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Merge pull request #13879 from chacha21:REDUCE_SUM2

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add REDUCE_SUM2 #13879 

proposal to add REDUCE_SUM2 to cv::reduce, an operation that sums up the square of elements
This commit is contained in:
Pierre Chatelier
2023-04-28 19:42:52 +02:00
committed by GitHub
parent 23b819efb8
commit 6dd8a9b6ad
9 changed files with 254 additions and 92 deletions
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modules/core/include/opencv2/core.hpp
+3 -2
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@@ -230,7 +230,8 @@ enum KmeansFlags {
enum ReduceTypes { REDUCE_SUM = 0, //!< the output is the sum of all rows/columns of the matrix.
REDUCE_AVG = 1, //!< the output is the mean vector of all rows/columns of the matrix.
REDUCE_MAX = 2, //!< the output is the maximum (column/row-wise) of all rows/columns of the matrix.
REDUCE_MIN = 3 //!< the output is the minimum (column/row-wise) of all rows/columns of the matrix.
REDUCE_MIN = 3, //!< the output is the minimum (column/row-wise) of all rows/columns of the matrix.
REDUCE_SUM2 = 4 //!< the output is the sum of all squared rows/columns of the matrix.
};
//! @} core_array
@@ -903,7 +904,7 @@ The function #reduce reduces the matrix to a vector by treating the matrix rows/
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 #REDUCE_MAX and #REDUCE_MIN , the output image should have the same type as the source one.
In case of #REDUCE_SUM and #REDUCE_AVG , the output may have a larger element bit-depth to preserve accuracy.
In case of #REDUCE_SUM, #REDUCE_SUM2 and #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 following code demonstrates its usage for a single channel matrix.