feat: initial BantayCam scaffold

- FastAPI backend with async SQLAlchemy
- Camera RTSP management (add, start, stop)
- Vehicle detection (YOLO + fast-alpr)
  - Type: car, motorcycle, truck, jeepney
  - Color detection (HSV)
  - License plate OCR
  - Motorcycle person count
- Face detection + InsightFace ArcFace embedding
- pgvector identity grouping (auto-cluster same face)
- Vehicle + person movement trail APIs
- Docker Compose with pgvector/pg16
- Models: Camera, VehicleIdentity, VehicleEvent, PersonIdentity, FaceEvent

backend/app/models/vehicle.py

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+from sqlalchemy import Column, String, Integer, Float, DateTime, Text, ForeignKey, Enum, JSON
+from sqlalchemy.dialects.postgresql import UUID
+from sqlalchemy.sql import func
+import uuid
+import enum
+
+from app.core.database import Base
+
+
+class VehicleType(str, enum.Enum):
+    car = "car"
+    motorcycle = "motorcycle"
+    truck = "truck"
+    van = "van"
+    jeepney = "jeepney"
+    tricycle = "tricycle"
+    unknown = "unknown"
+
+
+class VehicleIdentity(Base):
+    """
+    Unique vehicle identity — grouped by license plate.
+    Tracks every time this vehicle was seen across any camera.
+    """
+    __tablename__ = "vehicle_identities"
+
+    id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
+    plate_number = Column(String(20), nullable=True, index=True, unique=True)
+    vehicle_type = Column(Enum(VehicleType), default=VehicleType.unknown)
+    color = Column(String(50), nullable=True)
+    make_model = Column(String(100), nullable=True)          # e.g. "Toyota Vios"
+    notes = Column(Text, nullable=True)
+    label = Column(String(100), nullable=True)               # e.g. "Unit 4B Owner", "Delivery Van"
+    is_whitelisted = Column(Integer, default=0)              # 1 = resident/approved
+    is_blacklisted = Column(Integer, default=0)              # 1 = flagged/banned
+    thumbnail_path = Column(Text, nullable=True)             # Best shot saved
+    first_seen_at = Column(DateTime(timezone=True), nullable=True)
+    last_seen_at = Column(DateTime(timezone=True), nullable=True)
+    total_sightings = Column(Integer, default=0)
+    created_at = Column(DateTime(timezone=True), server_default=func.now())
+
+
+class VehicleEvent(Base):
+    """
+    Every detection event — one row per camera capture.
+    """
+    __tablename__ = "vehicle_events"
+
+    id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
+    camera_id = Column(UUID(as_uuid=True), ForeignKey("cameras.id"), nullable=False, index=True)
+    identity_id = Column(UUID(as_uuid=True), ForeignKey("vehicle_identities.id"), nullable=True, index=True)
+
+    # Detection data
+    plate_number = Column(String(20), nullable=True)
+    plate_confidence = Column(Float, nullable=True)
+    vehicle_type = Column(Enum(VehicleType), default=VehicleType.unknown)
+    color = Column(String(50), nullable=True)
+    person_count = Column(Integer, nullable=True)            # For motorcycle: how many riders
+    detection_confidence = Column(Float, nullable=True)
+
+    # Bounding boxes (stored as JSON: {"x":0,"y":0,"w":100,"h":100})
+    vehicle_bbox = Column(JSON, nullable=True)
+    plate_bbox = Column(JSON, nullable=True)
+
+    # Storage
+    snapshot_path = Column(Text, nullable=True)             # Full frame snapshot
+    plate_snapshot_path = Column(Text, nullable=True)       # Cropped plate image
+
+    # Meta
+    captured_at = Column(DateTime(timezone=True), server_default=func.now(), index=True)
+
+    def __repr__(self):
+        return f"<VehicleEvent plate={self.plate_number} type={self.vehicle_type} at={self.captured_at}>"