Add quality replacement for Frigate face training images

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>

winnow/config.py

@@ -30,6 +30,7 @@ class _Config:
     BLUR_THRESHOLD: float = 100.0
     MIN_CONFIDENCE: float = 0.7
     MAX_AUTO_IMAGES: int = 80
+    QUALITY_REPLACEMENT: bool = True
 
     # People filtering
     MIN_FACE_COUNT: int = 0
@@ -60,6 +61,7 @@ class _Config:
         self.BLUR_THRESHOLD = float(os.getenv("BLUR_THRESHOLD", "100.0"))
         self.MIN_CONFIDENCE = float(os.getenv("MIN_CONFIDENCE", "0.7"))
         self.MAX_AUTO_IMAGES = int(os.getenv("MAX_AUTO_IMAGES", "80"))
+        self.QUALITY_REPLACEMENT = os.getenv("QUALITY_REPLACEMENT", "true").lower() in ("true", "1", "yes")
         self.FACE_MARGIN = float(os.getenv("FACE_MARGIN", "0.15"))
         self.USE_FULL_RESOLUTION = os.getenv("USE_FULL_RESOLUTION", "true").lower() in ("true", "1", "yes")
         self.ENABLE_FACE_ALIGNMENT = os.getenv("ENABLE_FACE_ALIGNMENT", "true").lower() in ("true", "1", "yes")