class ClientThread(threading.Thread):
def __init__(self, config, host='192.168.137.183', port=8000):
super(ClientThread, self).__init__()
self.config = config
self.data = []
self.host = host
self.port = port
self.path = config.root + config.test_path + 'data' + self.host + 'temp.pkl'
self.device = torch.device("cpu")
self.model = torch.load(config.root + config.model_path,
map_location=torch.device('cpu')).to(
self.device)
self.model.eval()
self.do_run = True
self.data = []
self.v = Visualizer()
def __start_socket(self):
self.socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.socket.connect((self.host, self.port))
def __stop_socket(self):
self.socket.close()
def __test(self):
dataset = WifiData(self.config, test=True)
test_loader = DataLoader(dataset, batch_size=1)
for data, _ in test_loader:
data = data.to(self.device)
logits = self.model(data)
logits = logits.detach().numpy()[0]
logits[0] = np.clip(logits[0], self.config.x_min,
self.config.x_max)
logits[1] = np.clip(logits[1], self.config.y_min,
self.config.y_max)
# pos = np.around(logits)
self.v.update(logits[0], logits[1])
print(logits)
def run(self):
self.__start_socket()
t = threading.currentThread()
while getattr(t, "do_run", True):
datas = []
for i in range(1):
outdata = self.socket.recv(8192)
# data = pickle.loads(data) #data loaded.
try:
outdata = ast.literal_eval(outdata.decode())
except:
print(len(outdata))
break
data = {}
for key, value in outdata.items():
outdata[key] = float(value) / 70
data['Feature'] = outdata
self.data.append(data)
print('Recieve a dict with length %d from %s' %
(len(outdata), self.host))
# Start testing
datas.append(data)
with open(self.path, 'wb') as fout:
pickle.dump(datas, fout)
self.__test()
self.__stop_socket()
class ClientThread():
def __init__(self, config, host='192.168.137.183', port=8000):
super(ClientThread, self).__init__()
self.config = config
self.data = []
self.host = host
self.port = port
self.path = config.root + config.test_path + 'data' + self.host + 'temp.pkl'
self.device = torch.device("cpu")
parser = argparse.ArgumentParser(
description='Wifi Indoor Positioning System')
args = parser.parse_args()
args.feat_dim = config.n_address
args.dropout = 0.0
self.model = DNN_8(args)
self.model.load_state_dict(
torch.load(
"./checkpoints/address_128_8_layer_jitter_0.05_valsplit_0.01/models/model.t7",
map_location=self.device))
self.model.to(self.device)
self.model.eval()
print(self.model)
self.do_run = True
self.data = []
self.v = Visualizer()
self.x = None
self.y = None
self.alpha = 0.5
def __start_socket(self):
self.socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.socket.connect((self.host, self.port))
def __stop_socket(self):
self.socket.close()
def __test(self):
dataset = WifiData(self.config, test=True)
test_loader = DataLoader(dataset, batch_size=1)
for data, _ in test_loader:
data = data.to(self.device)
logits = self.model(data)
# print(data.shape, logits.shape)
logits = logits.detach().numpy()[0]
logits[0] = np.clip(logits[0], self.config.x_min,
self.config.x_max)
logits[1] = np.clip(logits[1], self.config.y_min,
self.config.y_max)
if not self.x:
self.x = logits[0]
self.y = logits[1]
self.x = self.x * (1 - self.alpha) + logits[0] * self.alpha
self.y = self.y * (1 - self.alpha) + logits[1] * self.alpha
self.v.update(self.x, self.y)
print(self.x, self.y)
# self.v.update(logits[0], logits[1])
# print(logits[0], logits[1])
def start(self):
self.__start_socket()
t = threading.currentThread()
while getattr(t, "do_run", True):
datas = []
for i in range(1):
outdata = self.socket.recv(8192)
# data = pickle.loads(data) #data loaded.
try:
outdata = ast.literal_eval(outdata.decode())
except:
print(len(outdata))
break
data = {}
for key, value in outdata.items():
outdata[key] = float(value) / 70
data['Feature'] = outdata
self.data.append(data)
# print('Recieve a dict with length %d from %s' %(len(outdata), self.host))
# Start testing
datas.append(data)
with open(self.path, 'wb') as fout:
pickle.dump(datas, fout)
self.__test()
self.__stop_socket()