threshold2.py

import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt
img = cv.imread('lena_copy.png', 0)
#_, th1 = cv.threshold(img, 127, 255, cv.THRESH_BINARY)
_, th1 = cv.threshold(img, 50, 255, cv.THRESH_BINARY)
#_, th2 = cv.threshold(img, 127, 255, cv.THRESH_BINARY_INV)
_, th2 = cv.threshold(img, 200, 255, cv.THRESH_BINARY_INV)
_, th3 = cv.threshold(img, 127, 255, cv.THRESH_TRUNC)
_, th4 = cv.threshold(img, 127, 255, cv.THRESH_TOZERO)
_, th5 = cv.threshold(img, 127, 255, cv.THRESH_TOZERO_INV)

titles = ['Original Image', 'BINARY', 'BINARY_INV', 'TRUNC', 'TOZERO', 'TOZERO_INV']
images = [img, th1, th2, th3, th4, th5]

for i in range(6):
    plt.subplot(2,3, i + 1), plt.imshow(images[i], 'gray')
    plt.title(titles[i])
    plt.xticks([]), plt.yticks([])

#cv.imshow("image", img)
#cv.imshow("th1", th1)
#cv.imshow("th2", th2)
#cv.imshow("th3", th3)
#cv.imshow("th4", th4)
#cv.imshow("th5", th5)
plt.show()
#cv.waitKey(0)
#cv.destroyAllWindows()