fix: raise BLUR_THRESHOLD default from 100 to 120 to match Frigate's floor

Frigate classifies images with Laplacian variance < 120 as "very blurry"
and its own docs recommend avoiding blurry training data. Winnow was
accepting images in the 100-120 range that Frigate considers too blurry.

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

.env.example

@@ -28,7 +28,7 @@ STRATEGY=auto
 # ENABLE_FACE_ALIGNMENT=true  # Align face before cropping (default: true)
 # USE_FULL_RESOLUTION=true    # Use full-res images vs thumbnails (default: true)
 # MIN_CONFIDENCE=0.7          # Minimum face detection confidence (default: 0.7)
-# BLUR_THRESHOLD=100.0        # Laplacian blur threshold; lower = accept more blur (default: 100.0)
+# BLUR_THRESHOLD=120.0        # Laplacian blur threshold; lower = accept more blur (default: 120.0)
 # MAX_AUTO_IMAGES=80          # Hard cap on auto-diversity selection (default: 80)
 
 # ── Caching & Models ──────────────────────────────────────────────────────────

tests/test_config.py

@@ -19,7 +19,7 @@ def test_config_loads_defaults(monkeypatch):
     assert cfg.YEARS_FILTER == 10
     assert cfg.MIN_FACE_WIDTH == 90
     assert cfg.MIN_FACE_COUNT == 0
-    assert cfg.BLUR_THRESHOLD == 100.0
+    assert cfg.BLUR_THRESHOLD == 120.0
     assert cfg.MIN_CONFIDENCE == 0.7
     assert cfg.MAX_AUTO_IMAGES == 80
     assert cfg.QUALITY_REPLACEMENT is True

winnow/config.py

@@ -27,7 +27,7 @@ class _Config:
 
     # Quality filtering
     MIN_FACE_WIDTH: int = 90
-    BLUR_THRESHOLD: float = 100.0
+    BLUR_THRESHOLD: float = 120.0
     MIN_CONFIDENCE: float = 0.7
     MAX_AUTO_IMAGES: int = 80
     QUALITY_REPLACEMENT: bool = True
@@ -58,7 +58,7 @@ class _Config:
         self.YEARS_FILTER = int(os.getenv("YEARS_FILTER", "10"))
         self.MIN_FACE_WIDTH = int(os.getenv("MIN_FACE_WIDTH", "90"))
         self.MIN_FACE_COUNT = int(os.getenv("MIN_FACE_COUNT", "0"))
-        self.BLUR_THRESHOLD = float(os.getenv("BLUR_THRESHOLD", "100.0"))
+        self.BLUR_THRESHOLD = float(os.getenv("BLUR_THRESHOLD", "120.0"))
         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")