Using cv.matchTemplate to find multiple best matches

I am using the function cv.matchTemplate to try to find template matches.

result = cv.matchTemplate(img, templ, match_method)

After I run the function I have a bunch of answers in list result. I want to filter the list to find the best n matches. The data in result just a large array of numbers so I don't know what criteria to filter based on. Using extremes = cv.minMaxLoc(result, None) filters the result list in an undesired way before converting them to locations.

The match_method is cv.TM_SQDIFF. I want to:

filter the results down to the best matches
Use the results to obtain the locations

How can I acheive this?

Solution

You can treshold the result of matchTemplate to find locations with sufficient match. This tutorial should get you started. Read at the bottom of the page for finding multiple matches.

import numpy as np

threshold = 0.2
loc = np.where( result <= threshold) # filter the results
for pt in zip(*loc[::-1]): #pt marks the location of the match
    cv2.rectangle(img_rgb, pt, (pt[0] + w, pt[1] + h), (0,0,255), 2)

Keep in mind depending on the function you use will determine how you filter. cv.TM_SQDIFF tends to zero as the match quality increases so setting the threshold closer to zero filters out worse. The opposite is true for cv.TM CCORR cv.TM_CCORR_NORMED cv.TM_COEFF and cv.TM_COEFF_NORMED matching methods (better tends to 1)