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# -*- coding: UTF-8 -*-
import os,sys
SRCDIR = os.path.join(os.getenv('RUNTIME_BASEDIR',os.path.abspath(os.path.join(os.path.dirname(__file__), '../'))))
sys.path.append(SRCDIR)
import requests
import numpy as np
from faces.save_embedding import download_img_for_svm, down_embedding, \
get_embedding_path, get_image_path, create_embedding_string
from qiniuUpload import qiniu_upload_data, SUFFIX
from uploadFile import useAliyun
from aliyunUpload import aliyun_upload_data
from getDeviceInfo import get_current_groupid, get_deviceid
from urllib2 import Request, urlopen, URLError, HTTPError
import json
from flask import Flask
from migrate_db import People, db
import FaceProcessing
from scipy import misc
import facenet
import subprocess
SVM_TRAIN_WITHOUT_CATEGORY=True
uuid = get_deviceid()
BASEDIR = os.getenv('RUNTIME_BASEDIR',os.path.abspath(os.path.join(os.path.dirname(__file__),'../')))
UPLOAD_FOLDER = os.path.join(BASEDIR, 'image')
DATABASE = 'sqlite:///' + os.path.join(BASEDIR, 'data/data.sqlite')
app = Flask(__name__)
app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
app.config['SQLALCHEMY_DATABASE_URI'] = DATABASE
app.config['SQLALCHEMY_COMMIT_ON_TEARDOWN'] = True
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = True
db.init_app(app)
facenet_model = os.path.join(BASEDIR, 'facenet_models/20170512-110547/20170512-110547.pb')
sess, graph = FaceProcessing.InitialFaceProcessor(facenet_model)
SVM_TRAIN_WITHOUT_CATEGORY=True
uuid = get_deviceid()
def featureCalculation(imgpath):
img = misc.imread(os.path.expanduser(imgpath))
img_size = np.asarray(img.shape)[0:2]
width = img_size[1]
height = img_size[0]
if width != 160 or height != 160:
print("bad image size")
return None
prewhitened = facenet.prewhiten(img)
with graph.as_default():
with sess.as_default():
embedding = FaceProcessing.FaceProcessingImageData(prewhitened, sess, graph)[0]
return embedding
def txt2embedding(file_path):
with open(file_path, 'r') as bottleneck_file:
embedding_string = bottleneck_file.read()
# print(bottleneck_string)
embedding_values = [float(x) for x in embedding_string.split(',')]
embedding = np.array(embedding_values, dtype='f')
return embedding
def recover_db(img_url, faceid, embedding, style='front'):
# 恢复embedding到db
p = People.query.filter_by(aliyun_url=img_url, group_id=group_id).first()
if not p:
people = People(embed=embedding, uuid=uuid, group_id=group_id,
objId=faceid, aliyun_url=img_url, classId=faceid, style=style)
db.session.add(people)
db.session.commit()
print("Add people")
return True
else:
print("No need add people")
return False
'''
old_train_set = TrainSet.query.filter_by(url=img_url, group_id=group_id).first() # 一张图片对应的人是唯一的
if not old_train_set:
new_train_set = TrainSet(url=img_url, group_id=group_id, is_or_isnot=True,
device_id='', face_id=face_id, filepath='', drop=False, style=style)
db.session.add(new_train_set)
db.session.commit()
'''
def down_img_embedding(img_url, group_id, face_id, style='front'):
# 下载图片及embedding
img_path = get_image_path(img_url, group_id, face_id, style)
embedding_path = get_embedding_path(img_path)
embedding_url = img_url + SUFFIX
if not os.path.exists(img_path):
download_img_for_svm(img_url, group_id, face_id, style)
embedding = None
if not os.path.exists(embedding_path):
status = down_embedding(embedding_url, embedding_path)
if not status:
# 下载embedding失败， 开始计算embedding
embedding = featureCalculation(img_path)
if embedding is None:
return False, None
create_embedding_string(embedding, embedding_path)
# 上传一次
key = img_url.rsplit('/', 1)[-1]
embedding_string = ','.join(str(x) for x in embedding)
embedding_bytes = embedding_string.encode('utf-8')
if useAliyun is True:
url = aliyun_upload_data(key, embedding_bytes)
else:
embedding_url = qiniu_upload_data(key, embedding_bytes)
#print('Download embedding file failed, caculate it.')
else:
embedding = txt2embedding(embedding_path)
#print('Download embedding file suc.')
else:
#print('embedding file exist.')
embedding = txt2embedding(embedding_path)
# print('need recover db')
return True, embedding
#return False, None
def migration():
sql_db = os.path.join(os.getenv('RUNTIME_BASEDIR',os.path.abspath(os.path.join(os.path.dirname(__file__),'../'))), 'data/') + 'data.sqlite'
if not os.path.exists(sql_db):
db.create_all()
migrate_db_exe = os.path.join(os.getenv('RUNTIME_BASEDIR',os.path.abspath(os.path.join(os.path.dirname(__file__), '../')))) + 'migrate_db.exe'
migrate_db_py = os.path.join(os.getenv('RUNTIME_BASEDIR',os.path.abspath(os.path.join(os.path.dirname(__file__), '../')))) + 'migrate_db.py'
if os.path.exists(migrate_db_exe):
out_put = subprocess.check_output([migrate_db_exe, 'db', 'upgrade'])
else:
out_put = subprocess.check_output(['python', migrate_db_py, 'db', 'upgrade'])
print(out_put)
print('> finish migrate upgrade')
if __name__ == '__main__':
group_id = get_current_groupid()
total_photos = 0
new_db_photos = 0
migration()
#host="http://localhost:3000/restapi/datasync/token/" + str(group_id)
API_SERVER_ADDRESS = os.getenv('API_SERVER_ADDRESS','workaihost.tiegushi.com')
API_SERVER_PORT = os.getenv('API_SERVER_PORT','80')
host = 'http://'+API_SERVER_ADDRESS+':'+API_SERVER_PORT+'/restapi/datasync/token/' + str(group_id)
result = None
try:
response = urlopen(host, timeout=10)
except HTTPError as e:
print('HTTPError: ', e.code)
except URLError as e:
print('URLError: ', e.reason)
except Exception as e:
print('Error: ', e)
else:
# everything is fine
if 200 == response.getcode():
result = response.readline()
#print(result)
result = json.loads(result)
for person in result:
faceId = person.get("faceId")
urls = person.get("urls")
print('--> {}'.format(faceId))
for url in urls:
print(' {}'.format(url))
with app.app_context():
total_photos = total_photos+1
# url,faceid 从点圈群相册获取
# todo 可以用for循环解析群相册获取的json数据
img_url = url['url']
faceid = faceId
style = url['style']
if SVM_TRAIN_WITHOUT_CATEGORY is True:
style = 'front'
status, embedding = down_img_embedding(img_url, group_id, faceid, style=style)
if status:
isAdded = recover_db(img_url, faceid, embedding, style=style)
if isAdded is True:
new_db_photos = new_db_photos+1
print("total_photos={}, new_db_photos={}".format(total_photos, new_db_photos))
else:
print('response code != 200')