import numpy as np
from PIL import Image

from image_prediction.info import Info


def random_single_color_image_from_metadata(metadata):
    image = Image.new(
        "RGB", (metadata[Info.WIDTH], metadata[Info.HEIGHT]), color=tuple(map(int, np.random.uniform(size=3) * 255))
    )
    return image


def gray_image_from_metadata(metadata):
    image = Image.new("RGB", (metadata[Info.WIDTH], metadata[Info.HEIGHT]), color=(100, 100, 100))
    return image


def array_to_image(array):
    assert np.all(array <= 1)
    assert np.all(array >= 0)

    if array.shape[-1] == 3:
        mode = "RGB"
    elif array.shape[-1] == 4:
        mode = "RGBA"
    else:
        raise ValueError(f"Unexpected number of channels {array.shape[-1]}. Expected 3 or 4.")

    # noinspection PyTypeChecker
    return Image.fromarray(np.uint8(array * 255), mode=mode)