Previously, effective_count and the jobs.py cap check used the total
Frigate file count (including manually-added files), so any file a user
curated by hand ate into winnow's managed quota. Now:
- get_tracked_frigate_file_count() returns len(frigate_files) from the
tracker — only files winnow uploaded and reconciled
- effective_count in the upload loop uses this tracker count so
manually-added files are invisible to the cap
- jobs.py capacity check uses len(frigate_files) instead of the live
Frigate API count or cached frigate_count
- Frigate API call for known_frigate_files_at_start is now only used
for the post-upload reconciliation diff, not for cap enforcement
Side-effect: fixes audit bug #1 — an unreachable Frigate GET no longer
zeroes effective_count and bypasses the cap, because the cap is now
read from the always-available local tracker.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
When a person is at MAX_AUTO_IMAGES, winnow now replaces the
lowest-quality mapped training image in Frigate if a higher-confidence
candidate is available, keeping the training set always optimised.
Only files winnow uploaded (tracked via frigate_files mapping) are ever
replaced — manually added Frigate training images are never touched.
A concurrent-upload race condition is detected per-file: if N>1 new
files appear after one upload, the mapping is skipped rather than
guessed, logging at INFO level. The per-file snapshot approach is
retained over a batch approach because wrong mappings (which a batch
approach risks on race) are worse than no mapping.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
flanandClaude Sonnet 4.6