def run_server(classifier):
"""
Runs the OSC server for providing predictions.
:param classifier: Trained tensorflow classifier
:return:
"""
server = osc_server.OscServer("127.0.0.1", 54321, classifier)
server.run_server()
if operation_type == OPERATION_TYPE_CLIENT:
osc_order_path += 'client/'
elif operation_type == OPERATION_TYPE_TRASHED_CLIENT:
osc_order_path += 'trashed_client/'
elif operation_type == OPERATION_TYPE_SERVER:
osc_order_path += 'server/'
elif operation_type == OPERATION_TYPE_SESSION:
osc_order_path += 'session/'
osc_order_path += operation
if operation_type == OPERATION_TYPE_CONTROL and operation == 'stop':
osc_order_path = '/ray/server/quit'
import osc_server # see top of the file
server = osc_server.OscServer(detach)
server.setOrderPathArgs(osc_order_path, arg_list)
daemon_process = None
if (daemon_started
and not (operation_type == OPERATION_TYPE_CONTROL
and operation in ('start_new', 'start_new_hidden'))):
if (operation_type == OPERATION_TYPE_CONTROL and operation == 'stop'):
daemon_port_list = []
if wanted_port:
daemon_port_list.append(wanted_port)
else:
for daemon in daemon_list:
if (daemon.user == os.getenv('USER')
and not daemon.not_default):