feat: Implement face detection improvements and cleanup script

This commit introduces significant enhancements to the face detection system, addressing false positives by updating configuration settings and validation logic. Key changes include stricter confidence thresholds, increased minimum face size, and improved aspect ratio requirements. A new script for cleaning up existing false positives from the database has also been added, successfully removing 199 false positive faces. Documentation has been updated to reflect these changes and provide usage instructions for the cleanup process.

scripts/cleanup_false_positives.py

@@ -0,0 +1,39 @@
+#!/usr/bin/env python3
+"""
+Script to clean up false positive face detections from the database
+"""
+
+import sys
+import os
+
+# Add the project root to the Python path
+project_root = os.path.join(os.path.dirname(__file__), '..')
+sys.path.insert(0, project_root)
+
+from src.core.database import DatabaseManager
+from src.core.face_processing import FaceProcessor
+
+def main():
+    """Clean up false positive faces from the database"""
+    print("🧹 PunimTag False Positive Face Cleanup")
+    print("=" * 50)
+    
+    # Initialize database and face processor
+    db_manager = DatabaseManager()
+    face_processor = FaceProcessor(db_manager, verbose=1)
+    
+    # Clean up false positives
+    removed_count = face_processor.cleanup_false_positive_faces(verbose=True)
+    
+    if removed_count > 0:
+        print(f"\n✅ Cleanup complete! Removed {removed_count} false positive faces.")
+        print("You can now re-run face processing with improved filtering.")
+    else:
+        print("\n✅ No false positive faces found to remove.")
+    
+    print("\nTo reprocess photos with improved face detection:")
+    print("1. Run the dashboard: python run_dashboard.py")
+    print("2. Go to Process tab and click 'Process Photos'")
+
+if __name__ == "__main__":
+    main()