scikit-image 0.18.1-fosscuda-2020b

There is a newer install 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 0.18.1-fosscuda-2020b

To load the module for scikit-image 0.18.1-fosscuda-2020b please use this command on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs):

module load scikit-image/0.18.1-fosscuda-2020b

BEAR Apps Version

2020b

Architectures

EL8-icelake (GPUs: NVIDIA A100, NVIDIA A30)

The listed architectures consist of two part: OS-CPU. The OS used is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.

Extensions

  • imageio 2.9.0
  • imread 0.7.4
  • pooch 1.3.0
  • PyWavelets 1.1.1
  • scikit-image-0.18.1
  • tifffile 2021.2.1

More Information

For more information visit the scikit-image website.

Dependencies

This version of scikit-image has a direct dependency on: dask/2021.4.0-fosscuda-2020b fosscuda/2020b matplotlib/3.3.3-fosscuda-2020b networkx/2.5-fosscuda-2020b Pillow/8.0.1-GCCcore-10.2.0 Python/3.8.6-GCCcore-10.2.0

Required By

This version of scikit-image is a direct dependent of: DECODE/0.10.0-fosscuda-2020b

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 21st March 2022