[SciPy-User] [ANN] scikit-image 0.17 release

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[SciPy-User] [ANN] scikit-image 0.17 release

Emmanuelle Gouillart
Announcement: scikit-image 0.17.1

We're happy to announce the release of scikit-image v0.17.1!

scikit-image is an image processing toolbox for SciPy that includes
algorithms for segmentation, geometric transformations, color space
manipulation, analysis, filtering, morphology, feature detection, and

For more information, examples, and documentation, please visit our


Many thanks to the 54 authors who contributed the amazing number of 213
merged pull requests! scikit-image is a community-based project and we
are happy that this number includes first-time contributors to

Special thanks for the release to the Cython team, who helped us make our
code compatible with their coming Cython 3.0 release. The full release
notes are available on

Please report any bug reports or suggestions on
https://github.com/scikit-image/scikit-image/issues/new. Community
support is available on https://forum.image.sc/tag/scikit-image.

New Features

- Hyperparameter calibration of denoising algorithms with
  `restoration.calibrate_denoiser` (#3824), with corresponding gallery
example and tutorial.

- `util.map_array` was introduced to map a set of pixel values to another
  one (for example to map region labels to the size of regions in an
image of labels) #4612 and #4646

- `measure.profile_line` has a new `reduce_func` parameter to accept a
  reduction operation to be computed on pixel values along the profile

- nD windows for reducing spectral leakage when computing the FFT of
  n-dimensional images, with `filters.window` (#4252) (with new gallery

- Add Minkowski distance metric support to corner_peak (#4218)

- Masked marching cubes (#3829)

- The SLIC superpixel algorithm now accepts a mask to exclude some parts
  of the image and force the superpixel boundaries to follow the boundary
of the mask (#3850)

- Pooch -- on the fly download of datasets from github: we introduced the
  possibility to include larger datasets in the `data` submodule, thanks
to the `pooch` library. `data.download_all` fetches all datasets. (#3945)

- Starting with this version, our gallery examples now have links to run
  the example notebook on a binder instance. (#4543)

New doc tutorials and gallery examples have been added to the use of
regionprops_table (#4348) geometrical transformations (#4385), and the
registration of rotation and scaling with no shared center (#4515). A new
section on registration has been added to the gallery (#4575).

For the full list of improvements, bug fixes and API changes, and the
list of authors and reviewers, please see

Emma, for the scikit-image team
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