小白，调用别人python算法进行图片匹配报错。
代码：
import cv2
from matplotlib import pyplot as plt
import numpy as np
import os
import math
def getMatchNum(matches,ratio):
'''返回特征点匹配数量和匹配掩码'''
matchesMask=[[0,0] for i in range(len(matches))]
matchNum=0
for i,(m,n) in enumerate(matches):
if m.distance<ratio*n.distance: #将距离比率小于ratio的匹配点删选出来
matchesMask[i]=[1,0]
matchNum+=1
return (matchNum,matchesMask)
path='D:/code/'
queryPath=path+'yangben/' #图库路径
samplePath=path+'yuanjian/image1.jpg' #样本图片
comparisonImageList=[] #记录比较结果
#创建SIFT特征提取器
sift = cv2.xfeatures2d.SIFT_create()
#创建FLANN匹配对象
FLANN_INDEX_KDTREE=0
indexParams=dict(algorithm=FLANN_INDEX_KDTREE,trees=5)
searchParams=dict(checks=50)
flann=cv2.FlannBasedMatcher(indexParams,searchParams)
sampleImage=cv2.imread(samplePath,0)
kp1, des1 = sift.detectAndCompute(sampleImage, None) #提取样本图片的特征
for parent,dirnames,filenames in os.walk(queryPath):
for p in filenames:
p=queryPath+p
queryImage=cv2.imread(p,0)
kp2, des2 = sift.detectAndCompute(queryImage, None) #提取比对图片的特征
matches=flann.knnMatch(des1,des2,k=2) #匹配特征点，为了删选匹配点，指定k为2，这样对样本图的每个特征点，返回两个匹配
(matchNum,matchesMask)=getMatchNum(matches,0.9) #通过比率条件，计算出匹配程度
matchRatio=matchNum*100/len(matches)
drawParams=dict(matchColor=(0,255,0),
singlePointColor=(255,0,0),
matchesMask=matchesMask,
flags=0)
comparisonImage=cv2.drawMatchesKnn(sampleImage,kp1,queryImage,kp2,matches,None,**drawParams)
comparisonImageList.append((comparisonImage,matchRatio)) #记录下结果
comparisonImageList.sort(key=lambda x:x[1],reverse=True) #按照匹配度排序
count=len(comparisonImageList)
column=4
row=math.ceil(count/column)
#绘图显示
figure,ax=plt.subplots(row,column)
for index,(image,ratio) in enumerate(comparisonImageList):
ax[int(index/column)][index%column].set_title('Similiarity %.2f%%' % ratio)
ax[int(index/column)][index%column].imshow(image)
plt.show()
报错信息：
Traceback (most recent call last):
File "sift7.py", line 55, in
ax[int(index/column)][index%column].set_title('Similiarity %.2f%%' % ratio)
TypeError: 'AxesSubplot' object does not support indexing
求大神指点。
