opencv 之 图像阈值处理

import cv2
import matplotlib.pyplot as plt
img_org = cv2.imread('test.png')
img = cv2.cvtColor(img_org, cv2.COLOR_BGR2GRAY)
img_org = img_org[:, :, ::-1]
'''
  threshhold(图片, 阈值, 最大值, 类型)
五个常用的阈值操作
  THRESH_BINARY   超过阈值的部分取最大值,否则就是0
  THRESH_BINARY_INV  这个就是把THRESH_BINARY 的结果反过来
  THRESH_TRUNC    大于阈值的部分设为阈值,否则不变
  THRESH_TOZERO   大于阈值部分不变,否则设为0
  THRESH_TOZERO_INV  就是上边的TOZERO的反转
'''
ret, thresh1 = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)
ret, thresh2 = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY_INV)
ret, thresh3 = cv2.threshold(img, 127, 255, cv2.THRESH_TRUNC)
ret, thresh4 = cv2.threshold(img, 127, 255, cv2.THRESH_TOZERO)
ret, thresh5 = cv2.threshold(img, 127, 255, cv2.THRESH_TOZERO_INV)
titles = ['original', 'binary', 'binary_inv', 'trunc', 'tozero', 'tozero_inv']
images = [img_org, thresh1, thresh2, thresh3, thresh4, thresh5]
for i in range(6):
    plt.subplot(2, 3, i+1), plt.imshow(images[i], 'gray')
    plt.title(titles[i])
    plt.xticks([]), plt.yticks([])
plt.show()