feat: add debug mode, distance-based thresholds, and improve pose detection

- Add debug mode support for encoding statistics in API responses
  - Debug info includes encoding length, min/max/mean/std, and first 10 values
  - Frontend logs encoding stats to browser console when debug enabled
  - Identify page enables debug mode by default

- Implement distance-based confidence thresholds for stricter matching
  - Borderline distances require higher confidence (70-95% vs 50%)
  - Applied when use_distance_based_thresholds=True (auto-match)
  - Reduces false positives for borderline matches

- Dual tolerance system for auto-match
  - Default tolerance 0.6 for regular browsing (more lenient)
  - Run auto-match button uses 0.5 tolerance with distance-based thresholds (stricter)
  - Auto-accept threshold updated to 85% (from 70%)

- Enhance pose detection with single-eye detection
  - Profile threshold reduced from 30° to 15° (stricter)
  - Detect single-eye visibility for extreme profile views
  - Infer profile direction from landmark visibility
  - Improved face width threshold (20px vs 10px)

- Clean up debug code
  - Remove test photo UUID checks from production code
  - Remove debug print statements
  - Replace print statements with proper logging

backend/schemas/faces.py

@@ -89,6 +89,7 @@ class SimilarFaceItem(BaseModel):
     quality_score: float
     filename: str
     pose_mode: Optional[str] = Field("frontal", description="Pose classification (frontal, profile_left, etc.)")
+    debug_info: Optional[dict] = Field(None, description="Debug information (encoding stats) when debug mode is enabled")
 
 
 class SimilarFacesResponse(BaseModel):
@@ -98,6 +99,7 @@ class SimilarFacesResponse(BaseModel):
 
     base_face_id: int
     items: list[SimilarFaceItem]
+    debug_info: Optional[dict] = Field(None, description="Debug information (base face encoding stats) when debug mode is enabled")
 
 
 class BatchSimilarityRequest(BaseModel):
@@ -215,6 +217,7 @@ class AutoMatchRequest(BaseModel):
     tolerance: float = Field(0.5, ge=0.0, le=1.0, description="Tolerance threshold (lower = stricter matching)")
     auto_accept: bool = Field(False, description="Enable automatic acceptance of matching faces")
     auto_accept_threshold: float = Field(70.0, ge=0.0, le=100.0, description="Similarity threshold for auto-acceptance (0-100%)")
+    use_distance_based_thresholds: bool = Field(False, description="Use distance-based confidence thresholds (stricter for borderline distances)")
 
 
 class AutoMatchFaceItem(BaseModel):