"""
Pydantic Models - GENERATED FILE

Do not edit directly. Regenerate using modelgen.
"""

from datetime import datetime
from enum import Enum
from typing import Any, Dict, List, Optional
from uuid import UUID

from pydantic import BaseModel, Field

class DetectRequest(BaseModel):
    """Request body for object detection."""
    image: str
    model: Optional[str] = None
    confidence: Optional[float] = None
    target_classes: Optional[List[str]] = None

class BBox(BaseModel):
    """A detected bounding box."""
    x: int
    y: int
    w: int
    h: int
    confidence: float
    label: str

class DetectResponse(BaseModel):
    """Response from object detection."""
    detections: List[BBox] = Field(default_factory=list)

class OCRRequest(BaseModel):
    """Request body for OCR."""
    image: str
    languages: Optional[List[str]] = None

class OCRTextResult(BaseModel):
    """A single OCR text extraction result."""
    text: str
    confidence: float
    bbox: List[int] = Field(default_factory=list)

class OCRResponse(BaseModel):
    """Response from OCR."""
    results: List[OCRTextResult] = Field(default_factory=list)

class PreprocessRequest(BaseModel):
    """Request body for image preprocessing."""
    image: str
    binarize: bool = False
    deskew: bool = False
    contrast: bool = True

class PreprocessResponse(BaseModel):
    """Response from preprocessing."""
    image: str

class VLMRequest(BaseModel):
    """Request body for visual language model query."""
    image: str
    prompt: str
    model: Optional[str] = None

class VLMResponse(BaseModel):
    """Response from VLM."""
    brand: str
    confidence: float
    reasoning: str

class AnalyzeRegionsRequest(BaseModel):
    """Request body for CV region analysis."""
    image: str
    edge_canny_low: int = 50
    edge_canny_high: int = 150
    edge_hough_threshold: int = 80
    edge_hough_min_length: int = 100
    edge_hough_max_gap: int = 10
    edge_pair_max_distance: int = 200
    edge_pair_min_distance: int = 15

class RegionBox(BaseModel):
    """A candidate region from CV analysis."""
    x: int
    y: int
    w: int
    h: int
    confidence: float
    label: str

class AnalyzeRegionsResponse(BaseModel):
    """Response from CV region analysis."""
    regions: List[RegionBox] = Field(default_factory=list)

class AnalyzeRegionsDebugResponse(BaseModel):
    """Response from CV region analysis with debug overlays."""
    regions: List[RegionBox] = Field(default_factory=list)
    edge_overlay_b64: str = ""
    lines_overlay_b64: str = ""
    horizontal_count: int = 0
    pair_count: int = 0

class SegmentFieldRequest(BaseModel):
    """Request body for field segmentation."""
    image: str
    hue_low: int = 30
    hue_high: int = 85
    sat_low: int = 30
    sat_high: int = 255
    val_low: int = 30
    val_high: int = 255
    morph_kernel: int = 15
    min_area_ratio: float = 0.05

class SegmentFieldResponse(BaseModel):
    """Response from field segmentation."""
    boundary: List[List[int]] = Field(default_factory=list)
    coverage: float = 0.0
    mask_b64: str = ""

class SegmentFieldDebugResponse(BaseModel):
    """Response from field segmentation with debug overlay."""
    boundary: List[List[int]] = Field(default_factory=list)
    coverage: float = 0.0
    mask_overlay_b64: str = ""

class ConfigUpdate(BaseModel):
    """Request body for updating server configuration."""
    device: Optional[str] = None
    yolo_model: Optional[str] = None
    yolo_confidence: Optional[float] = None
    vram_budget_mb: Optional[int] = None
    strategy: Optional[str] = None
    ocr_languages: Optional[List[str]] = None
    ocr_min_confidence: Optional[float] = None