README.md

metadata

title: Chess Assist
emoji: ♟️
colorFrom: gray
colorTo: green
sdk: gradio
sdk_version: 4.44.1
app_file: app.py
pinned: false

Chess Assist (v3): Image → FEN → Best Move

This bundle is hardened for Hugging Face Spaces:

• apt.txt installs system stockfish.
• requirements.txt pins CPU Torch wheels for Ultralytics.
• Better error messages in UI to surface what's failing (model download, engine path, etc.).

Deploy Steps

1. Create a new Space (Gradio, Python).
2. Upload: app.py, requirements.txt, apt.txt, runtime.txt, README.md.
3. In Space Settings → Space hardware, choose CPU Basic (enough for this demo).
4. In Space Settings → Networking, ensure "Allow internet access" is ON so the YOLO weights can download.
5. Commit and wait for build. First run will download the YOLO weights.

Common Issues

• Ultralytics / Torch errors: We pinned Torch CPU wheels. If still failing, change runtime to Python 3.10 (provided here).
• Stockfish not found: apt.txt should install it. If still missing, check build logs and confirm /usr/bin/stockfish exists.
• No opening name: Many midgame positions have no named opening; this is normal.
• Board not detected: Try a straighter photo with the board filling the frame; glare can confuse corner detection.

Local Run

python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
python app.py

Notes

• Labels assumed like wpawn, bqueen, etc. Adjust LABEL_TO_FEN if your detector uses different names.
• Evaluation score is kept internal per your specs; only a simple explanation is shown.