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TUN proposed to organize a sprint in december in Hanoi. Our objective is gather devs who are already familiar with scikit-image and our dev tools to progress on some PR.
At least, the group will be composed of TUN, Thomas Walter, and myself. If you would like to join (physically in Hanoi or remotely), you are welcome. Our github might experience a higher
activity, don't be surprised.
Let us know if you would like to join. If some of you want to participate remotely, we will do our best to communicate on the chat.
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I apologize for the cross posting. This is a reminder for the John Hunter
Excellence in Plotting Contest.
In memory of John Hunter, we are pleased to announce the John Hunter
Excellence in Plotting Contest for 2020. This open competition aims to
highlight the importance of data visualization to scientific progress and
showcase the capabilities of open source software.
Participants are invited to submit scientific plots to be judged by a
panel. The winning entries will be announced and displayed at SciPy 2020 or
announced in the John Hunter Excellence in Plotting Contest website and
John Hunter’s family are graciously sponsoring cash prizes for the winners
in the following amounts:
1st prize: $1000
2nd prize: $750
3rd prize: $500
Entries must be submitted by June 1st to the form at
Winners will be announced at Scipy 2020 in Austin, TX or publicly on the
John Hunter Excellence in Plotting Contest website and youtube channel
Participants do not need to attend the Scipy conference.
Entries may take the definition of “visualization” rather broadly.
Entries may be, for example, a traditional printed plot, an interactive
visualization for the web, a dashboard, or an animation.
Source code for the plot must be provided, in the form of Python code
and/or a Jupyter notebook, along with a rendering of the plot in a widely
used format. The rendering may be, for example, PDF for print, standalone
original data can not be shared for reasons of size or licensing, "fake"
data may be substituted, along with an image of the plot using real data.
Each entry must include a 300-500 word abstract describing the plot and
its importance for a general scientific audience.
Entries will be judged on their clarity, innovation and aesthetics, but
most importantly for their effectiveness in communicating a real-world
problem. Entrants are encouraged to submit plots that were used during the
course of research or work, rather than merely being hypothetical.
SciPy and the John Hunter Excellence in Plotting Contest organizers
reserves the right to display any and all entries, whether prize-winning or
not, at the conference, use in any materials or on its website, with
attribution to the original author(s).
Past entries can be found at https://jhepc.github.io/
Questions regarding the contest can be sent to jhepc.organizers(a)gmail.com
John Hunter Excellence in Plotting Contest Co-Chairs
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
support is available on https://forum.image.sc/tag/scikit-image.
- Hyperparameter calibration of denoising algorithms with
`restoration.calibrate_denoiser` (#3824), with corresponding
gallery example and tutorial.
- `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)
- `util.map_array` was introduced to map a set of pixel values to another
(for example to map region labels to the size of regions in an image of
labels) #4612 and #4646
- Masked marching cubes (#3829)
- The SLIC superpixel algorithm now accepts a mask to exclude some parts
image and force the superpixel boundaries to follow the boundary of the
- Pooch -- on the fly download of datasets from github: we introduced the
possibility to include larger datasets in the `data` submodule, thanks
`pooch` library. `data.download_all` fetches all datasets. (#3945)
- Starting with this version, our gallery examples now have links to run
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).
- scikit-image aims at being fully compatible with 3D arrays, and when
with nD arrays. nD support has been added to color conversion functions
(#4418), to the CLAHE `exposure.equalize_adapthist` algorithm (#4598)
and to the Sobel, Scharr, and Prewitt filters (#4347).
- Multichannel support for denoise_tv_bregman (#4446)
- The memory footprint of `segmentation.relabel_sequential` has been
the case of labels much larger than the number of labels (#4612)
- Random ellipses are now possible in `draw.random_shapes` (#4493)
- Add border conditions to ridge filters (#4396)
- `segmentation.random_walker` new Jacobi preconditioned conjugate
(#4359) and minor corrections #4630
- Warn when rescaling with NaN in exposure.intensity_range (#4265)
We have also improved the consistency of several functions regarding the
way they handle data types
- Make dtype consistent in filters.rank functions (#4289)
- Fix colorconv float32 to double cast (#4296)
- Prevent radon from upcasting float32 arrays to double (#4297)
- Manage iradon_sart input and output data type (#4300)
- When used with floating point inputs, ``denoise_wavelet`` no longer
the range of the data or clips the output to the range [0, 1] or [-1,
For non-float inputs, rescaling and clipping still occurs as in prior
releases (although with a bugfix related to the scaling of ``sigma``).
- For 2D input, edge filters (Sobel, Scharr, Prewitt, Roberts, and Farid)
no longer set the boundary pixels to 0 when a mask is not supplied.
changed because the boundary mode for `scipy.ndimage.convolve` is now
``'reflect'``, which allows meaningful values at the borders for these
filters. To retain the old behavior, pass
``mask=np.ones(image.shape, dtype=bool)`` (#4347)
- When ``out_range`` is a range of numbers and not a dtype in
:func:`skimage.exposure.rescale_intensity`, the output data type will
be float (#4585)
- The values returned by :func:`skimage.exposure.equalize_adapthist` will
slightly different from previous versions due to different rounding
- Move masked_register_translation from feature to registration (#4503)
- Move register_translation from skimage.feature to skimage.registration
- Move watershed from morphology to segmentation (#4443)
- Rename draw.circle() to draw.disk() (#4428)
- The forward and backward maps returned by
are no longer NumPy arrays, but more memory-efficient `ArrayMap`
objects that behave
the same way for mapping. See the ``relabel_sequential`` documentation
for more details.
To get NumPy arrays back, cast it as a NumPy array:
- ``denoise_wavelet``: For user-supplied `sigma`, if the input image gets
rescaled via ``img_as_float``, the same scaling will be applied to
preserve the relative scale of the noise estimate. To restore the old,
behaviour, the user can manually specify ``rescale_sigma=False``.
- Fix Frangi artefacts around the image (#4343)
- Fix Negative eigenvalue in inertia_tensor_eigvals due to floating point
- Fix morphology.flood for F-ordered images (#4556)
- Fix h_maxima/minima strange behaviors on floating point image input
- Fix peak_local_max coordinates ordering (#4501)
- Sort naturally peaks coordinates of same amplitude in peak_local_max
- Fix denoise_nl_means data type management (#4322)
- Update rescale_intensity to prevent under/overflow and produce proper
output dtype (#4585)
(other small bug fixes are part of the list of other pull requests at the
The minimal supported Python version by this release is 3.6.
- Parameter ``inplace`` in skimage.morphology.flood_fill has been
in favor of ``in_place`` and will be removed in version scikit-image
- ``skimage.segmentation.circle_level_set`` has been deprecated and will
removed in 0.19. Use ``skimage.segmentation.disk_level_set`` instead.
- ``skimage.draw.circle`` has been deprecated and will be removed in
Use ``skimage.draw.disk`` instead.
- Deprecate filter argument in iradon due to clash with python keyword
- Deprecate marching_cubes_classic (#4287)
- Change label2rgb default background value from -1 to 0 (#4614)
- Deprecate rgb2grey and grey2rgb (#4420)
- Complete deprecation of circle in morphsnakes (#4467)
- Deprecate non RGB image conversion in rgb2gray (#4838, #4439), and
non gray scale image conversion in gray2rgb (#4440)
54 authors added to this release [alphabetical by first name or login]
- aadideshpande (aadideshpande)
- Alexandre de Siqueira
- Asaf Kali
- D-Bhatta (D-Bhatta)
- Davis Bennett
- Dhiren Serai
- Dylan Cutler
- Egor Panfilov
- Emmanuelle Gouillart
- Eoghan O'Connell
- Eric Jelli
- Eric Perlman
- erjel (erjel)
- Evan Widloski
- François Boulogne
- Gregory R. Lee
- Hazen Babcock
- Jan Eglinger
- Joshua Batson
- Juan Nunez-Iglesias
- Justin Terry
- kalvdans (kalvdans)
- Karthikeyan Singaravelan
- Lars Grüter
- Leengit (Leengit)
- leGIT-bot (leGIT-bot)
- Marianne Corvellec
- Mark Harfouche
- Marvin Albert
- mellertd (Dave Mellert)
- Miguel de la Varga
- Mostafa Alaa
- Mojdeh Rastgoo (mrastgoo)
- notmatthancock (matt)
- Ole Streicher
- Riadh Fezzani
- robroooh (robroooh)
- schneefux (schneefux)
- Scott Sievert
- Stefan van der Walt
- Talley Lambert
- Tim Head (betatim)
- Thomas A Caswell
- Timothy Sweetser
- Tony Tung
- Uwe Schmidt
- VolkerH (VolkerH)
- Xiaoyu Wu
- Yuanqin Lu
- Zaccharie Ramzi
- Zhōu Bówēi 周伯威
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Thank you again for your submission to the SciPy Tools track at SciPy 2020.
We wanted to apologize for the delay in following up on your submission.We
have been working to transition SciPy to a virtual conference and the SciPy
Tools track had been in flux. We now have confirmation that the track will
move forward and we will have virtual presentations on July 6 and July 7 at
2:00 pm CDT. The SciPy Tools Chairs, Hannah and Tom, are curating a list of
tools and will be reaching out to projects in May and June. Please do not
hesitate to contact us if you have any questions.
SciPy Tools Co-Chairs
SciPy 2020 Logistics
Recruiting and Special Projects Manager | Enthought
Tel +1 512 536 1057