Python 2.7 使用ORB图像功能匹配时出现OpenCV python错误

我试图使用OpenCV ORB匹配两个图像，如中所述

这是我的密码：

import numpy as np
import cv2
import six
import pyparsing
import dateutil
from matplotlib import pyplot as plt
import timeit
import os
import sys

img1_path  = 'img1.jpg'
img2_path  = 'img2.jpg'

img1 = cv2.imread(img1_path,0) # queryImage
img2 = cv2.imread(img2_path,0) # trainImage

orb = cv2.ORB()

kp1, des1 = orb.detectAndCompute(img1,None)
kp2, des2 = orb.detectAndCompute(img2,None)

FLANN_INDEX_LSH = 6

index_params= dict(algorithm = FLANN_INDEX_LSH,
                   table_number = 6, # 12
                   key_size = 12,     # 20
                   multi_probe_level = 1) #2

search_params = dict(checks = 50)
flann = cv2.FlannBasedMatcher(index_params, search_params)

matches = flann.knnMatch(des1,des2,k=2)

if len(matches)>0:
    print "%d total matches found" % (len(matches))
else:
    print "No matches were found - %d" % (len(good))
    sys.exit()

# store all the good matches as per Lowe's ratio test.
good = []
for m,n in matches:
    if m.distance < 0.6*n.distance:
        good.append(m)

当img2明显是img1的较小子映像时，就会发生这种情况

（如果img2是原始图像，img1是修改后的图像，则表示有人向原始图像添加了详细信息）

如果我在文件名img1、img2之间切换，那么脚本运行时不会出现问题

---

查询图像（img1）必须小于或等于列车图像（img2）？

必须检查匹配列表中的每个成员是否确实存在两个邻居。这与图像大小无关

good = []
for m_n in matches:
  if len(m_n) != 2:
    continue
  (m,n) = m_n
  if m.distance < 0.6*n.distance:
    good.append(m)

good=[]
对于匹配中的m_n：
如果len（m_n）！=2:
持续
（m，n）=m_n
如果m.距离<0.6*n.距离：
好。追加（m）

good = []
for m_n in matches:
  if len(m_n) != 2:
    continue
  (m,n) = m_n
  if m.distance < 0.6*n.distance:
    good.append(m)