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 more. For more information, examples, and documentation, please visit our website: https://scikit-image.org 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 scikit-image. 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 https://scikit-image.org/docs/stable/release_notes_and_installation.html?hig... 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 (#4206) - nD windows for reducing spectral leakage when computing the FFT of n-dimensional images, with `filters.window` (#4252) (with new gallery example) - 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 https://scikit-image.org/docs/stable/release_notes_and_installation.html?hig... Emma, for the scikit-image team