opencv python 图像拼接_OpenCV-Python 图片简单处理 & 拼接对比

import cv2

import numpy as np

img = cv2.imread("Resources/The Legend of Zelda.jpg")

kernel = np.ones((5, 5), np.uint8) # 卷积核

# 颜色空间转换，转换成灰度图(注意是BGR而不是RBG)

imgGray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# 平滑处理，高斯模糊, 高斯核的宽和高只能是奇数

imgBlur = cv2.GaussianBlur(imgGray, (5, 5), 0)

# 边缘检测, 实际也是采用了高斯模糊去除噪音并设置梯度阈值进行过滤

imgCanny = cv2.Canny(img, 150, 200)

# 膨胀，可以适当增加迭代次数

imgDilated = cv2.dilate(imgCanny, kernel, iterations=1)

# 侵蚀

imgEroded = cv2.erode(imgDilated, kernel, iterations=1)

# 缩小到0.2倍并拼接

imgStack = stackImages(0.2, [[img, imgGray, imgBlur],

[imgCanny, imgDilated, imgEroded]])

cv2.imshow("Image Stack", imgStack)

cv2.waitKey(0)

其中stackImage函数的定义为

def stackImages(scale, imgArray):

'''

图像堆栈，可缩放，按列表排列，不受颜色通道限制

'''

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

封装了numpy中的vstack和hstack，方便使用

效果: