backend/py/app/models/schemas.py

from typing import Any, Dict, Literal, Optional

from pydantic import BaseModel, Field


class DetectionParams(BaseModel):
    canny_low: Optional[int] = Field(None, ge=0, le=255)
    canny_high: Optional[int] = Field(None, ge=0, le=255)
    harris_k: Optional[float] = Field(None, ge=0.0, le=1.0)
    harris_block: Optional[int] = Field(None, ge=1, le=16)
    harris_ksize: Optional[int] = Field(None, ge=1, le=15)
    hough_thresh: Optional[int] = Field(None, ge=1, le=500)
    hough_min_len: Optional[int] = Field(None, ge=1, le=1000)
    hough_max_gap: Optional[int] = Field(None, ge=0, le=200)
    ellipse_min_area: Optional[int] = Field(None, ge=10, le=100000)
    max_ellipses: Optional[int] = Field(None, ge=1, le=100)
    line_detector: Optional[Literal["hough", "lsd"]] = Field(
        None,
        description="Classical line detector variant to use: 'hough' (default) or 'lsd'.",
    )


class DetectionRequest(BaseModel):
    image: str = Field(..., description="Base64-encoded image (PNG/JPEG).")
    params: Optional[DetectionParams] = None
    mode: Literal["classical", "dl", "both"] = "classical"
    compare: bool = False
    dl_model: Optional[str] = Field(
        None, description="Optional ONNX filename override from ./models."
    )


class DetectionResponse(BaseModel):
    overlay: Optional[str] = None
    overlays: Dict[str, Optional[str]]
    features: Dict[str, Any]
    timings: Dict[str, float]
    fps_estimate: Optional[float] = None
    model: Dict[str, Any]
    models: Dict[str, Dict[str, Any]]