MeterEye：AI 指示燈與警報燈偵測

@dataclass(frozen=True)
class IndicatorConfigData:
    """Configuration for a single indicator/alarm light (immutable)."""

    id: str
    name: str
    perspective: PerspectivePoints
    detection_mode: str = "brightness"  # brightness or color
    threshold: int = 128  # 0 = auto (Otsu), 1-255 = manual
    on_color: str = "red"  # For color mode: red, green, blue
    show_on_dashboard: bool = True

@dataclass
class IndicatorReading:
    """A single indicator reading (on/off state)."""

    camera_id: str
    indicator_id: str
    state: bool  # True = ON, False = OFF
    brightness: float  # Actual brightness value (0-255) for debugging
    timestamp: datetime

def _detect_by_brightness(self, roi_image: np.ndarray) -> tuple[bool, float, np.ndarray]:
    # 轉灰階
    gray = cv2.cvtColor(roi_image, cv2.COLOR_BGR2GRAY)

    # 計算平均亮度
    brightness = float(np.mean(gray))

    # 決定閾值
    if self.threshold == 0:
        # 自動閾值：Otsu 演算法
        thresh_value, _ = cv2.threshold(
            gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU
        )
    else:
        thresh_value = self.threshold

    # 判定：亮度超過閾值 = ON
    state = brightness > thresh_value

    return state, brightness, debug

# HSV 色彩範圍定義
COLOR_RANGES = {
    "red": [
        # 紅色在 HSV 中跨越 0 度，需要兩個範圍
        ((0, 100, 100), (10, 255, 255)),
        ((160, 100, 100), (180, 255, 255)),
    ],
    "green": [
        ((35, 100, 100), (85, 255, 255)),
    ],
    "blue": [
        ((100, 100, 100), (130, 255, 255)),
    ],
    "yellow": [
        ((20, 100, 100), (35, 255, 255)),
    ],
    "orange": [
        ((10, 100, 100), (20, 255, 255)),
    ],
}

def _detect_by_color(self, roi_image: np.ndarray) -> tuple[bool, float, np.ndarray]:
    # 轉換到 HSV 色彩空間
    hsv = cv2.cvtColor(roi_image, cv2.COLOR_BGR2HSV)

    # 對目標顏色建立遮罩
    mask = np.zeros(hsv.shape[:2], dtype=np.uint8)
    for lower, upper in color_ranges:
        lower_bound = np.array(lower, dtype=np.uint8)
        upper_bound = np.array(upper, dtype=np.uint8)
        mask |= cv2.inRange(hsv, lower_bound, upper_bound)

    # 計算顏色比例（匹配像素的百分比）
    total_pixels = mask.shape[0] * mask.shape[1]
    color_pixels = np.count_nonzero(mask)
    color_ratio = (color_pixels / total_pixels) * 100

    # 超過閾值百分比 = ON
    state = color_ratio > thresh_value

    return state, color_ratio, debug

def _process_frame(self, frame: np.ndarray) -> None:
    timestamp = datetime.now()

    # 處理 Meters（七段顯示器辨識）
    for meter in self._meters:
        warped = apply_perspective_transform(frame, meter.perspective)
        if warped is None:
            continue
        recognizer = self._recognizers[meter.id]
        result, _ = recognizer.recognize(warped)
        # ... 建立 Reading 並發送到 queue

    # 處理 Indicators（燈號偵測）
    for indicator in self._indicators:
        warped = apply_perspective_transform(frame, indicator.perspective)
        if warped is None:
            continue
        detector = self._indicator_detectors[indicator.id]
        state, brightness, _ = detector.detect(warped)
        # ... 建立 IndicatorReading 並發送到 queue

def update_indicators(self, indicators: tuple[IndicatorConfigData, ...]) -> None:
    with self._status_lock:
        for indicator in indicators:
            old_det = old_detectors.get(indicator.id)
            if (old_det and
                old_det.detection_mode == indicator.detection_mode and
                old_det.threshold == indicator.threshold and
                old_det.on_color == indicator.on_color):
                # 設定未變更，復用既有偵測器
                self._indicator_detectors[indicator.id] = old_det
            else:
                # 建立新偵測器
                self._indicator_detectors[indicator.id] = IndicatorDetector(...)