函数:cv2.threshold()
这个函数有四个参数,
第一个原图像,必须是单通道
第二个进行分类的阈值,
第三个是高于(低于)阈值时赋予的新值,
第四个是一个方法选择参数,常用的有:
• cv2.THRESH_BINARY(黑白二值)
• cv2.THRESH_BINARY_INV(黑白二值反转)
• cv2.THRESH_TRUNC (得到的图像为多像素值)
• cv2.THRESH_TOZERO
• cv2.THRESH_TOZERO_INV
该函数有两个返回值,第一个retVal(得到的阈值值(在后面一个方法中会用到)),第二个就是阈值化后的图像
这里把阈值设置成了127,对于BINARY方法,当图像中的灰度值大于127的重置像素值为255.
import cv2
import matplotlib.pyplot as plt
img = cv2.imread(r'D:\meinv.jpg')
img_2 = img[:,:,[2,1,0]]
print(img_2.shape)
gray = cv2.cvtColor(img,cv2.COLOR_RGB2GRAY)
ret1,thresh1 = cv2.threshold(gray,127,255,cv2.THRESH_BINARY)
ret2,thresh2 = cv2.threshold(gray,127,255,cv2.THRESH_BINARY_INV)
ret,thresh3 = cv2.threshold(gray,127,255,cv2.THRESH_TRUNC)
ret,thresh4 = cv2.threshold(gray,127,255,cv2.THRESH_TOZERO)
ret,thresh5 = cv2.threshold(gray,127,255,cv2.THRESH_TOZERO_INV)
titles = ['img','BINARY','BINARY_INV','TRUNC','TOZERO','TOZERO_INV']
images = [img_2,thresh1,thresh2,thresh3,thresh4,thresh5]
for i in range(6):
plt.subplot(2,3,i+1)
plt.imshow(images[i])
plt.title(titles[i])
plt.show()
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