def console_server(consoles=None):
if not consoles:
location = config.server().get("monitorpath", None)
if location:
consoles = MonitoredConsoleCollection(location=location)
else:
consoles = ConsoleCollection()
consoles.open_all()
# create listening ssh session with cli
reactor.listenTCP(config.server().get("sshport", 8022), TSFactory(consoles))
import numpy as np
import sys
import pickle
import random
from PIL import Image
import cv2
from keras.utils import np_utils
import config
from sklearn.metrics import classification_report
from keras import backend as K
import math
server = config.server()
data_output_path = config.data_output_path()
data_folder_rgb = r'{}rgb/'.format(data_output_path)
data_folder_seq = r'{}seq3/'.format(data_output_path)
def getTrainData(keys, batch_size, classes, mode, train, opt_size, seq=False):
"""
mode 1: Single Stream
mode 2: Two Stream
mode 3: Multiple Stream
"""
while 1:
for i in range(0, len(keys), batch_size):
if not seq:
if mode == 1:
X_train, Y_train = stack_single_stream(
chunk=keys[i:i + batch_size],
opt_size=opt_size,
def process_portmonitor(self, location):
config.server()["monitorpath"] = location
