I'm working with the following python opencv example:
import cv2 import numpy as np from matplotlib import pyplot as pltimg = cv2.imread(‘messi5.jpg’,0)
img2 = img.copy()
template = cv2.imread(‘template.jpg’,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()
The matching works pretty well on a set of chosen images, which clearly contained the template. My problem is that even in images which clearly doesn’t contain the template a rectangle was drawn. How can I fit the source code, so it can handle image which doesn’t match at all.
Thanks in advance
#python #opencv