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Make drawing and labeling bounding boxes easy as cake
...There are optional functions that can draw multiple bounding boxes and/or write multiple labels on the same image, but it is advisable to use the above functions in a loop in order to have full control over your visualizations.
A python library for self-supervised learning on images
...Lightly requires Python 3.6+ but we recommend using Python 3.7+. We recommend installing Lightly in a Linux or OSX environment. With lightly, you can use the latest self-supervised learning methods in a modular way using the full power of PyTorch. Experiment with different backbones, models, and loss functions.
MetaErg is a stand-alone and fully automated metagenome and metaproteome annotation pipeline published at: https://www.frontiersin.org/articles/10.3389/fgene.2019.00999/full.
If you are using this pipeline for your work, please cite:
Dong X and Strous M (2019) An Integrated Pipeline for Annotation and Visualization of Metagenomic Contigs. Front. Genet. 10:999. doi: 10.3389/fgene.2019.00999
The instructions on configuring and running the MetaErg pipeline is available at GitHub repository: https://github.com/xiaoli-dong/metaerg