class OrderDAO():
def __init__(self):
self.db_helper = DBHelper()
self.db_helper.open_conn()
def __del__(self):
self.db_helper.close_conn()
def query_all_order(self):
'''
查询所有订单
:return: 所有订单实体组成的列表(list) or None
'''
order_list = []
sql = 'SELECT * FROM orders LIMIT 0,10'
result = self.db_helper.do_query(sql)
if not result:
print('查询结果为空')
return None
for row in result:
order_id = row[0]
cust_id = row[1]
if row[4]:
products_num = int(row[4])
else:
products_num = 0
if row[5]:
amt = float(row[5])
else:
amt = 0
order_list.append(Order(order_id, cust_id, products_num, amt))
return order_list
def query_by_id(self, id):
sql = 'select * from orders WHERE order_id = %s' % (id)
result = self.db_helper.do_query(sql)[0]
if not result:
print('查询结果为空')
return None
order_id = result[0]
cust_id = result[1]
if result[4]:
products_num = int(result[4])
else:
products_num = 0
if result[5]:
amt = float(result[5])
else:
amt = 0
order = Order(order_id, cust_id, products_num, amt)
return order
caffe.set_device(1) # 假如有多块gpu，选择第一块gpu
caffe.set_mode_gpu() # 设置用GPU来加载Caffe并且加载网络
labelmap_path = 'data/KITTI/labelmap_kitti.prototxt'
labelmap = get_labelmap(labelmap_path)
# * Load the net in the test phase for inference, and configure input preprocessing.
model_def = 'models/VGGNet/KITTI3/SSD_300x300/deploy.prototxt'
model_weights = 'models/VGGNet/KITTI3/SSD_300x300/VGG_KITTI_SSD_300x300_iter_80000.caffemodel'
net = caffe.Net(model_def, # defines the structure of the model
model_weights, # contains the trained weights
caffe.TEST) # use test mode (e.g., don't perform dropout)
transformer = input_process(net)
images_path = '/mnt/disk_a/beijing/DataSet/augsburg/'
im_names = []
for index in range(1000):
s = "%06d" % index
im_names.append(str(s) + '.png')
totaltime = 0
db = DBHelper()
db.get_conn()
db.create_database()
db.create_table()
for image_name in im_names:
print '~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~'
totaltime += im_detect(transformer, labelmap, image_name, images_path, db)
db.close_conn()
print 'totaltime = ' + str(totaltime) + ' for ' + str(len(im_names)) + ' images'
print 'averagetime = ' + str(totaltime / len(im_names))
