COVID-19 library in torchvision

🚀 Feature

Library of models and dataset interfaces for COVID-19 models

Motivation

There are quite a few models (feature extractors, mask segmentation, classifiers) for COVID-19, both in pytorch and tensorflow. They use different datasets, making it hard to scientists to compare results and extend their findings. It would be good to (re-implement) at least some models and dataset interfaces as a library in torchvision

Pitch

Similar to the models and datasets in torchvision: models for the published models (see below), at least those that come with pretrained weights (e.g. COVIDNet-CT), and datasets for open-source labelled dataset interfaces: eg. CNCB-CT, UCSD, MedSeg, Zenodo, especially mask extraction.

Alternatives

None that I know of

Additional context

Some candidates include COVIDNet (x-rays), COVIDNet-CT (ct-scans), COVNet (ct-scans), JCS (ct-scans).

cc @pmeier

The issue names no files, tests, or specific entry point. Start by reviewing torchvision's existing models and datasets interfaces, then assess the proposed COVIDNet, COVIDNet-CT, COVNet, and JCS models and the CNCB-CT, UCSD, MedSeg, and Zenodo datasets. Done would require a concrete scope for selected models, pretrained weights, and dataset interfaces.