def __init__(self):
with open('vocabulary-new.pkl', 'rb') as f:
self.voc = pickle.load(f)
url = 'static/'
self.imlist = vocabulary.get_img_list(url)
self.feature = vocabulary.get_feature_list(url)
self.nbr_images = len(self.imlist)
self.ndx = range(self.nbr_images)
self.maxres = 15
self.header = """
<!doctype html>
<head>
<title>Image search</title>
</head>
<body>
"""
self.footer = """
def __init__(self):
with open('vocabulary-new.pkl', 'rb') as f:
self.voc = pickle.load(f)
url = 'static/'
self.imlist = vocabulary.get_img_list(url)
self.feature = vocabulary.get_feature_list(url)
self.nbr_images = len(self.imlist)
self.ndx = range(self.nbr_images)
self.maxres = 15
self.header = """
<!doctype html>
<head>
<title>Image search</title>
</head>
<body>
"""
self.footer = """
# encoding:UTF-8
import pickle
import sift
import imagesearch
import homography
import vocabulary
from vocabulary import *
if __name__=='__main__':
url = '/home/aurora/hdd/workspace/PycharmProjects/data/pcv_img/first1000/'
imlists = vocabulary.get_img_list(url)
feature = vocabulary.get_feature_list(url)
nbr_images = len(imlists)
with open('vocabulary-new.pkl', 'rb') as f:
voc = pickle.load(f)
src = imagesearch.Searcher('test.db', voc)
q_ind = 50
nbr_results = 20
res_reg = [w[1] for w in src.query(imlists[q_ind])[:nbr_images]]
print 'top matches (regular):', res_reg
q_locs, q_descr = sift.read_feature_from_file(feature[q_ind])
fp = homography.make_homog(q_locs[:, :2].T)
model = homography.RansacModel()
rank = {}
# load image features for result
#载入候选图像的特征