import requests
from PIL import Image
import numpy as np
from io import BytesIO

from matplotlib import pyplot as plt
import plotly.graph_objects as go


def apply_convolution_operator(operator, image):
    if isinstance(image, str):
        image = Image.open(image)
    if isinstance(image, Image.Image):
        x_pixel, y_pixel = image.size

        # turn into editable list of colors
        data = np.asarray(image, dtype=np.uint8)
        # storage for the convoluted image
        data_new = np.zeros([y_pixel, x_pixel, 3], dtype=np.uint8)

        for i in range(1, y_pixel - 1):
            for j in range(1, x_pixel - 1):
                for k in range(3):
                    new_value = (
                            operator[0, 0] * data[i - 1, j - 1, k] +
                            operator[0, 1] * data[i - 1, j, k] +
                            operator[0, 2] * data[i - 1, j + 1, k] +
                            operator[1, 0] * data[i, j - 1, k] +
                            operator[1, 1] * data[i, j, k] +
                            operator[1, 2] * data[i, j + 1, k] +
                            operator[2, 0] * data[i + 1, j - 1, k] +
                            operator[2, 1] * data[i + 1, j, k] +
                            operator[2, 2] * data[i + 1, j + 1, k]
                    )
                    new_value = max(0, min(new_value, 255))
                    data_new[i, j, k] = new_value
        return Image.fromarray(data_new)
    else:
        raise TypeError("Not a valid instance of Image.Image")


g1 = np.array([
    [0, 1, 0],
    [0, 0, 0],
    [0, -1, 0]
])

g2 = np.array([
    [1, 0, 0],
    [0, 0, 0],
    [0, 0, -1]
])

g3 = np.array([
    [0, 0, 0],
    [1, 0, -1],
    [0, 0, 0]
])

g4 = np.array([
    [0, 0, 1],
    [0, 0, 0],
    [-1, 0, 0]
])

identity = np.array([
    [0, 0, 0],
    [0, 1, 0],
    [0, 0, 0]
])

laplace = np.array([
    [0, 1, 0],
    [1, -4, 1],
    [0, 1, 0]
])

"""
url = "https://cdn.prod.www.spiegel.de/images/9f9be1b3-ac0e-49f9-acbd-a809a102f9b6_w960_r1.778_fpx39_fpy30.jpg"
response = requests.get(url)

if response.status_code == 200:
    # image = Image.open(BytesIO(response.content))
    image = Image.open("next_generation.jpg")
    operators = [laplace]
    edited_image = image
    for operator in operators:
        edited_image = apply_convolution_operator(operator, edited_image)
    edited_image = edited_image.convert("RGB")  # Convert to RGB mode
    edited_image.show()
    edited_image.save("edited.jpg")
else:
    print(f"Failed to download image. Status code: {response.status_code}")
"""


class Simulation: