Score of similarity using SIFT (python)

[Akhou]

Hello,
I need to get the score of comparison of two images using SIFT. I found an example online and I wanted to adapt it with my needs, you'll find below the code.

import cv2
import os
import numpy as np

img1 = cv2.imread("C:/Users/Akhou/Desktop/ALTRAN Tech.jpg")
gray1= cv2.cvtColor(img1,cv2.COLOR_BGR2GRAY)
img2 = cv2.imread("C:/Users/Akhou/Desktop/ALTRAN Tech.jpg")
gray2= cv2.cvtColor(img2,cv2.COLOR_BGR2GRAY)



sift1 = cv2.xfeatures2d.SIFT_create()
kp1, des1 = sift1.detectAndCompute(gray1,None)
sift2 = cv2.xfeatures2d.SIFT_create()
kp2, des2 = sift2.detectAndCompute(gray2,None)

def extractFeatures_SIFT(): 

    featurlist += [kp2, des2]
    bf = cv2.BFMatcher()
    matches1 = bf.knnMatch(des1,des2, k=2)
    good = []
    for m,n in matches1:
        if m.distance < 0.7*n.distance:
            good.append([m])
            a=len(good)
            print(a)
            percent=(a*100)/kp2
            print("{} % similarity".format(percent))
            if percent >= 75.00:
                print('Match Found')
                break;
    return featurlist
print(featurlist)
img3 = cv2.drawMatchesKnn(img1,kp1,img2,kp2,good,None,flags=2)
if __name__ == '__main__':
    extractFeatures_SIFT()

Thank you