scikit-image 0.19.3-foss-2022a

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 0.19.3-foss-2022a

To load the module for scikit-image 0.19.3-foss-2022a please use this command on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs):

module load scikit-image/0.19.3-foss-2022a

BEAR Apps Version

2020a

Extensions

  • imread 0.7.4
  • pooch 1.6.0
  • PyWavelets 1.4.1
  • scikit-image-0.19.3
  • tifffile 2022.10.10

More Information

For more information visit the scikit-image website.

Dependencies

This version of scikit-image has a direct dependency on: dask/2022.12.0-foss-2022a foss/2022a imageio/2.22.2-foss-2022a matplotlib/3.5.2-foss-2022a networkx/2.8.4-foss-2022a Pillow/9.1.1-GCCcore-11.3.0 Python/3.10.4-GCCcore-11.3.0

Required By

This version of scikit-image is a direct dependent of: DeepLabCut/2.3.6-foss-2022a-CUDA-11.7.0 DeepLabCut/2.3.6-foss-2022a imgaug/0.4.0-foss-2022a-CUDA-11.7.0 imgaug/0.4.0-foss-2022a napari/0.4.17-foss-2022a OpenPose/1.7.0-foss-2022a-CUDA-11.7.0 ptwt/0.1.4.post2-foss-2022a-CUDA-11.7.0 ptwt/0.1.4.post2-foss-2022a RootPainter/0.2.27.0-foss-2022a-CUDA-11.7.0 steinbock/0.16.1-foss-2022a

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 16th February 2023