没有添加路径 不知道问题在哪 也没有报错 可否讲下代码

没有报错 不知道哪里有问题 程序是github上找的
import cv2
import numpy as np
import pickle as pk
import random
import os
import matplotlib.pyplot as plt
from imageio import imread

def extract_features(image_path, vector_size=32):
image = imread(image_path, mode="RGB")
try:
alg = cv2.SIFT_create()
kps = alg.detect(image)
kps = sorted(kps, key=lambda x: -x.response)[:vector_size]
kps, dsc = alg.compute(image, kps)
dsc = dsc.flatten()
needed_size = (vector_size * 64)
if dsc.size < needed_size:
dsc = np.concatenate([dsc, np.zeros(needed_size - dsc.size)])
except cv2.error as e:
print('Error: ', e)
return None

return dsc

def batch_extractor(images_path, pickled_db_path):
files = [os.path.join(images_path, p) for p in sorted(os.listdir(images_path))]

result = {}
for f in files:
    print('Extracting features from image %s' % f)
    name = f.split('/')[-1].lower()
    result[name] = extract_features(f)

# saving all our feature vectors in pickled file
with open(pickled_db_path, 'w') as fp:
    pickle.dump(result, fp)

class Matcher(object):

def __init__(self, pickled_db_path="features.pck"):
    with open(pickled_db_path) as fp:
        self.data = pickle.load(fp)
    self.names = []
    self.matrix = []
    for k, v in self.data.iteritems():
        self.names.append(k)
        self.matrix.append(v)
    self.matrix = np.array(self.matrix)
    self.names = np.array(self.names)

def cos_cdist(self, vector):
    # getting cosine distance between search image and images database
    v = vector.reshape(1, -1)
    return scipy.spatial.distance.cdist(self.matrix, v, 'cosine').reshape(-1)

def match(self, image_path, topn=5):
    features = extract_features(image_path)
    img_distances = self.cos_cdist(features)
    # getting top 5 records
    nearest_ids = np.argsort(img_distances)[:topn].tolist()
    nearest_img_paths = self.names[nearest_ids].tolis

extract_features在哪里调用呗，路径就是在调用的时候输入的，例如Matcher.match(image_path,5),这里的imgpath就是图像的路径。
或者你可以像我这样在调用里面print一下路径，就知道每次调用的图像在哪里

def extract_features(image_path, vector_size=32):
    image = imread(image_path, mode="RGB")
    print(image_path)