Metadata-Version: 2.1
Name: cryolo
Version: 1.8.0b35
Summary: Picking procedure for cryo em single particle analysis
Home-page: https://cryolo.readthedocs.io/en/stable/index.html
Author: Thorsten Wagner
Author-email: thorsten.wagner@mpi-dortmund.mpg.de
License: Other/Proprietary License (all rights reserved)
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Environment :: X11 Applications
Classifier: Intended Audience :: End Users/Desktop
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Programming Language :: Python :: 3
Classifier: License :: Other/Proprietary License
Requires-Python: >=3.5.0, <3.9
Description-Content-Type: text/markdown
Provides-Extra: gpu
Provides-Extra: cpu
License-File: LICENSE

[![pipeline status](https://gitlab.gwdg.de/mpi-dortmund/sphire/cryolo/badges/master/pipeline.svg)](https://gitlab.gwdg.de/mpi-dortmund/sphire/cryolo/-/commits/predict3d) 
[![coverage report](https://gitlab.gwdg.de/mpi-dortmund/sphire/cryolo/badges/master/coverage.svg)](https://gitlab.gwdg.de/mpi-dortmund/sphire/cryolo/-/commits/predict3d) 

# SPHIRE-crYOLO

Deep learning particle picking procedure based on YOLOv2.
Please see [our website](https://cryolo.readthedocs.io/en/stable/) for more information.

## License
The license information can be found here:

[EULA license of crYOLO](https://cryolo.readthedocs.io/en/stable/other/license.html)

## Paper
If you use crYOLO, please cite

Wagner, T. et al. SPHIRE-crYOLO is a fast and accurate fully automated particle picker for cryo-EM. Communications Biology 2, (2019).
 
 https://doi.org/10.1038/s42003-019-0437-z

