https://github.com/mkcor/als-ml-sync

Tracking a solid-liquid interface in synchrotron x-radiographs with machine learning.
https://github.com/mkcor/als-ml-sync

Last synced: about 2 months ago
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Tracking a solid-liquid interface in synchrotron x-radiographs with machine learning.

• Host: GitHub
• URL: https://github.com/mkcor/als-ml-sync
• Owner: mkcor
• License: bsd-3-clause
• Created: 2021-08-11T19:00:28.000Z (almost 5 years ago)
• Default Branch: main
• Last Pushed: 2021-12-09T14:59:32.000Z (over 4 years ago)
• Last Synced: 2025-01-01T17:23:12.986Z (over 1 year ago)
• Language: Jupyter Notebook
• Size: 2.85 MB
• Stars: 0
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Segmenting synchrotron x-radiographs with scikit-image

Materials presented at the ['Machine Learning for Synchrotrons'

workshop](https://als.lbl.gov/2021-user-meeting-workshops-tutorials/) of the

2021 ALS User Meeting.

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/mkcor/als-ml-sync.git/main?urlpath=%2Fvoila%2Frender%2Fslideshow.ipynb) (view Voilà slideshow)

[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/mkcor/als-ml-sync/main?filepath=slideshow.ipynb) (run Jupyter notebook)

## Setup

Install [Miniconda](https://docs.conda.io/en/latest/miniconda.html) or

[Mambaforge](https://github.com/conda-forge/miniforge#mambaforge).

    $ mamba env create -f environment.yml

    $ conda activate als-ml-sync

    $ voila --strip_sources=False --template=reveal slideshow.ipynb

## References

* https://github.com/cgusb/solidification-tracking