def __init__(self,
name=None,
passwd=None,
project=None,
flag='non-sys',
domain='default'):
self.__users_url = ('http://' + utils.init_data().get('host', 'IP') +
':' + utils.init_data().get('keystone', 'PORT') +
'/' +
utils.init_data().get('keystone', 'VERSION') +
'/users')
self.flag = flag
self.domain = domain
self.name = name
self.passwd = passwd
self.project = project
self.identification = None
self.enable = False
self.endpoint = {}
# TODO(dc) user quota
# TODO(dc) self.quota = None
self.token = utils.get_token(self)
self.headers = {
'User-Agent': utils.init_data().get('agent', 'ALL'),
'X-Auth-Token': self.token,
"Content-type": "application/json",
"Accept": "application/json"
}
self._set_info()
def load_data(args):
"""
Iterate through each file in data_folder and construct
the input data features (40-len DNA).
:param data_folder: path to folder of data
:param exclude: kth file to exclude in cross-validation
:returns type list: list of dicts for DNA-arr & label
"""
data = init_data(args)
x = data['X_plus'] + data['X_minus']
y = data['Y_plus'] + data['Y_minus']
ret = []
for img, label in zip(x, y):
ret.append({'x': img, 'y': label})
# for f_path in glob.glob(data_files):
# with open(f_path) as f_in:
# for line in f_in.read().splitlines():
# dna_arr, label = convert_data(line)
# data.append({
# 'x': dna_arr,
# 'y': label
# })
return ret
def start_train(epochs=10000,
target_park='宝琳珠宝交易中心',
start='2016-01-02',
end='2017-01-02'):
seqs_normal, adj, node_f, nks, conns, _, _ = utils.init_data(
target_park, start, end)
batch_size = 96 * 7 * fix_weeks
seqs_normal = seqs_normal.take(range(96 * 7 * 0, 96 * 7 * total_weeks))
use_gru_bag = [True, False]
use_gcn_bag = [True, False]
monitor = False
for (use_gru, use_gcn) in itertools.product(use_gru_bag, use_gcn_bag):
name = target_park + '/GAN' + ('_GCN' if use_gcn else
'') + ('_GRU' if use_gru else '')
print('Starting ' + name)
site_path = root_path + name
if not os.path.exists(site_path):
os.makedirs(site_path)
else:
continue
describe_site(nks, seqs_normal, site_path, target_park, node_f)
train = Train(seqs_normal, adj, node_f, epochs, nks[target_park],
use_gcn, batch_size, use_gru)
# print(train.generator.summary())
train_time_consumed, final_epoch = train(epochs, site_path, batch_size,
monitor)
if final_epoch < epochs:
epochs = final_epoch
monitor = False
# evaluation
metrics_ = train.evaluate(site_path, batch_size)
metrics_['name'] = name
metrics_['train_time_consumed'] = round(train_time_consumed, 2)
metrics_['final_epoch'] = final_epoch
metrics.write_metrics(root_path, metrics_)
def main(FLAGS):
train_data, test_data = init_data(FLAGS)
assert FLAGS.model_type in ['conv', 'res']
if FLAGS.model_type == 'conv':
model = ConvModel(train_data, test_data, FLAGS)
elif FLAGS.model_type == 'res':
model = ResModel(train_data, test_data, FLAGS)
model.compile()
model.train()
def __init__(self):
self.token = utils.get_token()
self.enable = True
self.__headers = {
'User-Agent': utils.init_data().get('agent', 'ALL'),
'X-Auth-Token': self.token,
"Content-type": "application/json",
"Accept": "application/json"
}
self.__roles_url = utils.get_endpoint(self.token,
'keystone') + '/roles'
def register_user(
key=None,
auth='vdc'
): # TODO(dc): domain is not concerned and set to default
"""
:param key: openstack project key that database contain
:param auth: access openstack model and value is 'system' and 'vdc'
:return: class user that will be used in other api
"""
project_manager = project.ProjectManger()
user_manager = user.UserManager()
if auth == 'system' and key is None:
return user_manager.get(
name=utils.init_data().get('host', 'ADMIN'),
passwd=utils.init_data().get('host', 'PASSWD'),
project=project_manager.get(
name=utils.init_data().get('host', 'PROJECT')),
domain=utils.init_data().get('host', 'DOMAIN'),
flag='sys')
elif auth == 'vdc':
if key is None:
warnings.warn("Wrong param key!")
return None
if isinstance(key, str) is False:
warnings.warn("Wrong param key!")
return None
return user_manager.get(
project=project_manager.get(key[0:(len(key) / 3)]),
name=key[(len(key) / 3):(2 * len(key) / 3)],
passwd=key[(2 * len(key) / 3):],
domain=utils.init_data().get('host', 'DOMAIN'))
else:
warnings.warn("Register_user wrong auth parameters!")
import warnings
import cv2 as cv
import tensorflow as tf
import utils
from matplotlib import pyplot as plt
PLOT_PNG = '_plot.png'
COLOR_TITLE = 'maroon'
FONT_SIZE = 20
FIG_SIZE = 7
warnings.simplefilter(action='ignore', category=FutureWarning)
path = 'static/animals'
path_gen = 'static/generated/'
categories, img_size, norm = utils.init_data(path)
seq_model = tf.keras.models.load_model('static/models/model-20.model',
compile=False)
def show_category_probability(predictions, animal_predicted):
colors = ['magenta', 'turquoise', 'yellow'] # Cat, Dog, Panda respectively
explode = (0.03, 0.03, 0.03)
percentage = [predictions[0][0], predictions[0][1], predictions[0][2]]
plt.figure(figsize=[FIG_SIZE, FIG_SIZE])
plt.title('Animal Probability', fontsize=FONT_SIZE, color=COLOR_TITLE)
plt.pie(percentage,
labels=categories,
autopct='%1.4f%%',
explode=explode,