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Check out the documentation for more information.
models
Model weights trained on Kaggle. This folder is empty in git (see .gitignore at the repo
root); large files are distributed via Hugging Face Hub, not via commit.
What must be here before running the backend
models/
detector.pt YOLOv8 weights fine-tuned on SKU-110K (see notebooks/)
encoder/ encoder embedding checkpoint folder (config + weights, fine-tuned on RPC)
How they get here
Automatic (default, no manual step): docker compose up fetches both from the Hugging
Face Hub repo named by the HF_REPO_ID environment variable in docker-compose.yml, the
first time this folder is empty (backend/entrypoint.sh). This satisfies the MVP scope
constraint that docker-compose up must run the whole system with no manual step beyond
that command (CLAUDE.md section 2). Nothing to do here as a judge running this repo
locally, as long as HF_REPO_ID in docker-compose.yml points at a real public repo
containing detector.pt at its root and an encoder/ folder alongside it.
Manual (for local development, or if you don't want the auto-download): place
detector.pt and the encoder/ folder exactly as shown in the structure above yourself,
before running docker compose up. entrypoint.sh checks for both first and skips the
network fetch entirely if they're already present, so this keeps working unchanged.
This folder is mounted to /models inside the backend container via a volume mount in
docker-compose.yml. Weights are loaded once at startup and never change during runtime
(see CLAUDE.md section 6 at the repo root).