A Python machine learning and computer vision library for automating cryo-EM data collection. The accompanying paper is available on arxiv. Ptolemy is designed to handle localization and scoring of squares in low-mag images (pixelsize of around 2000-5000 Angstroms/pixel) and holes in medium-mag images (100-1000 angstroms/pixel). It works on both gold and carbon holey, untilted grids.
Example Low Mag Image
Example Med Mag Image
Images and visualization are handled by the Exposure class in ptolemy/images.py, with algorithms for processing low and medium mag images in ptolemy/algorithms.py. The workflow is outlined in the tutorial notebooks.
We plan to improve Ptolemy with active learning on individual data collection sessions, support for tilted grids, and superresolution (unbinned) medium-mag images.
Tested with python 3.9
- pytorch
- torchvision
- numpy
- pandas
- scipy
- scikit-learn
- matplotlib
- scikit-image
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