Matrix Reductions

gpu::meanStdDev

Computes a mean value and a standard deviation of matrix elements.

C++: void gpu::meanStdDev(const GpuMat& mtx, Scalar& mean, Scalar& stddev)
C++: void gpu::meanStdDev(const GpuMat& mtx, Scalar& mean, Scalar& stddev, GpuMat& buf)
Parameters:
  • mtx – Source matrix. CV_8UC1 matrices are supported for now.
  • mean – Mean value.
  • stddev – Standard deviation value.
  • buf – Optional buffer to avoid extra memory allocations. It is resized automatically.

See also

meanStdDev()

gpu::norm

Returns the norm of a matrix (or difference of two matrices).

C++: double gpu::norm(const GpuMat& src1, int normType=NORM_L2)
C++: double gpu::norm(const GpuMat& src1, int normType, GpuMat& buf)
C++: double gpu::norm(const GpuMat& src1, int normType, const GpuMat& mask, GpuMat& buf)
C++: double gpu::norm(const GpuMat& src1, const GpuMat& src2, int normType=NORM_L2)
Parameters:
  • src1 – Source matrix. Any matrices except 64F are supported.
  • src2 – Second source matrix (if any) with the same size and type as src1.
  • normType – Norm type. NORM_L1 , NORM_L2 , and NORM_INF are supported for now.
  • mask – optional operation mask; it must have the same size as src1 and CV_8UC1 type.
  • buf – Optional buffer to avoid extra memory allocations. It is resized automatically.

See also

norm()

gpu::sum

Returns the sum of matrix elements.

C++: Scalar gpu::sum(const GpuMat& src)
C++: Scalar gpu::sum(const GpuMat& src, GpuMat& buf)
C++: Scalar gpu::sum(const GpuMat& src, const GpuMat& mask, GpuMat& buf)
Parameters:
  • src – Source image of any depth except for CV_64F .
  • mask – optional operation mask; it must have the same size as src1 and CV_8UC1 type.
  • buf – Optional buffer to avoid extra memory allocations. It is resized automatically.

See also

sum()

gpu::absSum

Returns the sum of absolute values for matrix elements.

C++: Scalar gpu::absSum(const GpuMat& src)
C++: Scalar gpu::absSum(const GpuMat& src, GpuMat& buf)
C++: Scalar gpu::absSum(const GpuMat& src, const GpuMat& mask, GpuMat& buf)
Parameters:
  • src – Source image of any depth except for CV_64F .
  • mask – optional operation mask; it must have the same size as src1 and CV_8UC1 type.
  • buf – Optional buffer to avoid extra memory allocations. It is resized automatically.

gpu::sqrSum

Returns the squared sum of matrix elements.

C++: Scalar gpu::sqrSum(const GpuMat& src)
C++: Scalar gpu::sqrSum(const GpuMat& src, GpuMat& buf)
C++: Scalar gpu::sqrSum(const GpuMat& src, const GpuMat& mask, GpuMat& buf)
Parameters:
  • src – Source image of any depth except for CV_64F .
  • mask – optional operation mask; it must have the same size as src1 and CV_8UC1 type.
  • buf – Optional buffer to avoid extra memory allocations. It is resized automatically.

gpu::minMax

Finds global minimum and maximum matrix elements and returns their values.

C++: void gpu::minMax(const GpuMat& src, double* minVal, double* maxVal=0, const GpuMat& mask=GpuMat())
C++: void gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask, GpuMat& buf)
Parameters:
  • src – Single-channel source image.
  • minVal – Pointer to the returned minimum value. Use NULL if not required.
  • maxVal – Pointer to the returned maximum value. Use NULL if not required.
  • mask – Optional mask to select a sub-matrix.
  • buf – Optional buffer to avoid extra memory allocations. It is resized automatically.

The function does not work with CV_64F images on GPUs with the compute capability < 1.3.

See also

minMaxLoc()

gpu::minMaxLoc

Finds global minimum and maximum matrix elements and returns their values with locations.

C++: void gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal=0, Point* minLoc=0, Point* maxLoc=0, const GpuMat& mask=GpuMat())
C++: void gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc, const GpuMat& mask, GpuMat& valbuf, GpuMat& locbuf)
Parameters:
  • src – Single-channel source image.
  • minVal – Pointer to the returned minimum value. Use NULL if not required.
  • maxVal – Pointer to the returned maximum value. Use NULL if not required.
  • minLoc – Pointer to the returned minimum location. Use NULL if not required.
  • maxLoc – Pointer to the returned maximum location. Use NULL if not required.
  • mask – Optional mask to select a sub-matrix.
  • valbuf – Optional values buffer to avoid extra memory allocations. It is resized automatically.
  • locbuf – Optional locations buffer to avoid extra memory allocations. It is resized automatically.

The function does not work with CV_64F images on GPU with the compute capability < 1.3.

See also

minMaxLoc()

gpu::countNonZero

Counts non-zero matrix elements.

C++: int gpu::countNonZero(const GpuMat& src)
C++: int gpu::countNonZero(const GpuMat& src, GpuMat& buf)
Parameters:
  • src – Single-channel source image.
  • buf – Optional buffer to avoid extra memory allocations. It is resized automatically.

The function does not work with CV_64F images on GPUs with the compute capability < 1.3.

See also

countNonZero()

gpu::reduce

Reduces a matrix to a vector.

C++: void gpu::reduce(const GpuMat& mtx, GpuMat& vec, int dim, int reduceOp, int dtype=-1, Stream& stream=Stream::Null())
Parameters:
  • mtx – Source 2D matrix.
  • vec – Destination row vector. Its type is defined by dtype parameter.
  • dim – Dimension index along which the matrix is reduced. 0 means that the matrix is reduced to a single row(of length equal to number of matrix columns). 1 means that the matrix is reduced to a single column(of length equal to the number of matrix rows). In either case, the output is always stored as a row vector of appropriate length.
  • reduceOp

    Reduction operation that could be one of the following:

    • CV_REDUCE_SUM The output is the sum of all rows/columns of the matrix.
    • CV_REDUCE_AVG The output is the mean vector of all rows/columns of the matrix.
    • CV_REDUCE_MAX The output is the maximum (column/row-wise) of all rows/columns of the matrix.
    • CV_REDUCE_MIN The output is the minimum (column/row-wise) of all rows/columns of the matrix.
  • dtype – When it is negative, the destination vector will have the same type as the source matrix. Otherwise, its type will be CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), mtx.channels()) .

The function reduce reduces the matrix to a vector by treating the matrix rows/columns as a set of 1D vectors and performing the specified operation on the vectors until a single column/row is obtained. However, the result is always stored as a row vector. For example, the function can be used to compute horizontal and vertical projections of a raster image. In case of CV_REDUCE_SUM and CV_REDUCE_AVG , the output may have a larger element bit-depth to preserve accuracy. And multi-channel arrays are also supported in these two reduction modes.

See also

reduce()