9.Write a program to implement Template matching
 
import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt
 
img = cv.imread('v.jpg', cv.IMREAD_GRAYSCALE)
assert img is not None, "file could not be read, check with os.path.exists()"
img2 = img.copy()
template = cv.imread('template.jpg', cv.IMREAD_GRAYSCALE)
assert template is not None, "file could not be read, check with os.path.exists()"
w, h = template.shape[::-1]
 
# All the 6 methods for comparison in a list
methods = ['cv.TM_CCOEFF', 'cv.TM_CCOEFF_NORMED', 'cv.TM_CCORR', 'cv.TM_CCORR_NORMED', 'cv.TM_SQDIFF', 'cv.TM_SQDIFF_NORMED']
 
for meth in methods:
     img = img2.copy()
     method = eval(meth)
     res = cv.matchTemplate(img,template,method)
     min_val, max_val, min_loc, max_loc = cv.minMaxLoc(res)
 
 # If the method is TM_SQDIFF or TM_SQDIFF_NORMED, take minimum
     if method in [cv.TM_SQDIFF, cv.TM_SQDIFF_NORMED]:
         top_left = min_loc
     else:
         top_left = max_loc
         bottom_right = (top_left[0] + w, top_left[1] + h)
 
     cv.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()


INPUT : 

 template.jpg                                         v.jpg

OUTPUT: 
V.jpg