A small example package
Project description
torchxrayvision
A library for chest X-ray datasets and models. Including pre-trainined models.
This code is still under development
models
model = xrv.models.DenseNet(weights="nih")
model = xrv.models.DenseNet(weights="chex")
model = xrv.models.DenseNet(weights="minix_nb")
model = xrv.models.DenseNet(weights="minix_ch")
model = xrv.models.DenseNet(weights="all")
datasets
transform = torchvision.transforms.Compose([xrv.datasets.XRayCenterCrop(),
xrv.datasets.XRayResizer(224)])
d_kaggle = xrv.datasets.Kaggle_Dataset(imgpath="path to stage_2_train_images_jpg",
transform=transform)
d_chex = xrv.datasets.CheX_Dataset(imgpath="path to CheXpert-v1.0-small",
csvpath="path to CheXpert-v1.0-small/train.csv",
transform=transform)
d_nih = xrv.datasets.NIH_Dataset(imgpath="path to NIH images")
d_nih2 = xrv.datasets.NIH_Google_Dataset(imgpath="path to NIH images")
d_pc = xrv.datasets.PC_Dataset(imgpath="path to image folder")
d_covid19 = xrv.datasets.COVID19_Dataset()
dataset tools
relabel_dataset will align labels to have the same order as the pathologies argument.
xrv.datasets.relabel_dataset(pathologies, d_nih) # has side effects
Cite:
Joseph Paul Cohen, Joseph Viviano, and Hadrien Bertrand. TorchXrayVision: A library of chest X-ray datasets and models. https://github.com/mlmed/torchxrayvision, 2020
and
Cohen, J. P., Hashir, M., Brooks, R., & Bertrand, H. On the limits of cross-domain generalization in automated X-ray prediction. 2020 arXiv preprint arXiv:2002.02497.
@article{cohen2020limits,
title={On the limits of cross-domain generalization in automated X-ray prediction},
author={Cohen, Joseph Paul and Hashir, Mohammad and Brooks, Rupert and Bertrand, Hadrien},
journal={arXiv preprint arXiv:2002.02497},
year={2020}
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
torchxrayvision-0.0.2.tar.gz
(10.7 kB
view hashes)
Built Distribution
Close
Hashes for torchxrayvision-0.0.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | c08681e44a0a1413982f89d2bdb230bca60b4ea7528ae17334384b1b11d9949b |
|
MD5 | 3fc766d5bfff07843bd0394b7be962d3 |
|
BLAKE2b-256 | 0badf5d03cf9c98f7530298e763f5a0baf078d2d0969138230888c6b09c9abbe |