Published October 4, 2022
| Version v0.2.7
Software
Open
Volume Segmantics: A Python Package for Semantic Segmentation of Volumetric Data Using Pre-trained PyTorch Deep Learning Models
Creators
- 1. Diamond Light Source Ltd
- 2. Rosalind Franklin Institute
Description
This version of the software is the version reviewed for the paper submitted to the Journal of Open Source Software entitled: Volume Segmantics: A Python Package for Semantic Segmentation of Volumetric Data Using Pre-trained PyTorch Deep Learning Models
Files
DiamondLightSource/volume-segmantics-v0.2.7.zip
Files
(16.1 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:a9b44a3daba2b6cb251f788bbc135b93
|
16.1 MB | Preview Download |
Additional details
Related works
- Is supplement to
- https://github.com/DiamondLightSource/volume-segmantics/tree/v0.2.7 (URL)
References
- Buslaev, A., Iglovikov, V.I., Khvedchenya, E., Parinov, A., Druzhinin, M., and Kalinin, A.A. (2020). Albumentations: Fast and Flexible Image Augmentations. Information 11. https://doi.org/10.3390/info11020125
- Yakubovskiy, P. (2020). Segmentation Models Pytorch. GitHub
- Wolny, A., Cerrone, L., Vijayan, A., Tofanelli, R., Barro, A.V., Louveaux, M., Wenzl, C., Strauss, S., Wilson-Sánchez, D., Lymbouridou, R., et al. (2020). Accurate and versatile 3D segmentation of plant tissues at cellular resolution. ELife 9, e57613. https://doi.org/10.7554/eLife.57613