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Merge pull request #25785 from refmitchell:issue_25784

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Documentation update for minMaxLoc #25785

Fixes #25784

Update documentation for minMaxLoc to be more specific about when multi-channel images are and are not supported.

Testing:
Built documentation locally to check that updates were incorporated correctly.

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- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
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Robert Mitchell 2024-09-13 10:34:01 +01:00 committed by GitHub
parent c8080aa415
commit f143f45fa2
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1 changed files with 13 additions and 5 deletions
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18
modules/core/include/opencv2/core.hpp
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@ -855,13 +855,21 @@ CV_EXPORTS void normalize( const SparseMat& src, SparseMat& dst, double alpha, i
/** @brief Finds the global minimum and maximum in an array.
The function cv::minMaxLoc finds the minimum and maximum element values and their positions. The
extremums are searched across the whole array or, if mask is not an empty array, in the specified
extrema are searched across the whole array or, if mask is not an empty array, in the specified
array region.
The function do not work with multi-channel arrays. If you need to find minimum or maximum
elements across all the channels, use Mat::reshape first to reinterpret the array as
single-channel. Or you may extract the particular channel using either extractImageCOI, or
mixChannels, or split.
In C++, if the input is multi-channel, you should omit the minLoc, maxLoc, and mask arguments
(i.e. leave them as NULL, NULL, and noArray() respectively). These arguments are not
supported for multi-channel input arrays. If working with multi-channel input and you
need the minLoc, maxLoc, or mask arguments, then use Mat::reshape first to reinterpret
the array as single-channel. Alternatively, you can extract the particular channel using either
extractImageCOI, mixChannels, or split.
In Python, multi-channel input is not supported at all due to a limitation in the
binding generation process (there is no way to set minLoc and maxLoc to NULL). A
workaround is to operate on each channel individually or to use NumPy to achieve the same
functionality.
@param src input single-channel array.
@param minVal pointer to the returned minimum value; NULL is used if not required.
@param maxVal pointer to the returned maximum value; NULL is used if not required.