opencv图像拼接， 通道合并和分开

拼接

import  cv2
img =cv2.imread(file_path[i])
img=cv2.hconcat([img,img,img])#水平拼接
img=cv2.vconcat([img,img,img])#垂直拼接

合并

# 生成一个值为0的单通道数组
zeros = np.zeros(image.shape[:2], dtype = "uint8")
# 分别扩展B、G、R成为三通道。另外两个通道用上面的值为0的数组填充
cv2.imshow("Blue", cv2.merge([B, zeros, zeros]))
cv2.imshow("Green", cv2.merge([zeros, G, zeros]))
cv2.imshow("Red", cv2.merge([zeros, zeros, R]))
cv2.waitKey(0)

拆分

# 导入库
import numpy as np
import argparse
import cv2
 
# 构造参数解析器
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True, help="Path to the image")
args = vars(ap.parse_args())
 
# 加载图像
image = cv2.imread(args["image"])

# 通道分离，注意顺序BGR不是RGB
(B, G, R) = cv2.split(image)
 
# 显示各个分离出的通道
cv2.imshow("Red", R)
cv2.imshow("Green", G)
cv2.imshow("Blue", B)
cv2.waitKey(0)