def get_radio_info():
client = Client()
client.connect(host, port)
print("Sending request to server...")
# object variables as dict
client.send(iradio_structs.station_info_request().__dict__)
radio_list = client.recv()
print("radio_list recieved")
return jsonify(**radio_list)
# default uses python 2
import sys, os
base_video_dir = os.environ['CLOUD_ROOT_DIR']
utils_dir = base_video_dir + '/utils/'
sys.path.append(utils_dir)
from jsonsocket import Client, Server
host = 'localhost'
port = 8000
# Client code:
client = Client()
#client.connect(host, port).send({'some_list': [123, 456]})
client.connect(host, port).send([123, 456])
response = client.recv()
print('response: ', response)
# response now is {'data': {'some_list': [123, 456]}}
client.close()
# ONLY IF WE OFFLOAD, query the cloud model with the embedding
if offload_decision:
# whether we have offloaded once for this frame
at_least_one_offload = True
# embedding vector to send to cloud server over a socket
embedding_vec_to_send_dict = {
'frame': frame_number,
'emb': [str(x) for x in vec[0]]
}
# connect to server and send
client.connect(host, port).send(embedding_vec_to_send_dict)
# recieve the results back
cloud_response_dict = client.recv()
# unpack the label from the cloud
cloud_name = cloud_response_dict['cloud_name']
cloud_SVM_proba = cloud_response_dict['cloud_SVM_proba']
cloud_numeric_prediction = cloud_response_dict[
'cloud_numeric_prediction']
print('frame: ', frame_number, 'RESPONSE CLOUD NAME: ',
cloud_name, 'RESPONSE SVM PROBA: ', cloud_SVM_proba,
'CLOUD PRED: ', cloud_numeric_prediction)
else:
# this is PURELY for training a model
cloud_name, cloud_SVM_proba = query_facenet_model_SVM(
vec=vec, recognizer=cloud_recognizer, le=cloud_le)
cloud_numeric_prediction = get_numeric_prediction(
#!/usr/bin/python # This is client.py file
from jsonsocket import Client
host = '192.168.12.1'
port = 7878 # Reserve a port for your service.
client = Client()
print 'Client starts.'
client.connect((host, port))
print 'Client connected.'
client.send({'tx_id': 1234, 'amount': 4321})
response = client.recv()
print response
client.close()
