scale, bool conjB=false);}
\begin{description}
\cvarg{a}{First spectrum.}
\cvarg{b}{Second spectrum. Must have the same size and type as \texttt{a}.}
\cvarg{c}{Destination spectrum.}
\cvarg{flags}{Mock paramter is kept for CPU/GPU interfaces similarity.}
\cvarg{scale}{Scale constant.}
\cvarg{conjB}{Optional flag which indicates the second spectrum must be conjugated before the multiplcation.}
\end{description}
Only full (i.e. not packed) 32FC2 complex spectrums in the interleaved format are supported for now.
See also: \cvCppCross{mulSpectrums}.
\cvCppFunc{gpu::dft}
Performs a forward or inverse discrete Fourier transform (1D or 2D) of floating point matrix.
\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{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.}
\end{description}}
\end{description}
The source matrix should be continuous, otherwise reallocation and data copying will be performed. Function chooses the operation mode depending on the flags, size and channel count of the source matrix:
\begin{itemize}
\item If the source matrix is complex and the output isn't specified as real then the destination matrix will be complex, will have \texttt{dft\_size} size and 32FC2 type. It will contain full result of the DFT (forward or inverse).
\item If the source matrix is complex and the output is specified as real then function assumes that its input is the result of the forward transform (see next item). The destionation matrix will have \texttt{dft\_size} size and 32FC1 type. It will contain result of the inverse DFT.
\item If the source matrix is real (i.e. its type is 32FC1) then forward DFT will be performed. The result of the DFT will be packed into complex (32FC2) matrix so its width will be \texttt{dft\_size.width / 2 + 1}, but if the source is a single column then height will be reduced.
\end{itemize}
See also: \cvCppCross{dft}.
\cvCppFunc{gpu::convolve}
Computes convolution (or cross-correlation) of two images.
\cvarg{src\_disp}{Source disparity image. Supports \texttt{CV\_8UC1} and \texttt{CV\_16SC1} types.}
\cvarg{dst\_disp}{Output disparity image. Will have the same size as \texttt{src\_disp} and \texttt{CV\_8UC4} type in \texttt{BGRA} format (alpha = 255).}
\cvarg{ndisp}{Number of disparities.}
\cvarg{stream}{Stream fo async version.}
\end{description}
This function converts $[0..ndisp)$ interval to $[0..240, 1, 1]$ in \texttt{HSV} color space, than convert \texttt{HSV} color space to \texttt{RGB}.
\cvarg{disp}{The input single-channel 8-bit unsigned ot 16-bit signed integer disparity image.}
\cvarg{xyzw}{The output 4-channel floating-point image of the same size as \texttt{disp}. Each element of \texttt{xyzw(x,y)} will contain the 3D coordinates \texttt{(x,y,z,1)} of the point \texttt{(x,y)}, computed from the disparity map.}
\cvarg{Q}{The $4\times4$ perspective transformation matrix that can be obtained with \cvCross{StereoRectify}{stereoRectify}.}
\cvarg{stream}{Stream fo async version.}
\end{description}
See also: \cvCppCross{reprojectImageTo3D}.
\cvCppFunc{gpu::cvtColor}
Converts image from one color space to another.
\cvdefCpp{
void cvtColor(const GpuMat\& src, GpuMat\& dst, int code, int dcn = 0);
}
\cvdefCpp{
void cvtColor(const GpuMat\& src, GpuMat\& dst, int code, int dcn, \par const Stream\& stream);
\cvarg{dst}{The destination image; will have the same size and the same depth as \texttt{src}.}
\cvarg{code}{The color space conversion code.}
\cvarg{dcn}{The number of channels in the destination image; if the parameter is 0, the number of the channels will be derived automatically from \texttt{src} and the \texttt{code}.}
\cvarg{stream}{Stream fo async version.}
\end{description}
3-channels color spaces (like \texttt{HSV}, \texttt{XYZ}, etc) can be stored to 4-channels image for better perfomance.\newline
See also: \cvCppCross{cvtColor}.
\cvCppFunc{gpu::threshold}
Applies a fixed-level threshold to each array element.
\cvarg{dst}{Destination image. It will have size \texttt{dsize} (when it is non-zero) or the size computed from \texttt{src.size()} and \texttt{fx} and \texttt{fy}. The type of \texttt{dst} will be the same as of \texttt{src}.}
\cvarg{dsize}{The destination image size. If it is zero, then it is computed as: \[\texttt{dsize = Size(round(fx*src.cols), round(fy*src.rows))}\] Either \texttt{dsize} or both \texttt{fx} or \texttt{fy} must be non-zero.}
\cvarg{fx}{The scale factor along the horizontal axis. When 0, it is computed as \[\texttt{(double)dsize.width/src.cols}\]}
\cvarg{fy}{The scale factor along the vertical axis. When 0, it is computed as \[\texttt{(double)dsize.height/src.rows}\]}
\cvarg{interpolation}{The interpolation method. Supports only \texttt{INTER\_NEAREST} and \texttt{INTER\_LINEAR}.}
\end{description}
See also: \cvCppCross{resize}.
\cvCppFunc{gpu::warpAffine}
Applies an affine transformation to an image.
\cvdefCpp{
void warpAffine(const GpuMat\& src, GpuMat\& dst, const Mat\& M, \par Size dsize, int flags = INTER\_LINEAR);
}
\begin{description}
\cvarg{src}{Source image. Supports 8-bit unsigned, 16-bit unsigned, 32-bit signed amd 32-bit floating one, three and four channels images.}
\cvarg{dst}{Destination image; will have size \texttt{dsize} and the same type as \texttt{src}.}
\cvarg{M}{$2\times3$ transformation matrix.}
\cvarg{dsize}{Size of the destination image.}
\cvarg{flags}{A combination of interpolation methods, see \cvCppCross{resize}, and the optional flag \texttt{WARP\_INVERSE\_MAP} that means that \texttt{M} is the inverse transformation ($\texttt{dst}\rightarrow\texttt{src}$). Supports only \texttt{INTER\_NEAREST}, \texttt{INTER\_LINEAR} and \texttt{INTER\_CUBIC} interpolation methods.}
\end{description}
See also: \cvCppCross{warpAffine}.
\cvCppFunc{gpu::warpPerspective}
Applies a perspective transformation to an image.
\cvdefCpp{
void warpPerspective(const GpuMat\& src, GpuMat\& dst, const Mat\& M, \par Size dsize, int flags = INTER\_LINEAR);
}
\begin{description}
\cvarg{src}{Source image. Supports 8-bit unsigned, 16-bit unsigned, 32-bit signed amd 32-bit floating one, three and four channels images.}
\cvarg{dst}{Destination image; will have size \texttt{dsize} and the same type as \texttt{src}.}
\cvarg{M}{$2\times3$ transformation matrix.}
\cvarg{dsize}{Size of the destination image.}
\cvarg{flags}{A combination of interpolation methods, see \cvCppCross{resize}, and the optional flag \texttt{WARP\_INVERSE\_MAP} that means that \texttt{M} is the inverse transformation ($\texttt{dst}\rightarrow\texttt{src}$). Supports only \texttt{INTER\_NEAREST}, \texttt{INTER\_LINEAR} and \texttt{INTER\_CUBIC} interpolation methods.}
\end{description}
See also: \cvCppCross{warpPerspective}.
\cvCppFunc{gpu::rotate}
Rotates an image around the origin (0,0) and then shifts it.
\cvarg{dst}{Destination image; will have size \texttt{dsize} and the same type as \texttt{src}.}
\cvarg{dsize}{Size of the destination image.}
\cvarg{angle}{The angle of rotation in degrees.}
\cvarg{xShift}{Shift along horizontal axis.}
\cvarg{yShift}{Shift along vertical axis.}
\cvarg{interpolation}{The interpolation method. Supports only \texttt{INTER\_NEAREST}, \texttt{INTER\_LINEAR} and \texttt{INTER\_CUBIC}.}
\end{description}
See also: \cvCppCross{gpu::warpAffine}.
\cvCppFunc{gpu::copyMakeBorder}
Copies 2D array to a larger destination array and pads borders with user-specifiable constant.
\cvdefCpp{
void copyMakeBorder(const GpuMat\& src, GpuMat\& dst, \par int top, int bottom, int left, int right, \par const Scalar\& value = Scalar());
}
\begin{description}
\cvarg{src}{The source image. Supports \texttt{CV\_8UC1}, \texttt{CV\_8UC4}, \texttt{CV\_32SC1} and \texttt{CV\_32FC1} types.}
\cvarg{dst}{The destination image; will have the same type as \texttt{src} and the size \texttt{Size(src.cols+left+right, src.rows+top+bottom)}.}
\cvarg{top, bottom, left, right}{Specify how much pixels in each direction from the source image rectangle one needs to extrapolate, e.g. \texttt{top=1, bottom=1, left=1, right=1} mean that 1 pixel-wide border needs to be built.}
\cvarg{value}{The border value.}
\end{description}
See also: \cvCppCross{copyMakeBorder}
\cvCppFunc{gpu::rectStdDev}
Computes the standard deviation of integral images.
\cvarg{src}{The source image. Supports only \texttt{CV\_32SC1} type.}
\cvarg{sqr}{The squared source image. Supports only \texttt{CV\_32FC1} type.}
\cvarg{dst}{The destination image; will have the same type and the same size as \texttt{src}.}
\cvarg{rect}{Rectangular window.}
\end{description}
\cvCppFunc{gpu::evenLevels}
Compute levels with even distribution.
\cvdefCpp{
void evenLevels(GpuMat\& levels, int nLevels, \par int lowerLevel, int upperLevel);
}
\begin{description}
\cvarg{levels}{The destination array. \texttt{levels} will have 1 row and \texttt{nLevels} cols and \texttt{CV\_32SC1} type.}
\cvarg{nLevels}{The number of levels being computed. \texttt{nLevels} must be at least 2}
\cvarg{lowerLevel}{Lower boundary value of the lowest level.}
\cvarg{upperLevel}{Upper boundary value of the greatest level.}
\end{description}
\cvCppFunc{gpu::histEven}
Calculates histogram with evenly distributed bins.
\cvdefCpp{
void histEven(const GpuMat\& src, GpuMat\& hist, \par int histSize, int lowerLevel, int upperLevel);
}
\cvdefCpp{
void histEven(const GpuMat\& src, GpuMat hist[4], \par int histSize[4], int lowerLevel[4], int upperLevel[4]);
}
\begin{description}
\cvarg{src}{The source image. Supports 8-bit unsigned, 16-bit unsigned and 16-bit one or four channel images. For four channels image all channels are processed separately.}
\cvarg{hist}{Destination histogram. Will have one row, \texttt{histSize} cols and \texttt{CV\_32S} type.}
\cvarg{histSize}{Size of histogram.}
\cvarg{lowerLevel}{Lower boundary of lowest level bin.}
\cvarg{upperLevel}{Upper boundary of highest level bin.}
\end{description}
\cvCppFunc{gpu::histRange}
Calculates histogram with bins determined by levels array.
\cvarg{src}{The source image. Supports 8-bit unsigned, 16-bit unsigned and 16-bit one or four channel images. For four channels image all channels are processed separately.}
\cvarg{hist}{Destination histogram. Will have one row, \texttt{(levels.cols-1)} cols and \texttt{CV\_32SC1} type.}
