test_threshold.py

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import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt

def test_random():
    min = 50
    max = 200
    img = np.random.randint(0,200, size=(172,224), dtype=np.uint16)
    ret,thresh1 = cv.threshold(img,min,max,cv.THRESH_BINARY)
    ret,thresh2 = cv.threshold(img,min,max,cv.THRESH_BINARY_INV)
    ret,thresh3 = cv.threshold(img,min,max,cv.THRESH_TRUNC)
    ret,thresh4 = cv.threshold(img,min,max,cv.THRESH_TOZERO)
    ret,thresh5 = cv.threshold(img,min,max,cv.THRESH_TOZERO_INV)

    titles = ['Original Image','BINARY','BINARY_INV','TRUNC','TOZERO','TOZERO_INV']
    images = [img, thresh1, thresh2, thresh3, thresh4, thresh5]
    for i in range(6):
        plt.subplot(2,3,i+1),plt.imshow(images[i],'gray',vmin=0,vmax=255)
        plt.title(titles[i])
        plt.xticks([]),plt.yticks([])
    plt.show()


def test_image():
    img = cv.imread('gradient.jpg',0)
    ret,thresh1 = cv.threshold(img,127,255,cv.THRESH_BINARY)
    ret,thresh2 = cv.threshold(img,127,255,cv.THRESH_BINARY_INV)
    ret,thresh3 = cv.threshold(img,127,255,cv.THRESH_TRUNC)
    ret,thresh4 = cv.threshold(img,127,255,cv.THRESH_TOZERO)
    ret,thresh5 = cv.threshold(img,127,255,cv.THRESH_TOZERO_INV)

    titles = ['Original Image','BINARY','BINARY_INV','TRUNC','TOZERO','TOZERO_INV']
    images = [img, thresh1, thresh2, thresh3, thresh4, thresh5]
    for i in range(6):
        plt.subplot(2,3,i+1),plt.imshow(images[i],'gray',vmin=0,vmax=255)
        plt.title(titles[i])
        plt.xticks([]),plt.yticks([])
    plt.show()

if __name__ == '__main__':
    test_random()