pixel_numb = img2.shape[0] * img2.shape[1]
prom_pond = 1/pixel_numb
bins = 100

hist = img3
final_thresh = -1
final_value = -1
intensity = np.arange(100)
for x in range (1,100):
    pcb = np.sum(hist[:x])
    pcf = np.sum(hist[x:])
    wb = pcb * prom_pond
    wf = pcf * prom_pond
    
    mub = np.sum(intensity[:x] * hist[:x]) / (pcb)
    muf = np.sum(intensity[x:] * hist[x:]) / (pcf)
    
    value = wb * wf * (mub-muf) **2
    if value > final_value:
        final_thresh = x/100
        final_value = value

print(final_thresh)
img8 = img2.copy()
img8[img2 > final_thresh] = 1
img8[img2 < final_thresh] = 0

plt.figure(6)
plt.title('Binarizacion por el método de Otsu')
plt.imshow(img8,'gray')