注意
该代码只针对这两张图片进行的实现,对于其他的图像拼接请移步
opencv实现全景图像拼接及结果去黑_鸭鸭爱吃辣的博客-CSDN博客
事例图片
导入必要包
import cv2
import os
import math
import numpy as np
定义人机交互函数
def on_EVENT_LBUTTONDOWN(event, x, y, flags, param):
global input_list
a = len(input_list)
if event == cv2.EVENT_LBUTTONDOWN:
input_list.append([x,y])
cv2.circle(img, (x, y), 3, (255, 0, 0), thickness = -1)
cv2.putText(img, str(a+1), (x, y), cv2.FONT_HERSHEY_PLAIN,
1.0, (0,255,0), thickness = 1)
cv2.imshow("window 2", img)
后面根据图片中相同的点集来计算图片之间的距离差值(由于点击误差太大,给设定了30像素的误差)
dataset_dir = 'photo' #输入文件夹
image_filenames = [(os.path.join(dataset_dir, x))
for x in os.listdir(dataset_dir)] #path为图片地址
all_list = []
for path in image_filenames:
img0 = cv2.imread(path)
img = img0.copy()
input_list = list()
cv2.namedWindow("window 1", flags=cv2.WINDOW_NORMAL | cv2.WINDOW_FREERATIO)
cv2.imshow("window 1", img0)
cv2.namedWindow("window 2", flags=cv2.WINDOW_NORMAL | cv2.WINDOW_FREERATIO)
cv2.imshow("window 2", img)
cv2.setMouseCallback("window 2", on_EVENT_LBUTTONDOWN)
while (1):
if cv2.waitKey(0): # 按ESC键,循环终止,释放所有窗口资源
break
cv2.destroyAllWindows() # 关闭窗口
all_list+=[input_list[:4]] #截取前4个相同的点来作为参考(要按照顺序来进行)
img1 = cv2.imread('./photo/1.png')
img2 = cv2.imread('./photo/2.png')
EX = (all_list[0][0][0] + all_list[0][1][0] + all_list[0][1][0] + all_list[0][1][0])//4 - (all_list[1][0][0] +all_list[1][1][0] + all_list[1][2][0] + all_list[1][3][0])//4
tmp = img2[:,-EX+30:,:] #30为误差值
此时的tmp为需要拼接进img1的部分,然后再计算他所需旋转的角度即可,选取2点计算
img0 = cv2.imread('./photo/1.png')
img = img0.copy()
input_list = list()
cv2.namedWindow("window 1", flags=cv2.WINDOW_NORMAL | cv2.WINDOW_FREERATIO)
cv2.imshow("window 1", img0)
cv2.namedWindow("window 2", flags=cv2.WINDOW_NORMAL | cv2.WINDOW_FREERATIO)
cv2.imshow("window 2", img)
cv2.setMouseCallback("window 2", on_EVENT_LBUTTONDOWN)
while (1):
if cv2.waitKey(0): # 按ESC键,循环终止,释放所有窗口资源
break
cv2.destroyAllWindows() # 关闭窗口
list1 = input_list[:2]
img0 = cv2.imread('./photo/2.png')
img = img0.copy()
input_list = list()
cv2.namedWindow("window 1", flags=cv2.WINDOW_NORMAL | cv2.WINDOW_FREERATIO)
cv2.imshow("window 1", img0)
cv2.namedWindow("window 2", flags=cv2.WINDOW_NORMAL | cv2.WINDOW_FREERATIO)
cv2.imshow("window 2", img)
cv2.setMouseCallback("window 2", on_EVENT_LBUTTONDOWN)
while (1):
if cv2.waitKey(0): # 按ESC键,循环终止,释放所有窗口资源
break
cv2.destroyAllWindows() # 关闭窗口
list2 = input_list[:2]
#计算角度
jiaodu = math.atan2(list2[0][1]-list1[0][1],list2[0][0]-list1[0][0])
后面将tmp选择即可,最后接入img1即可
M = cv2.getRotationMatrix2D((EX-1,0),-jiaodu,1)
dst = cv2.warpAffine(tmp, M, (len(tmp[1]),389))
fin = np.hstack((img1, dst))
cv2.imshow('jieguo',fin)
cv2.imwrite('./out1/result.png'.format(len(fin)), fin)
cv2.waitKey(0)
cv2.destroyAllWindows()
结果
总结
人机交互手搓误差太大,不如自动实现