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

def cv_show(name,img):
    cv2.imshow(name,img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

img = cv2.imread('01_Picture/01_cat.jpg')
cat = img[0:200,0:200] # 选择图片感兴趣的区域
cv_show('cat',cat)

img = cv2.imread('01_Picture/01_cat.jpg')
b,g,r = cv2.split(img)
cv_show('cat_b',b)
print('b.shape:',b.shape) # B通道，单通道，灰度图
cv_show('cat_g',g)
print('g.shape:',g.shape) # G通道，单通道，灰度图
cv_show('cat_r',r)
print('r.shape:',r.shape) # R通道，单通道，灰度图
img = cv2.merge((b,g,r))
print('img.shape:',img.shape) # 3 通道，彩色图

b.shape: (414, 500)
g.shape: (414, 500)
r.shape: (414, 500)
img.shape: (414, 500, 3)

# 只保留 R
img = cv2.imread('01_Picture/01_cat.jpg')
b,g,r = cv2.split(img)
img = cv2.merge((b,g,r))
cur_img = img.copy()
cur_img[:,:,0] = 0 
cur_img[:,:,1] = 0
cv_show('R',cur_img)

# 只保留 G
img = cv2.imread('01_Picture/01_cat.jpg')
cur_img = img.copy()
cur_img[:,:,0] = 0 
cur_img[:,:,2] = 0
cv_show('G',cur_img)

# 只保留 R
img = cv2.imread('01_Picture/01_cat.jpg')
cur_img = img.copy()
cur_img[:,:,1] = 0 
cur_img[:,:,2] = 0
cv_show('B',cur_img)

ROI区域¶

1. 位置提取ROI¶

2. 通道提取ROI¶

2.1 分离 BGR 通道¶

2.2 展示 R 通道¶

2.3 展示 G 通道¶

2.4 展示 R 通道¶