template_matching.py

import cv2
import numpy as np
from matplotlib import pyplot as plt

img = cv2.imread('pics/PS/Capture.png',0)
img2 = img.copy()
template = cv2.imread('pics/PS/topleft2.png',0)
w, h = template.shape[::-1]

# All the 6 methods for comparison in a list
methods = ['cv2.TM_CCOEFF', 'cv2.TM_CCOEFF_NORMED', 'cv2.TM_CCORR',
         'cv2.TM_CCORR_NORMED', 'cv2.TM_SQDIFF', 'cv2.TM_SQDIFF_NORMED']

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)

     cv2.rectangle(img,top_left, bottom_right, 255, 2)

     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)

     plt.show()