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build(deps): bump scikit-image from 0.24.0 to 0.25.0 #1599

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Dec 16, 2024

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@dependabot dependabot bot commented on behalf of github Dec 16, 2024

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:

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
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Bumps [scikit-image](https://github.com/scikit-image/scikit-image) from 0.24.0 to 0.25.0.
- [Release notes](https://github.com/scikit-image/scikit-image/releases)
- [Changelog](https://github.com/scikit-image/scikit-image/blob/main/RELEASE.txt)
- [Commits](scikit-image/scikit-image@v0.24.0...v0.25.0)

---
updated-dependencies:
- dependency-name: scikit-image
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot bot added dependencies Pull requests that update a dependency file python Pull requests that update Python code labels Dec 16, 2024
@paulschreiber paulschreiber merged commit 0eabe61 into main Dec 16, 2024
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@paulschreiber paulschreiber deleted the dependabot/pip/scikit-image-0.25.0 branch December 16, 2024 22:15
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