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

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

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

There is a CPU version of this module: scikit-image 0.16.2-foss-2019b-Python-3.7.4

BEAR Apps Version

2020h

Extensions

  • 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.

Dependencies

This version of scikit-image has a direct dependency on: dask/2.8.0-fosscuda-2019b-Python-3.7.4 fosscuda/2019b matplotlib/3.1.1-fosscuda-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: BEAR-Python-DataScience/2019b-fosscuda-2019b-Python-3.7.4 BEAR-Python-DataScience/2019b-fosscuda-2019b-Python-3.7.4-ppc64le imgaug/0.4.0-fosscuda-2019b-Python-3.7.4 neural_renderer_pytorch/1.1.3-fosscuda-2019b-Python-3.7.4-PyTorch-1.4.0 neural_renderer_pytorch/1.1.3-fosscuda-2019b-Python-3.7.4 PyTorch-Geometric/1.4.3-fosscuda-2019b-Python-3.7.4-PyTorch-1.4.0 SoftRas/f644279-fosscuda-2019b-Python-3.7.4-PyTorch-1.4.0 SoftRas/f644279-fosscuda-2019b-Python-3.7.4

Other Versions

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

Last modified on 4th February 2020