|
--- |
|
tags: |
|
- feature-extraction |
|
- image-classification |
|
- timm |
|
- biology |
|
- cancer |
|
- histology |
|
library_name: timm |
|
model-index: |
|
- name: tcga_brca |
|
results: |
|
- task: |
|
type: image-classification |
|
name: Image Classification |
|
dataset: |
|
name: TCGA-BRCA |
|
type: image-classification |
|
metrics: |
|
- type: accuracy |
|
value: 0.879 ± 0.069 |
|
name: AUC |
|
verified: false |
|
license: gpl-3.0 |
|
pipeline_tag: feature-extraction |
|
inference: false |
|
--- |
|
|
|
# Model card for resnet50.tcga_brca_simclr |
|
|
|
A ResNet50 image classification model. \ |
|
Trained on 2M histology patches from TCGA-BRCA. |
|
|
|
## Model Details |
|
|
|
- **Model Type:** Feature backbone |
|
- **Model Stats:** |
|
- Params (M): 23.6 |
|
- Image size: 256 x 256 x 3 |
|
- **Papers:** |
|
- Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology: https://arxiv.org/abs/2203.00585 |
|
- **Dataset:** TCGA BRCA: https://portal.gdc.cancer.gov/ |
|
- **Original:** https://github.com/Richarizardd/Self-Supervised-ViT-Path/ |
|
- **License:** [GPLv3](https://github.com/Richarizardd/Self-Supervised-ViT-Path/blob/master/LICENSE) |
|
|
|
## Model Usage |
|
|
|
### Image Embeddings |
|
```python |
|
from urllib.request import urlopen |
|
from PIL import Image |
|
import timm |
|
|
|
# get example histology image |
|
img = Image.open( |
|
urlopen( |
|
"https://github.com/owkin/HistoSSLscaling/raw/main/assets/example.tif" |
|
) |
|
) |
|
|
|
# load model from the hub |
|
model = timm.create_model( |
|
model_name="hf-hub:1aurent/resnet50.tcga_brca_simclr", |
|
pretrained=True, |
|
).eval() |
|
|
|
# get model specific transforms (normalization, resize) |
|
data_config = timm.data.resolve_model_data_config(model) |
|
transforms = timm.data.create_transform(**data_config, is_training=False) |
|
|
|
output = model(transforms(img).unsqueeze(0)) # output is (batch_size, num_features) shaped tensor |
|
``` |
|
|
|
## Citation |
|
```bibtex |
|
@misc{chen2022selfsupervised, |
|
title = {Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology}, |
|
author = {Richard J. Chen and Rahul G. Krishnan}, |
|
year = {2022}, |
|
eprint = {2203.00585}, |
|
archiveprefix = {arXiv}, |
|
primaryclass = {cs.CV} |
|
} |
|
``` |
