from PIL import Image
import matplotlib.pyplot as plt
import numpy as np
file = "./sample.png "

#Function that returns a threshold
def decideTh(area, ret):
    #Threshold
    th = 0
    #background
    background = 0
    #Area ratio
    bg_ratio = 1 / 2
    count = 0
    #Seeking background
    for i in ret[0]:
        background += i
        if background == 0:
            ratio = 0
        else:
            ratio = background /area
        #Substitute the brightness value until the background exceeds the area ratio
        if ratio  <= bg_ratio:
            th = ret[1][count]
        count+=1

    return th

#A function that converts an image as a histogram and as a threshold
def binari(filename):
    #Histogram area
    area = 0
    #Convert the image to grayscale and assign the brightness value to the function
    img = np.array(Image.open(filename).convert("L")).reshape(-1,1)
    #Convert the brightness value to a histogram and substitute
    ret = (plt.hist(img, bins=255))
    #Find the area of the histogram
    for i in ret[0]:
        area += i
    
    th = decideTh(area,ret)
    return th

print(binari(file))

img = np.array(Image.open(filename).convert("L")).reshape(-1,1)
    ret = (plt.hist(img, bins=255))

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