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c794b6b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | # Vision & Face Recognition Audit
The Face Recognition system is located in `backend/Face_Recognition`.
## Key Findings:
1. **Matcher Engine**: `FaceMatcher` handles operations via `InsightFace` models.
2. **Embedding Storage**: Enrollments are saved as `.npy` files. Stored inside `faces_db` and `temp_faces_db`.
3. **Concurrency**: It employs thread locks (`threading.Lock()`) for updating the embedding dict safely across background refreshes and API calls.
4. **Background Refresh**: Boot sequence kicks off a thread to refresh stale embeddings without blocking startup.
5. **Dynamic Thresholds**: Reads defaults via env vars (`FACE_MATCH_THRESHOLD`) but overrides them based on a `PERSON_THRESHOLDS` mapping for predefined demo identities (mk, urvi, vidit), ensuring fewer false positives.
## Recommendations:
- Transition from file-based `.npy` lookups to a vector database if the identity count exceeds a few thousand.
- Ensure the background thread handles InsightFace GPU resource contention if any.
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