Summary
Source: https://github.com/ilastik/ilastik
License: GPL v2
Path: /software/ilastik
Documentation: https://www.ilastik.org/
The interactive learning and segmentation toolkit
Leverage machine learning algorithms to easily segment, classify, track and count your cells or other experimental data. Most operations are interactive, even on large datasets: you just draw the labels and immediately see the result. No machine learning expertise required.
Using ilastik
To initialize the environment (it's actually a python 3.9 virtual environment) use the module command:
export PATH=/software/ilastik/1.4.0/bin:$PATH ilastik
Note: ilastik has been modfied to os.unsetenv('SESSION_MANAGER') preventing QT error messages.
ilastik will best work in FastX desktops, which also allows using ilastik as a standalone application in a web-browser or your desktop:
