python opencv sift 图像配准找到特征点

import cv2
import numpy as np
 
def sift_kp(image):
    gray_image = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
    sift=cv2.xfeatures2d.SIFT_create()
    kp,des = sift.detectAndCompute(image,None)
    kp_image = cv2.drawKeypoints(gray_image,kp,None)
    return kp_image,kp,des
 
 
def get_good_match(des1,des2):
    bf = cv2.BFMatcher()
    matches = bf.knnMatch(des1, des2, k=2) #des1为模板图，des2为匹配图
    matches = sorted(matches,key=lambda x:x[0].distance/x[1].distance)
    good = []
    for m, n in matches:
        if m.distance < 0.75 * n.distance:
            good.append(m)
    return good
 
 
def siftImageAlignment(img1,img2):
   _,kp1,des1 = sift_kp(img1)
   _,kp2,des2 = sift_kp(img2)
   goodMatch = get_good_match(des1,des2)
   if len(goodMatch) > 4:
       ptsA= np.float32([kp1[m.queryIdx].pt for m in goodMatch]).reshape(-1, 1, 2)
       ptsB = np.float32([kp2[m.trainIdx].pt for m in goodMatch]).reshape(-1, 1, 2)
       ransacReprojThre