Spaces:
Configuration error
Configuration error
| # Cow Breed Classifier (Roboflow -> Hugging Face Space) | |
| ## What to upload to the Space | |
| - `dataset.zip` : export zip from Roboflow (pick YOLOv5 PyTorch or Pascal VOC when downloading). | |
| - Place `dataset.zip` in the Space root (where `app.py` sits) before committing. | |
| OR | |
| - `model.pth` : If you already trained a model elsewhere, upload `model.pth` (the saved dict with keys `model_state` and `classes`) to skip training. | |
| ## How it works | |
| - On first start: | |
| - If `model.pth` exists: the app loads it and serves predictions. | |
| - Else if `dataset.zip` exists: app extracts it, converts detection labels -> classification folders, and trains a small ResNet18 model for a few epochs, then saves `model.pth`. | |
| - Use the UI to upload images and see top-3 breed predictions. | |
| ## Notes & tips | |
| - Training on CPU (Hugging Face free Spaces) can be slow. Keep `NUM_EPOCHS=3` (default) small. You can increase by setting an environment variable in the Space settings. | |
| - If training fails due to PyTorch issues in the Space build, train locally (or on Colab) and upload `model.pth`. | |