import cv2
import numpy as np
from PIL import Image
from PIL.Image import Image as Image_t
from matplotlib import pyplot as plt

from cv_analysis.utils.conversion import normalize_image_format_to_array


def show_image(image, backend="mpl", **kwargs):
    image = normalize_image_format_to_array(image)
    if backend == "mpl":
        show_image_mpl(image, **kwargs)
    elif backend == "cv2":
        show_image_cv2(image, **kwargs)
    elif backend == "pil":
        Image.fromarray(image).show()
    else:
        raise ValueError(f"Unknown backend: {backend}")


def show_image_cv2(image, maxdim=700, **kwargs):
    h, w, c = image.shape
    maxhw = max(h, w)
    if maxhw > maxdim:
        ratio = maxdim / maxhw
        h = int(h * ratio)
        w = int(w * ratio)

    img = cv2.resize(image, (h, w))
    cv2.imshow("", img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()


def show_image_mpl(image, **kwargs):
    if isinstance(image, Image_t):
        # noinspection PyTypeChecker
        image = np.array(image)
        # noinspection PyArgumentList
        assert image.max() <= 255
    fig, ax = plt.subplots(1, 1)
    fig.set_size_inches(20, 20)
    assert image.dtype == np.uint8
    ax.imshow(image, cmap="gray")
    ax.title.set_text(kwargs.get("title", ""))
    plt.show()


def save_image(image, path):
    cv2.imwrite(path, image)