from PIL import Image
import matplotlib.pyplot as plt
from IPython.display import display
import os
import random
import numpy as np
import numpy.random as rand
import matplotlib.image as mpimg
from PIL import ImageOps
import math
class pictures:
  def __init__(self, dir = 'task4'):
    self.dir = dir
    self.allpictures = []
    i = 1
    while True:
        try:
            self.allpictures.append(Image.open('{}/{}.jpg'.format(dir, i)))
        except FileNotFoundError:
            break
        i = i + 1
  def resize(self, size):
    self.resizepictures = []
    for i in self.allpictures:
        f = i.resize((size[0], size[1]))
        self.resizepictures.append(f)
  def whiteimage(self, image1, image2):
    ar1 = np.asarray(image1)
    ar2 = np.asarray(image2)
    self.templateimage = Image.new('RGB',(ar1.shape[0]*ar2.shape[0], ar1.shape[1]*ar2.shape[1]))
  def mean_color(self, picture):
    ar = np.asarray(picture)
    res = [0, 0, 0]
    res[0] = np.sum(ar[:, :, 0]) / len(ar) / len(ar[0])
    res[1] = np.sum(ar[:, :, 1]) / len(ar) / len(ar[0])
    res[2] = np.sum(ar[:, :, 2]) / len(ar) / len(ar[0])
    return res
    """self.res = np.sum(np.sum(ar, axis = 1), axis = 0)//(ar.shape[0] * ar.shape[1])
    return self.res"""
  def dist(self, color1, color2):
    """self.d = math.sqrt((int(color1[0]) - int(color2[0]))**2 + (int(color1[1]) - int(color2[1]))**2 + (int(color1[2]) - int(color2[2]))**2)
    print(self.d)"""
    self.d = 0
    for i in range(len(color1)):
        res = (color1[i] - color2[i])**2
        self.d = self.d + res
    return round(self.d)
  def get_pixelart(self, image):
    ar = np.asarray(image)
    min_dist = float(1000)
    for i in range(ar.shape[0]):
        for j in range(ar.shape[1]):
            for h in self.resizepictures:
                print(ar[i, j], self.mean_color(h))
                new_min_dist = self.dist(ar[i, j], self.mean_color(h))
                if new_min_dist < min_dist:
                    min_dist = new_min_dist
            min_dist = float(1000)