图像阈值¶
1. 图像阈值¶
① ret, dst = cv2.threshold(src, thresh, maxval, type)
- src： 输入图，只能输入单通道图像，通常来说为灰度图
- thresh： 阈值
- dst： 输出图
- ret： 阈值
- maxval： 当像素值超过了阈值 ( 或者小于阈值，根据 type 来决定 )，所赋予的值
- type：二值化操作的类型，包含以下5种类型：
- cv2.THRESH_BINARY 超过阈值部分取maxval ( 最大值 )，否则取0
- cv2.THRESH_BINARY_INV THRESH_BINARY的反转
- cv2.THRESH_TRUNC 大于阈值部分设为阈值，否则不变
- cv2.THRESH_TOZERO 大于阈值部分不改变，否则设为0
- cv2.THRESH_TOZERO_INV THRESH_TOZERO的反转
In [1]:
import cv2 #opencv的缩写为cv2
import matplotlib.pyplot as plt # matplotlib库用于绘图展示
import numpy as np # numpy数值计算工具包
# 魔法指令，直接展示图，Jupyter notebook特有
%matplotlib inline
In [2]:
img = cv2.imread('01_Picture/01_cat.jpg',cv2.IMREAD_COLOR)
img_gray = cv2.imread('01_Picture/01_cat.jpg',cv2.IMREAD_GRAYSCALE)
ret, thresh1 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY)
print(ret)
ret, thresh2 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY_INV) # THRESH_BINARY_INV 相对 THRESH_BINARY 黑的变成白的，白的变成黑的
print(ret)
ret, thresh3 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_TRUNC)
print(ret)
ret, thresh4 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_TOZERO)
print(ret)
ret, thresh5 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_TOZERO_INV)
print(ret)
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')
plt.title(titles[i])
plt.xticks([]),plt.yticks([])
plt.show()
127.0 127.0 127.0 127.0 127.0
