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GitHub / tbepler / topaz
Pipeline for particle picking in cryo-electron microscopy images using convolutional neural networks trained from positive and unlabeled examples. Also featuring micrograph and tomogram denoising with DNNs.
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tbepler%2Ftopaz
Stars: 164
Forks: 64
Open Issues: 24
License: gpl-3.0
Language: Jupyter Notebook
Repo Size: 111 MB
Dependencies:
32
Created: over 6 years ago
Updated: 17 days ago
Last pushed: about 1 month ago
Last synced: 8 days ago
Commit Stats
Commits: 255
Authors: 8
Mean commits per author: 31.88
Development Distribution Score: 0.322
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/tbepler/topaz
Topics: cnn, cryo-em, cryoem, denoising, machine-learning, object-detection, particle-picking, positive-unlabeled, pytorch, topaz, topaz-denoise, topaz-em
Files
Dependencies
- Dockerfile * docker
- actions/checkout v2 composite
- actions/setup-python v2 composite
- actions/checkout v1 composite
- darnellgranberry/conda-package-publish-action master composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- pypa/gh-action-pypi-publish 27b31702a0e7fc50959f5ad993c78deac1bdfc29 composite
- continuumio/miniconda3 4.7.10 build
- nvidia/cuda 10.1-cudnn7-devel-ubuntu16.04 build
- myst-parser *
- nbsphinx *
- rst-to-myst *
- sphinx ==4.4.0
- sphinx-argparse *
- sphinx_rtd_theme *
- future *
- numpy >=1.11
- pandas *
- pillow >=6.2.0
- scikit-learn >=0.19.0
- scipy >=0.17.0
- torch >=1.0.0
- torchvision *
- future *
- numpy >=1.11
- pandas *
- pillow >=6.2.0
- scikit-learn >=0.19.0
- scipy >=0.17.0
- torch >=1.0.0
- torchvision *