perf: batch GET /api/faces; skip download on low confidence; batch gate tracker writes

Fetch all Frigate training files once before the upload loop instead of once
per person — for N people this reduces GET /api/faces calls from N to 1.
Falls back to per-person calls if the pre-fetch fails.

Check InsightFace detection confidence immediately after face enrichment,
before fetching the full-resolution image. Assets that fail MIN_CONFIDENCE
are skipped without downloading, saving potentially large image downloads.

Collapse the gate removal tracker writes from 3×N file ops into 2 total
via remove_and_reclassify_batch: one write to the uploaded tracker (remove
file mappings + remove from flat set) and one write to the rejected tracker.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

winnow/frigate_api.py

@@ -40,6 +40,22 @@ def get_frigate_face_counts() -> dict[str, int] | None:
     }
 
 
+def get_all_frigate_person_files() -> dict[str, list[str]] | None:
+    """Return {person_name: [filename, ...]} for every person in Frigate.
+
+    Single call used to build per-person snapshots before the upload loop,
+    avoiding one GET /api/faces per person.  Returns None if unavailable.
+    """
+    data = _get_faces_data()
+    if data is None:
+        return None
+    return {
+        name: files
+        for name, files in data.items()
+        if name != "train" and isinstance(files, list)
+    }
+
+
 def get_frigate_person_files(person_name: str) -> list[str] | None:
     """Return the list of training filenames for a person in Frigate.