from dataclasses import dataclass
from datetime import datetime
from typing import List, Optional, Tuple
import numpy as np
from enum import Enum
from pydantic import BaseModel

class OperationType(str, Enum):
    REGISTER = "register"
    VERIFICATION = "verify"
    IDENTIFICATION = "identify"

@dataclass
class Face:
    id: str
    user_id: str
    image_path: str
    embedding: np.ndarray
    created_at: datetime
    quality_score: float
    bbox: List[float]
    landmarks: Optional[List[List[float]]] = None

@dataclass
class User:
    id: str
    name: str
    created_at: datetime
    face_ids: List[str]
    mean_embedding: Optional[np.ndarray] = None

@dataclass
class VerificationResult:
    is_verified: bool
    confidence: float
    user_id: str
    face_id: str
    threshold: float
    processing_time: float

@dataclass
class IdentificationResult:
    is_identified: bool
    user_id: Optional[str]
    confidence: float
    candidates: List[Tuple[str, float]]
    threshold: float
    processing_time: float

class ProcessedFace(BaseModel):
    bbox: List[float]  # [x1, y1, x2, y2]
    landmarks: List[List[float]]  # [[x1, y1], [x2, y2], ...]
    quality_score: float
    embedding: List[float]