"""Shared types for swappable vision targets."""

from __future__ import annotations

from dataclasses import dataclass

import numpy as np


@dataclass(frozen=True)
class Detection:
    """One detected object in image pixel coordinates."""

    label: str
    cx: float
    cy: float
    radius: float
    score: float  # 0..1 confidence / quality
    width: float | None = None  # minAreaRect width (rect detections)
    height: float | None = None
    angle: float | None = None  # minAreaRect angle in degrees


class TargetDetector:
    """Interface every target module should implement."""

    name: str = "target"

    def detect(self, frame_bgr: np.ndarray) -> list[Detection]:
        raise NotImplementedError

    def annotate(self, frame_bgr: np.ndarray, detections: list[Detection]) -> np.ndarray:
        """Draw detections on a copy of the frame and return it."""
        import cv2

        out = frame_bgr.copy()
        for d in detections:
            center = (int(round(d.cx)), int(round(d.cy)))
            if d.width is not None and d.height is not None and d.angle is not None:
                rect = (
                    (float(d.cx), float(d.cy)),
                    (float(d.width), float(d.height)),
                    float(d.angle),
                )
                box = cv2.boxPoints(rect).astype(int)
                cv2.drawContours(out, [box], 0, (0, 255, 0), 2)
                cv2.drawMarker(out, center, (0, 255, 255), cv2.MARKER_CROSS, 12, 2)
            else:
                radius = max(1, int(round(d.radius)))
                cv2.circle(out, center, radius, (0, 255, 0), 2)
                cv2.drawMarker(out, center, (0, 255, 255), cv2.MARKER_CROSS, 12, 2)
            cv2.putText(
                out,
                f"{d.label} {d.score:.2f}",
                (center[0] + 8, center[1] - 8),
                cv2.FONT_HERSHEY_SIMPLEX,
                0.45,
                (0, 255, 0),
                1,
                cv2.LINE_AA,
            )
        return out