from typing import Optional

import numpy as np

COLOR_BLACK = (0, 0, 0)
COLOR_WHITE = (255, 255, 255)


def to_grayscale(
    img: np.ndarray, min_val: Optional[float] = None, max_val: Optional[float] = None
):
    """
    Convert an arbitrary image to a grayscale image with a value range of [0, 255].

    :param img: the image to be converted to grayscale
    :param min_val: minimum value used for normalization, this is helpful if the image has to be normalized relative to others
    :param max_val: maximum value used for normalization, this is helpful if the image has to be normalized relative to others
    :return: the image in grayscale
    """
    if min_val is None:
        min_val = img.min()

    if max_val is None:
        max_val = img.max()

    if (max_val - min_val) == 0:
        return np.zeros(img.shape, np.uint8)

    _img = (img - min_val) / (max_val - min_val)
    _img = (_img * 255).astype(np.uint8)
    return _img


def grayscale_to_rgb(img: np.ndarray):
    """
    Convert a grayscale image to an rgb image by repeating it three times.

    :param img: the grayscale image to be converted to rgb
    :return: the image in rgb
    """
    assert img.ndim == 2, f"grascale image has more than 2 dimensions {img.shape}"
    return img.repeat(3).reshape((*img.shape, 3))