我正在做这个套接字通信代码从server.py(在笔记本电脑上)发送输入到client.py(树莓派)，在这个通信中，我从2d Numpy数组一次发送一行到客户端，然后客户端使用Keras模型预测输出。通信不是问题，但问题是在套接字通信中发送数据必须以字节为单位，因此每次发送数据时我都将数组更改为字节，接收时我再次将字节返回到NumPy数组中。问题是当我试图改变模型的预测值时，它会改变值。
Server.py
import socket
import numpy as np
import pandas as pd
import sklearn
from sklearn.preprocessing import MinMaxScaler
import struct
def send_data(connection, data):
data_size = len(data)
data_size_as_4_bytes = struct.pack('>I', data_size)
connection.send(data_size_as_4_bytes)
connection.send(data)
def recv_data(connection, chunk_size=64):
data_size_as_4_bytes = connection.recv(4)
data_size = struct.unpack('>I', data_size_as_4_bytes)[0]
data = b""
size = 0
while size < data_size:
chunk = connection.recv(chunk_size)
print(chunk)
size += len(chunk)
data += chunk
return data
scaler_ti = MinMaxScaler()
test_inputs = []
test_inputs = np.array(test_inputs)
temp_in = pd.read_excel(r'K:BachelorThesisDataTestingDataMix_Data_inputs.xlsx')
test_inputs = temp_in.to_numpy()
scaler_ti.fit(test_inputs)
normalized_test_inputs = scaler_ti.transform(test_inputs)
HOST = ''
PORT = 62402
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
s.bind((HOST, PORT))
s.listen(5)
try:
while True:
print('Waiting for client')
connection, address = s.accept()
print(f"Connection from {address} has been established!")
for row in normalized_test_inputs:
print('send:', row)
data = row.tobytes()
send_data(connection, data)
data = recv_data(connection)
row = np.frombuffer(data)
print(row)
inverse = scaler_ti.inverse_transform(row.reshape(1,8))
print('recv:', inverse)
send_data(connection, 'end'.encode())
connection.close()
except KeyboardInterrupt:
print("Stopped by Ctrl+C")
finally:
s.close()
client.py
# author: Bartlomiej "furas" Burek (https://blog.furas.pl)
# date: 2021.07.23
#
# title: receiving back data from the client
# url: https://stackoverflow.com/questions/68499599/receiving-back-data-
from-the-client/68502806#68502806
import socket
import numpy as np
from random import randint
import os
import tensorflow as tf
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.models import load_model
import struct
def send_data(connection, data):
data_size = len(data)
data_size_as_4_bytes = struct.pack('>I', data_size)
connection.send(data_size_as_4_bytes)
connection.send(data)
def recv_data(connection, chunk_size=64):
data_size_as_4_bytes = connection.recv(4)
data_size = struct.unpack('>I', data_size_as_4_bytes)[0]
data = b""
size = 0
while size < data_size:
chunk = connection.recv(chunk_size)
size += len(chunk)
data += chunk
return data
def Predicting(input_data):
input_data = input_data.reshape(1,8)
output_data = modelANN.predict(input_data)
return output_data
modelANN = load_model(os.path.join("K:BachelorThesiscode
testingTireForces.LSTM","ANN_model.h5"))
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
host = socket.gethostname()
port = 62402
s.connect((host, port))
while True:
data = recv_data(s)
if data == b'end':
break
input_data = np.frombuffer(data)
print('recv:', input_data)
output_data = Predicting(input_data)
print('send:', output_data)
data = output_data.tobytes()
print(data)
send_data(s, data)
s.close()
server.py
Waiting for client
Connection from ('192.168.137.1', 52967) has been established!
send: [3.24085967e-04 3.20361343e-04 3.52129031e-04 3.77033700e-04
6.79706856e-01 4.95983138e-01 4.52484158e-04 4.92325891e-01]
b"x0ex97/?xf4xe68?|x18)?Bx1c}>xc5xd7'?xf2xd7n?=xe5x1b?)x1fxcb>"
[3.79976874e-04 1.08444638e-07 5.11999896e-05 3.23316134e-06]
Traceback (most recent call last):
File "K:BachelorThesiscode testingserver.py", line 74, in <module>
inverse = scaler_ti.inverse_transform(row.reshape(1,8))
ValueError: cannot reshape array of size 4 into shape (1,8)
client.py
的输出recv: [3.24085967e-04 3.20361343e-04 3.52129031e-04 3.77033700e-04
6.79706856e-01 4.95983138e-01 4.52484158e-04 4.92325891e-01]
send: [[0.68589866 0.72227407 0.66052985 0.24717811 0.65563613 0.54235756
0.60896665 0.3967221 ]]
b"x0ex97/?xf4xe68?|x18)?Bx1c}>xc5xd7'?xf2xd7n?=xe5x1b?)x1fxcb>"
Traceback (most recent call last):
File "K:BachelorThesiscode testingclient.py", line 50, in <module>
data = recv_data(s)
File "K:BachelorThesiscode testingclient.py", line 20, in recv_data
data_size = struct.unpack('>I', data_size_as_4_bytes)[0]
struct.error: unpack requires a buffer of 4 bytes
tobytes只是数组数据缓冲区的字节拷贝。它不传递任何类型或形状信息:
In [31]: x = np.arange(12).reshape((3,4))
In [32]: astr = x.tobytes()
In [33]: astr
Out[33]: b'x00x00x00x00x00x00x00x00x01x00x00x00x00x00x00x00x02x00x0...x00x00x00'
根据文档，默认加载为float64:
In [34]: y = np.frombuffer(astr)
In [35]: y
Out[35]:
array([0.0e+000, 4.9e-324, 9.9e-324, 1.5e-323, 2.0e-323, 2.5e-323,
3.0e-323, 3.5e-323, 4.0e-323, 4.4e-323, 4.9e-323, 5.4e-323])
纠正dtype
In [36]: y = np.frombuffer(astr, dtype=int)
In [37]: y
Out[37]: array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])
添加形状:
In [38]: y.reshape((3,4))
Out[38]:
array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])