scikit-image 0.16.2-foss-2019b-Python-3.7.4

There is a newer version of scikit-image

Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering. It strives to be simple and efficient, accessible to everybody, and reusable in various contexts.

Accessing scikit-image 0.16.2-foss-2019b-Python-3.7.4

To load the module for scikit-image 0.16.2-foss-2019b-Python-3.7.4 please use this command on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs):

module load scikit-image/0.16.2-foss-2019b-Python-3.7.4

There is a GPU enabled version of this module: scikit-image 0.16.2-fosscuda-2019b-Python-3.7.4

BEAR Apps Version



  • imageio 2.6.1
  • imread 0.7.1
  • networkx 2.4
  • PyWavelets 1.1.1
  • scikit-image-0.16.2

More Information

For more information visit the scikit-image website.


This version of scikit-image has a direct dependency on: dask/2.8.0-foss-2019b-Python-3.7.4 foss/2019b matplotlib/3.1.1-foss-2019b-Python-3.7.4 Pillow/6.2.1-GCCcore-8.3.0 Python/3.7.4-GCCcore-8.3.0

Required By

This version of scikit-image is a direct dependent of: imgaug/0.4.0-foss-2019b-Python-3.7.4 PyTorch-Geometric/1.4.3-foss-2019b-Python-3.7.4-PyTorch-1.4.0 Scrublet/0.2.1-foss-2019b-Python-3.7.4 SunPy/1.1.3-foss-2019b-Python-3.7.4

Other Versions

These versions of scikit-image are available on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.

Last modified on 13th May 2020