Template Matching Using OpenCV in Python

Question

I am a newbie in Image Processing and learning about Template Matching by getting some help from OpenCV documentation, but I didn't understand some lines of the code.
Here is the code:

import cv2
import numpy as np
from matplotlib import pyplot as plt
img_rgb = cv2.imread('mario.png')
img_gray = cv2.cvtColor(img_rgb, cv2.COLOR_BGR2GRAY)
template = cv2.imread('coin.png', 0)
w, h = template.shape[::-1]
count = 0

res = cv2.matchTemplate(img_gray, template, cv2.TM_CCOEFF_NORMED)
threshold = 0.8
loc = np.where(res >= threshold)
for pt in zip(*loc[::-1]):
    count += 1
    cv2.rectangle(img_rgb, pt, (pt[0] + w, pt[1] + h), (0,0,255), 2)

cv2.imwrite('res.png', img_rgb)
print(count)

The objective is to template match the coin in the super mario map.
My Questions :
1. In the loop for pt in zip(*loc[::-1]): I put a counter and when I print it, it prints 65, whereas the number of coins is only 19.
2. What is the function of the variable threshold=0.8, when I change its value, the resulting image is changed.

Can anyone help me to answer my question? Thank you in advance.

Answer 1

The threshold 0.8 means the match should be at least 80% of template image and the source region of interest. Thus if it is greater than 80%, it is a coin. If you reduce the threshold the false positive results would increase even if it is not a coin.

for pt in zip(*loc[::-1]): is for the points which have values greater than threshold. zip is a container of all such points and it will iterate to all such points and draw rectangle around this closed entity i.e. coins here.

Answer 2

Threshold = 0.8 works according to lightness on the image you are working on. If lights are proper on your image then threshold > 0.8 will work but mostly in camera images brightness varies so lightness > 0.65 can work. To match more points you have to reduce your threshold value.