Use only NumPy to create the Normalize Class: Image Normalization is a technique used to touch up images that are too dark or too light for the human viewing experience. Implement a version that outputs images with full dynamic range (0255 pixel intensity). In other words, for each color channel (r, g, b), rescale the range of pixel values for that channel to include both 0 and 255. After normalizing, there should be at least one pixel with a red value of 0, at least one pixel with a red value of 255, at least one pixel with a green value of 0, etc. To normalize a list of numbers nums to the range 0n, set nums[i] = (nums[i]min(nums))/(max(nums)min(nums))n for all i. Be careful! When max(nums) == min(nums), you should not touch that list (why?).

class Normalize(ImageEffect): def apply(pixels: np.ndarray) -> np.ndarray