这篇文章主要讲解了“python+opencv怎么实现堆叠图片”，文中的讲解内容简单清晰，易于学习与理解，下面请大家跟着小编的思路慢慢深入，一起来研究和学习“python+opencv怎么实现堆叠图片”吧！
代码如下：
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# import cv2
# import numpy as np
#
# img = cv2.imread('../images/full.jpg')
#
# img_hor = np.hstack((img,img))
# img_ver = np.vstack((img,img))
#
# cv2.imshow('Horizontal',img_hor)
# cv2.imshow('Vertical',img_ver)
#
# cv2.waitKey(0)
import cv2
import numpy as np
def stackImages(scale,imgArray):
rows = len(imgArray)
cols = len(imgArray[0])
rowsAvailable = isinstance(imgArray[0], list)
width = imgArray[0][0].shape[1]
height = imgArray[0][0].shape[0]
if rowsAvailable:
for x in range ( 0, rows):
for y in range(0, cols):
if imgArray[x][y].shape[:2] == imgArray[0][0].shape [:2]:
imgArray[x][y] = cv2.resize(imgArray[x][y], (0, 0), None, scale, scale)
else:
imgArray[x][y] = cv2.resize(imgArray[x][y], (imgArray[0][0].shape[1], imgArray[0][0].shape[0]), None, scale, scale)
if len(imgArray[x][y].shape) == 2: imgArray[x][y]= cv2.cvtColor( imgArray[x][y], cv2.COLOR_GRAY2BGR)
imageBlank = np.zeros((height, width, 3), np.uint8)
hor = [imageBlank]*rows
hor_con = [imageBlank]*rows
for x in range(0, rows):
hor[x] = np.hstack(imgArray[x])
ver = np.vstack(hor)
else:
for x in range(0, rows):
if imgArray[x].shape[:2] == imgArray[0].shape[:2]:
imgArray[x] = cv2.resize(imgArray[x], (0, 0), None, scale, scale)
else:
imgArray[x] = cv2.resize(imgArray[x], (imgArray[0].shape[1], imgArray[0].shape[0]), None,scale, scale)
if len(imgArray[x].shape) == 2: imgArray[x] = cv2.cvtColor(imgArray[x], cv2.COLOR_GRAY2BGR)
hor= np.hstack(imgArray)
ver = hor
return ver
img = cv2.imread('../images/lanbojini.jpg')
imgGray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
imgStack = stackImages(0.5,([img,imgGray,img],[img,img,img]))
# imgStack = stackImages(0.5,([img,imgGray,img],[img,img,img]))
# imgHor = np.hstack((img,img))
# imgVer = np.vstack((img,img))
#
# cv2.imshow("Horizontal",imgHor)
# cv2.imshow("Vertical",imgVer)
cv2.imshow("ImageStack",imgStack)
cv2.waitKey(0)效果：
感谢各位的阅读，以上就是“python+opencv怎么实现堆叠图片”的内容了，经过本文的学习后，相信大家对python+opencv怎么实现堆叠图片这一问题有了更深刻的体会，具体使用情况还需要大家实践验证。这里是亿速云，小编将为大家推送更多相关知识点的文章，欢迎关注！
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