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