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Merge pull request #8887 from krishraghuram:gpu_reduce_doc

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Modified doc for gpu::reduce(fixes issue 8628)
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Alexander Alekhin
2017-06-10 22:27:17 +02:00
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parent 01e34b6a91 d0f3a14456
commit 3649ee3cd3
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modules/gpu/doc/matrix_reductions.rst
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@@ -186,9 +186,9 @@ Reduces a matrix to a vector.
:param mtx: Source 2D matrix.
:param vec: Destination vector. Its size and type is defined by ``dim`` and ``dtype`` parameters.
:param vec: Destination row vector. Its type is defined by ``dtype`` parameter.
:param dim: Dimension index along which the matrix is reduced. 0 means that the matrix is reduced to a single row. 1 means that the matrix is reduced to a single column.
:param 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.
:param reduceOp: Reduction operation that could be one of the following:
@@ -202,6 +202,6 @@ Reduces a matrix to a vector.
:param 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 row/column is obtained. 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.
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.
.. seealso:: :ocv:func:`reduce`