import cv2
import numpy as np


def clahe_canny(bgr: np.ndarray) -> np.ndarray:
    """Return 3-channel image. Must match the preprocessing used to train the
    weights currently loaded by the detector."""
    gray     = cv2.cvtColor(bgr, cv2.COLOR_BGR2GRAY)
    enhanced = cv2.createCLAHE(clipLimit=6.0, tileGridSize=(16, 16)).apply(gray)
    return cv2.merge([enhanced, enhanced, enhanced])     # [C, C, C] — matches `clahe_best_yolox`


def to_gray_3ch(bgr: np.ndarray) -> np.ndarray:
    """Grayscale replicated to 3 channels (baseline pipeline input)."""
    g = cv2.cvtColor(bgr, cv2.COLOR_BGR2GRAY)
    return cv2.merge([g, g, g])