Update README.md

README.md

@@ -1,8 +1,86 @@
 ---
 tags:
+- feature-extraction
 - image-classification
 - timm
+- biology
+- cancer
+- histology
 library_name: timm
-license: apache-2.0
+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.tgca_brca
+
+# Model card for resnet50.tcga_brca
+
+A ResNet50 image classification model. \
+Trained on 2M histology patches from TCGA-BRCA.
+
+![](https://github.com/Richarizardd/Self-Supervised-ViT-Path/raw/master/.github/Pathology_DINO.jpg)
+
+## 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:** TGCA 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",
+  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}
+}
+```