content: 
  
  
  import cv2
  import numpy as np
  import time
  from matplotlib import pyplot as plt
  
  x = 0
  y = 0
  
  
  def makematchpicture(Grayurl):
      img = cv2.imread(Grayurl, 0)
      img2 = img.copy()
      template = cv2.imread('test.png', 0)
      w, h = template.shape[::-1]
  
      methods = ['cv2.TM_SQDIFF']
  
      for meth in methods:
          img = img2.copy()
          method = eval(meth)
  
          # Apply template Matching
          res = cv2.matchTemplate(img, template, method)
          min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
  
          # If the method is TM_SQDIFF or TM_SQDIFF_NORMED, take minimum
          if method in [cv2.TM_SQDIFF, cv2.TM_SQDIFF_NORMED]:
              top_left = min_loc
          else:
              top_left = max_loc
          bottom_right = (top_left[0] + w, top_left[1] + h)
          print("模板匹配：",int(top_left[0] + w / 2), int(top_left[1] + h / 2))
          cv2.rectangle(img, top_left, bottom_right, 255, 2)
          plt.figure()
          plt.subplot(121), plt.imshow(res, cmap='gray')
          plt.title('Matching Result'), plt.xticks([]), plt.yticks([])
          plt.subplot(122), plt.imshow(img, cmap='gray')
          plt.title('Detected Point'), plt.xticks([]), plt.yticks([])
          plt.suptitle(meth)
          global x
          global y
          x = int(top_left[0] + w / 2)
          y = int(top_left[1] + h / 2)
  