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from scipy.stats import qmc
import matplotlib.pyplot as plt
import cv2
from math import floor
import numpy as np

img = cv2.imread('poo.png')
plt_img = plt.imread('poo.png')

l_bounds = [0]
u_bounds = [512]

sampler = qmc.Halton(d=1, scramble=False)
sample = sampler.random(n=500)

sample = qmc.scale(sample, l_bounds, u_bounds).flatten()

thing = []

for i in range(1, 501):
    thing.append((i / 500) * 511)

combined = np.vstack((sample, np.array(thing))).T
print(combined)

colors = []

for i in range(500):
    elem = combined[i]
    x = floor(elem[0])
    y = floor(elem[1])
    
    b,g,r = img[y][x]

    colors.append((r / 255.0,  g/255.0, b / 255.0))

fig, ax = plt.subplots()
ax.scatter(combined[:,0], combined[:,1], c=colors)
ax.imshow(plt_img)
plt.show()