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Open Source Computer Vision Library
https://opencv.org/
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275 lines
11 KiB
275 lines
11 KiB
\section{Per-element Operations.} |
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\cvCppFunc{gpu::add} |
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Computes matrix-matrix or matrix-scalar sum. |
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\cvdefCpp{void add(const GpuMat\& a, const GpuMat\& b, GpuMat\& c);} |
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\begin{description} |
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\cvarg{a}{First source matrix. \texttt{CV\_8UC1}, \texttt{CV\_8UC4}, \texttt{CV\_32SC1} and \texttt{CV\_32FC1} matrices are supported for now.} |
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\cvarg{b}{Second source matrix. Must have the same size and type as \texttt{a}.} |
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\cvarg{c}{Destination matrix. Will have the same size and type as \texttt{a}.} |
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\end{description} |
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\cvdefCpp{void add(const GpuMat\& a, const Scalar\& sc, GpuMat\& c);} |
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\begin{description} |
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\cvarg{a}{Source matrix. \texttt{CV\_32FC1} and \texttt{CV\_32FC2} matrixes are supported for now.} |
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\cvarg{b}{Source scalar to be added to the source matrix.} |
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\cvarg{c}{Destination matrix. Will have the same size and type as \texttt{a}.} |
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\end{description} |
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See also: \cvCppCross{add}. |
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\cvCppFunc{gpu::subtract} |
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Subtracts matrix from another matrix (or scalar from matrix). |
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\cvdefCpp{void subtract(const GpuMat\& a, const GpuMat\& b, GpuMat\& c);} |
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\begin{description} |
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\cvarg{a}{First source matrix. \texttt{CV\_8UC1}, \texttt{CV\_8UC4}, \texttt{CV\_32SC1} and \texttt{CV\_32FC1} matrices are supported for now.} |
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\cvarg{b}{Second source matrix. Must have the same size and type as \texttt{a}.} |
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\cvarg{c}{Destination matrix. Will have the same size and type as \texttt{a}.} |
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\end{description} |
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\cvdefCpp{void subtract(const GpuMat\& a, const Scalar\& sc, GpuMat\& c);} |
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\begin{description} |
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\cvarg{a}{Source matrix. \texttt{CV\_32FC1} and \texttt{CV\_32FC2} matrixes are supported for now.} |
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\cvarg{b}{Scalar to be subtracted from the source matrix elements.} |
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\cvarg{c}{Destination matrix. Will have the same size and type as \texttt{a}.} |
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\end{description} |
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See also: \cvCppCross{subtract}. |
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\cvCppFunc{gpu::multiply} |
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Computes per-element product of two matrices (or of matrix and scalar). |
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\cvdefCpp{void multiply(const GpuMat\& a, const GpuMat\& b, GpuMat\& c);} |
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\begin{description} |
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\cvarg{a}{First source matrix. \texttt{CV\_8UC1}, \texttt{CV\_8UC4}, \texttt{CV\_32SC1} and \texttt{CV\_32FC1} matrices are supported for now.} |
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\cvarg{b}{Second source matrix. Must have the same size and type as \texttt{a}.} |
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\cvarg{c}{Destionation matrix. Will have the same size and type as \texttt{a}.} |
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\end{description} |
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\cvdefCpp{void multiply(const GpuMat\& a, const Scalar\& sc, GpuMat\& c);} |
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\begin{description} |
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\cvarg{a}{Source matrix. \texttt{CV\_32FC1} and \texttt{CV\_32FC2} matrixes are supported for now.} |
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\cvarg{b}{Scalar to be multiplied by.} |
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\cvarg{c}{Destination matrix. Will have the same size and type as \texttt{a}.} |
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\end{description} |
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See also: \cvCppCross{multiply}. |
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\cvCppFunc{gpu::divide} |
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Performs per-element division of two matrices (or division of matrix by scalar). |
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\cvdefCpp{void divide(const GpuMat\& a, const GpuMat\& b, GpuMat\& c);} |
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\begin{description} |
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\cvarg{a}{First source matrix. \texttt{CV\_8UC1}, \texttt{CV\_8UC4}, \texttt{CV\_32SC1} and \texttt{CV\_32FC1} matrices are supported for now.} |
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\cvarg{b}{Second source matrix. Must have the same size and type as \texttt{a}.} |
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\cvarg{c}{Destionation matrix. Will have the same size and type as \texttt{a}.} |
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\end{description} |
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\cvdefCpp{void divide(const GpuMat\& a, const Scalar\& sc, GpuMat\& c);} |
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\begin{description} |
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\cvarg{a}{Source matrix. \texttt{CV\_32FC1} and \texttt{CV\_32FC2} matrixes are supported for now.} |
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\cvarg{b}{Scalar to be divided by.} |
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\cvarg{c}{Destination matrix. Will have the same size and type as \texttt{a}.} |
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\end{description} |
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See also: \cvCppCross{divide}. |
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\cvCppFunc{gpu::exp} |
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Computes exponent of each matrix element. |
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\cvdefCpp{void exp(const GpuMat\& a, GpuMat\& b);} |
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\begin{description} |
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\cvarg{a}{Source matrix. \texttt{CV\_32FC1} matrixes are supported for now.} |
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\cvarg{b}{Destination matrix. Will have the same size and type as \texttt{a}.} |
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\end{description} |
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See also: \cvCppCross{exp}. |
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\cvCppFunc{gpu::log} |
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Computes natural logarithm of absolute value of each matrix element. |
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\cvdefCpp{void log(const GpuMat\& a, GpuMat\& b);} |
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\begin{description} |
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\cvarg{a}{Source matrix. \texttt{CV\_32FC1} matrixes are supported for now.} |
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\cvarg{b}{Destination matrix. Will have the same size and type as \texttt{a}.} |
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\end{description} |
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See also: \cvCppCross{log}. |
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\cvCppFunc{gpu::absdiff} |
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Computes per-element absolute difference of two matrices (or of matrix and scalar). |
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\cvdefCpp{void absdiff(const GpuMat\& a, const GpuMat\& b, GpuMat\& c);} |
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\begin{description} |
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\cvarg{a}{First source matrix. \texttt{CV\_8UC1}, \texttt{CV\_8UC4}, \texttt{CV\_32SC1} and \texttt{CV\_32FC1} matrices are supported for now.} |
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\cvarg{b}{Second source matrix. Must have the same size and type as \texttt{a}.} |
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\cvarg{c}{Destionation matrix. Will have the same size and type as \texttt{a}.} |
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\end{description} |
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\cvdefCpp{void absdiff(const GpuMat\& a, const Scalar\& s, GpuMat\& c);} |
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\begin{description} |
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\cvarg{a}{Source matrix. \texttt{CV\_32FC1} matrixes are supported for now.} |
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\cvarg{b}{Scalar to be subtracted from the source matrix elements.} |
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\cvarg{c}{Destination matrix. Will have the same size and type as \texttt{a}.} |
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\end{description} |
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See also: \cvCppCross{absdiff}. |
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\cvCppFunc{gpu::compare} |
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Compares elements of two matrices. |
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\cvdefCpp{void compare(const GpuMat\& a, const GpuMat\& b, GpuMat\& c, int cmpop);} |
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\begin{description} |
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\cvarg{a}{First source matrix. \texttt{CV\_8UC4} and \texttt{CV\_32FC1} matrices are supported for now.} |
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\cvarg{b}{Second source matrix. Must have the same size and type as \texttt{a}.} |
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\cvarg{c}{Destination matrix. Will have the same size as \texttt{a} and be \texttt{CV\_8UC1} type.} |
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\cvarg{cmpop}{Flag specifying the relation between the elements to be checked: |
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\begin{description} |
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\cvarg{CMP\_EQ}{$=$} |
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\cvarg{CMP\_GT}{$>$} |
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\cvarg{CMP\_GE}{$\ge$} |
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\cvarg{CMP\_LT}{$<$} |
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\cvarg{CMP\_LE}{$\le$} |
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\cvarg{CMP\_NE}{$\ne$} |
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\end{description} |
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} |
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\end{description} |
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See also: \cvCppCross{compare}. |
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\cvfunc{cv::gpu::bitwise\_not}\label{cppfunc.gpu.bitwise.not} |
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Performs per-element bitwise inversion. |
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\cvdefCpp{void bitwise\_not(const GpuMat\& src, GpuMat\& dst,\par |
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const GpuMat\& mask=GpuMat());\newline |
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void bitwise\_not(const GpuMat\& src, GpuMat\& dst,\par |
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const GpuMat\& mask, const Stream\& stream);} |
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\begin{description} |
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\cvarg{src}{Source matrix.} |
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\cvarg{dst}{Destination matrix. Will have the same size and type as \texttt{src}.} |
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\cvarg{mask}{Optional operation mask. 8-bit single channel image.} |
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\cvarg{stream}{Stream for the asynchronous version.} |
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\end{description} |
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See also: \hyperref[cppfunc.bitwise.not]{cv::bitwise\_not}. |
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\cvfunc{cv::gpu::bitwise\_or}\label{cppfunc.gpu.bitwise.or} |
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Performs per-element bitwise disjunction of two matrices. |
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\cvdefCpp{void bitwise\_or(const GpuMat\& src1, const GpuMat\& src2, GpuMat\& dst,\par |
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const GpuMat\& mask=GpuMat());\newline |
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void bitwise\_or(const GpuMat\& src1, const GpuMat\& src2, GpuMat\& dst,\par |
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const GpuMat\& mask, const Stream\& stream);} |
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\begin{description} |
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\cvarg{src1}{First source matrix.} |
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\cvarg{src2}{Second source matrix. It must have the same size and type as \texttt{src1}.} |
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\cvarg{dst}{Destination matrix. Will have the same size and type as \texttt{src1}.} |
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\cvarg{mask}{Optional operation mask. 8-bit single channel image.} |
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\cvarg{stream}{Stream for the asynchronous version.} |
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\end{description} |
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See also: \hyperref[cppfunc.bitwise.or]{cv::bitwise\_or}. |
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\cvfunc{cv::gpu::bitwise\_and}\label{cppfunc.gpu.bitwise.and} |
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Performs per-element bitwise conjunction of two matrices. |
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\cvdefCpp{void bitwise\_and(const GpuMat\& src1, const GpuMat\& src2, GpuMat\& dst,\par |
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const GpuMat\& mask=GpuMat());\newline |
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void bitwise\_and(const GpuMat\& src1, const GpuMat\& src2, GpuMat\& dst,\par |
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const GpuMat\& mask, const Stream\& stream);} |
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\begin{description} |
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\cvarg{src1}{First source matrix.} |
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\cvarg{src2}{Second source matrix. It must have the same size and type as \texttt{src1}.} |
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\cvarg{dst}{Destination matrix. Will have the same size and type as \texttt{src1}.} |
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\cvarg{mask}{Optional operation mask. 8-bit single channel image.} |
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\cvarg{stream}{Stream for the asynchronous version.} |
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\end{description} |
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See also: \hyperref[cppfunc.bitwise.and]{cv::bitwise\_and}. |
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\cvfunc{cv::gpu::bitwise\_xor}\label{cppfunc.gpu.bitwise.xor} |
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Performs per-element bitwise "exclusive or" of two matrices. |
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\cvdefCpp{void bitwise\_xor(const GpuMat\& src1, const GpuMat\& src2, GpuMat\& dst,\par |
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const GpuMat\& mask=GpuMat());\newline |
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void bitwise\_xor(const GpuMat\& src1, const GpuMat\& src2, GpuMat\& dst,\par |
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const GpuMat\& mask, const Stream\& stream);} |
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\begin{description} |
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\cvarg{src1}{First source matrix.} |
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\cvarg{src2}{Second source matrix. It must have the same size and type as \texttt{src1}.} |
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\cvarg{dst}{Destination matrix. Will have the same size and type as \texttt{src1}.} |
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\cvarg{mask}{Optional operation mask. 8-bit single channel image.} |
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\cvarg{stream}{Stream for the asynchronous version.} |
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\end{description} |
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See also: \hyperref[cppfunc.bitwise.xor]{cv::bitwise\_xor}. |
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\cvCppFunc{gpu::min} |
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Computes per-element minimum of two matrices (or of matrix and scalar). |
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\cvdefCpp{void min(const GpuMat\& src1, const GpuMat\& src2, GpuMat\& dst);\newline |
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void min(const GpuMat\& src1, const GpuMat\& src2, GpuMat\& dst,\par |
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const Stream\& stream);} |
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\begin{description} |
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\cvarg{src1}{First source matrix.} |
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\cvarg{src2}{Second source matrix.} |
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\cvarg{dst}{Destination matrix. Will have the same size and type as \texttt{src1}.} |
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\cvarg{stream}{Stream for the asynchronous version.} |
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\end{description} |
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\cvdefCpp{void min(const GpuMat\& src1, double src2, GpuMat\& dst);\newline |
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void min(const GpuMat\& src1, double src2, GpuMat\& dst,\par |
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const Stream\& stream);} |
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\begin{description} |
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\cvarg{src1}{Source matrix.} |
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\cvarg{src2}{Scalar to be compared with.} |
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\cvarg{dst}{Destination matrix. Will have the same size and type as \texttt{src1}.} |
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\cvarg{stream}{Stream for the asynchronous version.} |
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\end{description} |
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See also: \cvCppCross{min}. |
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\cvCppFunc{gpu::max} |
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Computes per-element maximum of two matrices (or of matrix and scalar). |
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\cvdefCpp{void max(const GpuMat\& src1, const GpuMat\& src2, GpuMat\& dst);\newline |
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void max(const GpuMat\& src1, const GpuMat\& src2, GpuMat\& dst,\par |
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const Stream\& stream);} |
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\begin{description} |
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\cvarg{src1}{First source matrix.} |
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\cvarg{src2}{Second source matrix.} |
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\cvarg{dst}{Destination matrix. Will have the same size and type as \texttt{src1}.} |
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\cvarg{stream}{Stream for the asynchronous version.} |
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\end{description} |
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\cvdefCpp{void max(const GpuMat\& src1, double src2, GpuMat\& dst);\newline |
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void max(const GpuMat\& src1, double src2, GpuMat\& dst,\par |
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const Stream\& stream);} |
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\begin{description} |
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\cvarg{src1}{Source matrix.} |
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\cvarg{src2}{Scalar to be compared with.} |
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\cvarg{dst}{Destination matrix. Will have the same size and type as \texttt{src1}.} |
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\cvarg{stream}{Stream for the asynchronous version.} |
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\end{description} |
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See also: \cvCppCross{max}. |