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test.py
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test.py
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import cv2
import numpy as np
from matplotlib import pyplot as plt
img = cv2.imread('screenshot.PNG',0)
img2 = img.copy()
template = cv2.imread('balloon.PNG',0)
w, h = template.shape[::-1]
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 match
res = cv2.matchTemplate(img,template,method)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
#if method is TM_SQDIFF or TM_SQDIFF_NORMED use minimum
if method in [cv2.TM_SQDIFF_NORMED, cv2.TM_SQDIFF]:
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='magma')
plt.title('matching result'), plt.xticks([]), plt.yticks([])
plt.subplot(122), plt.imshow(img,cmap='magma')
plt.title('detected point'), plt.xticks([]), plt.yticks([])
plt.suptitle(meth)
plt.show()