Beispiel #1
0
def add(file):

    targetImgSiftPath = file[:-3] + 'sift'
    sift.process_image(file, targetImgSiftPath)


    voc = vocabulary.Vocabulary('target')
    voc.train([targetImgSiftPath], 100, 10)
    print('vocabulary is:', voc.name, voc.nbr_words)
    locs, descr = sift.read_features_from_file(targetImgSiftPath)


    indx = imagesearch.Indexer('testImaAdd.db', voc)
    indx.add_to_index(file, descr)
    indx.db_commit()

    return voc
from PCV.imagesearch import imagesearch
from PCV.localdescriptors import sift
import sqlite3
from PCV.tools.imtools import get_imlist

#获取图像列表
imlist = get_imlist('training/')
nbr_images = len(imlist)

#获取特征列表
featlist = [imlist[i][:-3] + 'sift' for i in range(nbr_images)]

# load vocabulary
with open('training/vocabulary.pkl', 'rb') as f:
    voc = pickle.load(f)

# 创建索引
indx = imagesearch.Indexer('testImaAdd_training.db', voc)
indx.create_tables()

# go through all images, project features on vocabulary and insert
for i in range(nbr_images):
    locs, descr = sift.read_features_from_file(featlist[i])
    indx.add_to_index(imlist[i], descr)

# commit to database
indx.db_commit()
con = sqlite3.connect('testImaAdd_training.db')
print(con.execute('select count (filename) from imlist').fetchone())
print(con.execute('select * from imlist').fetchone())
Beispiel #3
0
import pickle
from PCV.imagesearch import imagesearch
from PCV.localdescriptors import sift
from sqlite3 import dbapi2 as sqlite
from PCV.tools.imtools import get_imlist

imlist = get_imlist('./first500/')
nbr_images = len(imlist)
featlist = [imlist[i][:-3] + 'sift' for i in range(nbr_images)]
# load vocabulary
with open('./first500/vocabulary.pkl', 'rb') as f:
    voc = pickle.load(f)
# create indexer
indx = imagesearch.Indexer('web.db', voc)
indx.create_tables()
# go through all images, project features on vocabulary and insert
for i in range(nbr_images)[:500]:
    locs, descr = sift.read_features_from_file(featlist[i])
    indx.add_to_index(imlist[i], descr)
# commit to database
indx.db_commit()

con = sqlite.connect('web.db')
print con.execute('select count (filename) from imlist').fetchone()
print con.execute('select * from imlist').fetchone()
Beispiel #4
0
import pickle
from PCV.imagesearch import imagesearch
from PCV.localdescriptors import sift
from sqlite3 import dbapi2 as sqlite
from PCV.tools.imtools import get_imlist
import os

path = "F:\\BaiduNet\\ukbench\\full\\"
imlist = [os.path.join(path, f) for f in os.listdir(path)]
imnbr = len(imlist)
featlist = [imlist[i].split('\\')[-1][:-3] + 'sift' for i in range(imnbr)]

with open('vocabulary.pkl', 'rb') as f:
    voc = pickle.load(f)

index = imagesearch.Indexer('testImgAdd.db', voc)
index.create_tables()

for i in range(imnbr)[:500]:
    locs, descr = sift.read_features_from_file(featlist[i])
    index.add_to_index(imlist[i], descr)

index.db_commit()

con = sqlite.connect('testImgAdd.db')
print con.execute('select * from imlist').fetchone()