Bump scikit-image from 0.24.0 to 0.25.0 in /docker/processing-image-file

[dependabot]

Bumps scikit-image from 0.24.0 to 0.25.0.

Release notes

Sourced from scikit-image's releases.

v0.25.0

scikit-image 0.25.0

We're happy to announce the release of scikit-image 0.25.0!

New Features

• Add the new Gray-Level Co-occurrence Matrix (GLCM) properties "mean", "variance", "standard deviation" and "entropy" to skimage.feature.texture.graycoprops (#7375).
• Add the new skimage.morphology.footprint_rectangle supporting generation of rectangular or hyper-rectangular footprints in one function (#7566).

API Changes

• Complete the deprecation of and remove skimage.feature.plot_matches. Use skimage.feature.plot_matched_features going forward (#7487).
• Deprecate skimage.io.imshow, skimage.io.imshow_collection and skimage.io.show. Please use matplotlib, napari, etc. to visualize images (#7508).
• Remove deprecated skimage.morphology.skeletonize_3d; use skimage.morphology.skeletonize instead (#7572).
• Deprecate skimage.io plugin infrastructure (#7353).
• Switched to using the scipy.sparse array interface. For more details, see the note about the new scipy.sparse array interface here (#7576).
• Deprecate skimage.morphology.rectangle in favor of the new function skimage.morphology.footprint_rectangle (#7566).
• Deprecate skimage.morphology.square in favor of the new function skimage.morphology.footprint_rectangle (#7566).
• Deprecate skimage.morphology.cube in favor of the new function skimage.morphology.footprint_rectangle (#7566).

Enhancements

• Improve numerical stability of skimage.morphology.local_minima for extremely small floats (#7534).
• Make sure that skimage.feature.plot_matched_features uses the same random colors, if matches_color isn't provided explicitly (#7541).
• Allow passing a sequence of colors to the parameter matches_color in skimage.feature.plot_matched_features (#7541).

Performance

• skimage.feature.peak_local_max will now skip unnecessary distance computations in the case of min_distance=1. This results in performance improvements to functions like skimage.feature.blob_dog, skimage.feature.blob_log, skimage.feature.blob_doh and skimage.feature.corner_peaks that call peak_local_max internally (#7548).
• In skimage.featurepeak_local_max, skip unnecessary check for cases where min_distance > 1 is passed (#7548).

Bug Fixes

• Ensure that skimage.morphology.remove_objects_by_distance doesn't fail if the given integer dtype cannot be safely cast to the architecture specific size of intp, e.g. on i386 architectures (#7453).
• Fix degeneracy in skimage.draw.ellipsoid_stats when all semi-axes have the same length (#7473).
• Prevent skimage.morphology.thin from accidentally modifying the input image in case it is of dtype uint8 (#7469).
• Fix numerical precision error in skimage.measure.ransac. In some cases, ransac was stopping at the first iteration (#7065).
• Fix numerical precision error in skimage.measure.ransac; very small probabilities lead to -0 number of max trials (#7496).
• Ensure that RegionProperties objects returned by skimage.measure.regionprops can be deserialized with pickle (#7569).
• Fix edge case where setting watershed_lines=True in skimage.segmentation.watershed resulted in an incorrect solution (#7071).
• Fix the behavior of skimage.segmentation.watershed when the markers don't align with local minima by making sure every marker is evaluated before successive pixels (#7071).
• Fix dtype promotion in skimage.segmentation.join_segmentations if numpy.uint is used with NumPy<2 (#7292).

Documentation

• In skimage.morphology.skeletonize, clarify the expected image dtypes and how objects of different intensities are handled (#7456).
• Fix example section in docstring of skimage.feature.graycomatrix (#7297).
• Use conda-forge consistently in instructions for setting up the development environment (#7483).
• Use new CITATION.cff instead of CITATION.bib (#7505).

... (truncated)

Changelog

Sourced from scikit-image's changelog.

How to make a new release of skimage

While following this guide, note down all the times that you need to consult a previous release manager, or that you find an instruction unclear. You will, of course, make a PR to update these notes after you are done with the release! ;-)

Before you start, make sure you have all the required write permissions (if not, you will need to ask an owner to grant you access), specifically to:

• https://pypi.org/project/scikit-image/

• https://github.com/scikit-image/skimage-web

• Check TODO.txt for any outstanding tasks.

We use a variant of "semantic versioning", where version numbers are classified as v... By default, releases are made from the main branch as part of a linear release history and, as described below, are triggered by pushing a git tag to the scikit-image repository on github. If a patch release is required, a branch can be created from the appropriate point in main and the following instructions are still apt.

Example version number

• 0.23.0rc0.dev0 # development version for 0.23.0 first release candidate
• 0.23.0rc0 # 0.23.0 first release candidate
• 0.23.0rc1.dev0 # development version for 0.23.0 second release candidate
• 0.23.0 # 0.23.0 release

Commits

• f172eba Designate 0.25.0 release
• af12cc8 Fix CI (#7631)
• 583af85 Bump version
• ee3f821 Designate 0.25.0rc2 release
• a2a80b7 Lazy load legacy imports in skimage top module (#6892)
• aa7042c Change type annotation of ball radius from int to float (#7627)
• a854ec5 Upgrade to spin 0.13 (#7622)
• 2d0c092 Add forgotten TODO about deprecated square, cube & rectangle (#7624)
• 1bd1598 Fix join_segmentations dtype error for np.uint (#7292)
• 4fb2464 Replace square, rectangle, cube with footprint_rectangle (#7566)
• Additional commits viewable in compare view

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