README.md

metadata

title: Retina Training
emoji: 🐢
colorFrom: red
colorTo: green
sdk: docker
pinned: false
license: mit
short_description: Training model for some retina dataset

RETFound MAE – Hugging Face Space (FastAPI): Train + Inference

This Space lets you upload a zipped ImageFolder dataset, fine-tune a classifier head on top of RETFound MAE, run predictions, and push the trained model to the Hub.

Endpoints

• POST /upload_dataset → form-data file=dataset.zip (contains train/, val/)
• POST /train → form fields: epochs, batch_size, lr, freeze_backbone
• GET /status → training status & metadata
• POST /predict → form-data file=image.jpg
• POST /push → optional form field: repo_id (else uses HF_PUSH_REPO)

Env Vars

• HF_BASE_MODEL_REPO (e.g., username/retfound-model)
• HF_BASE_MODEL_FILE (e.g., RETFound_mae_meh.pth)
• HF_PUSH_REPO (e.g., username/retfound-classifier)

Dataset format

zip-root/
train/
ClassA/*.jpg
ClassB/*.jpg
val/
ClassA/*.jpg
ClassB/*.jpg

Notes

• GPU recommended. If CPU-only, reduce batch size.
• Validation accuracy is reported; best checkpoint saved to checkpoints/.