Home

winnow

winnow pulls photos from Immich, selects diverse high-quality subsets using AI embeddings (InsightFace Buffalo_L / ArcFace), and delivers them as training data for Frigate's face recognition.

The goal is to fill the gap where you don't have manually-curated training photos. winnow mines your existing Immich library for the most diverse spread of real-world appearances and keeps the Frigate training set fresh as your library grows.

winnow only touches files it uploaded. Faces added to Frigate manually through its UI are never deleted, replaced, or modified — not by quality replacement, not by RESET_PERSON, not by stale cleanup. If you have a curated training set, it is safe.

Pages

• Setup — installation, Docker Compose configuration, GPU passthrough, environment variables
• Benchmarks — GPU vs CPU inference latency and throughput (InsightFace)
• Troubleshooting — common failures and fixes
• FAQ — frequently asked questions

Quick Links

• GitHub Repository
• CHANGELOG
• compose.yml