v1

def calculate_brenner_measure(
    input_image: np.ndarray,
    text_color: Tuple[int, int, int] = (255, 255, 255),
    text_thickness: int = 2,
) -> Tuple[np.ndarray, float]:
    """
    Brenner's focus measure.

    Parameters
    ----------
    input_image : np.ndarray
        The input image in grayscale.
    text_color : Tuple[int, int, int], optional
        The color of the text displaying the Brenner value, in BGR format. Default is white (255, 255, 255).
    text_thickness : int, optional
        The thickness of the text displaying the Brenner value. Default is 2.

    Returns
    -------
    Tuple[np.ndarray, float]
        The Brenner image and the Brenner value.
    """
    # Convert image to grayscale if it has 3 channels
    if len(input_image.shape) == 3:
        input_image = cv2.cvtColor(input_image, cv2.COLOR_BGR2GRAY)

    # Convert image to 16-bit integer format
    converted_image = input_image.astype(np.int16)

    # Get the dimensions of the image
    height, width = converted_image.shape

    # Initialize two matrices for horizontal and vertical focus measures
    horizontal_diff = np.zeros((height, width))
    vertical_diff = np.zeros((height, width))

    # Calculate horizontal and vertical focus measures
    horizontal_diff[:, : width - 2] = np.clip(
        converted_image[:, 2:] - converted_image[:, :-2], 0, None
    )
    vertical_diff[: height - 2, :] = np.clip(
        converted_image[2:, :] - converted_image[:-2, :], 0, None
    )

    # Calculate final focus measure
    focus_measure = np.max((horizontal_diff, vertical_diff), axis=0) ** 2

    # Convert focus measure matrix to 8-bit for visualization
    focus_measure_image = ((focus_measure / focus_measure.max()) * 255).astype(np.uint8)

    # Display the Brenner value on the top left of the image
    cv2.putText(
        focus_measure_image,
        f"Focus value: {focus_measure.mean():.2f}",
        (10, 30),
        cv2.FONT_HERSHEY_SIMPLEX,
        1,
        text_color,
        text_thickness,
    )

    return focus_measure_image, focus_measure.mean()