fix: v0.6.2 — structural tracker refactor, batch writes, multi-instance prep

- Drop flat list as primary storage; derive uploaded/rejected IDs from by_person
  (single source of truth). Legacy flat lists in existing files still read for
  backward compat. Removes dual-representation sync hazard.
- Add begin_batch/flush_batch: per-person upload loop now does 1 os.replace
  instead of N (one per mark_uploaded call). Benefit on slow storage.
- reset_all_people(): RESET_PERSON=* is now O(1) disk writes instead of O(P^2).
- blur_score_from_image inlines cv2.Laplacian directly, removing assess_quality
  call overhead and decoupling from the full quality pipeline.

winnow/executor.py

@@ -34,6 +34,8 @@ from .upload_tracker import (
     has_frigate_scores,
     mark_rejected,
     mark_uploaded,
+    begin_batch,
+    flush_batch,
     remove_frigate_file,
     remove_frigate_files_batch,
 )
@@ -364,6 +366,7 @@ def upload_to_frigate(jobs: list[dict]) -> None:
             min_quality_score_for_slot: float | None = None
             person_has_fscores: bool = has_frigate_scores(name)
 
+            begin_batch(UPLOAD_TRACKER_FILE)
             for fname in person_files:
                 fpath = os.path.join(person_dir, fname)
 
@@ -590,6 +593,8 @@ def upload_to_frigate(jobs: list[dict]) -> None:
                     " was not filled this run — will be available next run"
                 )
 
+            flush_batch(UPLOAD_TRACKER_FILE)
+
             # Batch-map Frigate filenames to asset IDs now that all uploads are done.
             if actually_uploaded and not _skip_reconcile:
                 reconcile_frigate_mappings(name, known_frigate_files_at_start, actually_uploaded)