Good day,
I've searched for this but haven't come up with any responses. I wish to send a multi dimensional numpy array over a socket. Hence, I decided to convert it to a string:
However, it destroys the representation of the array:
>>> import numpy as np
>>> x = np.array([[0, 1], [2, 3]])
>>> xstring = x.tostring()
>>> print xstring
>>> print x
[[0 1]
[2 3]]
>>> print xstring
>>> nparr = np.fromstring(xstring, dtype=np.uint8)
>>> print nparr
[0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0]
Is there anyway I can get the conversion to string to somehow, save the dimension of it?
Try this example:-
import socket
import numpy as np
from cStringIO import StringIO
class numpysocket():
def __init__(self):
pass
@staticmethod
def startServer():
port=7555
server_socket=socket.socket()
server_socket.bind(('',port))
server_socket.listen(1)
print 'waiting for a connection...'
client_connection,client_address=server_socket.accept()
print 'connected to ',client_address[0]
ultimate_buffer=''
while True:
receiving_buffer = client_connection.recv(1024)
if not receiving_buffer: break
ultimate_buffer+= receiving_buffer
print '-',
final_image=np.load(StringIO(ultimate_buffer))['frame']
client_connection.close()
server_socket.close()
print '\nframe received'
return final_image
@staticmethod
def startClient(server_address,image):
if not isinstance(image,np.ndarray):
print 'not a valid numpy image'
return
client_socket=socket.socket()
port=7555
try:
client_socket.connect((server_address, port))
print 'Connected to %s on port %s' % (server_address, port)
except socket.error,e:
print 'Connection to %s on port %s failed: %s' % (server_address, port, e)
return
f = StringIO()
np.savez_compressed(f,frame=image)
f.seek(0)
out = f.read()
client_socket.sendall(out)
client_socket.shutdown(1)
client_socket.close()
print 'image sent'
pass
In this model client sends multidimensional ndarray to server.
There are two functions startServer() and startClient().
startServer takes no arguments but startClient needs server address as well as the ndarray as arguments.
First start Server and then start client.
Server starts reading from buffer only after receiving the shutdown message from client.
Indeed, .tostring only returns the raw data. This means you additionally need to send the shape and dtype of the array if these aren't known on the other side.
Maybe it's easier to serialize the array using Pickle:
import numpy as np
from cPickle import dumps, loads
x = np.array([[1, 2],[3, 4]], np.uint8)
print loads(dumps(x))
# [[1 2]
# [3 4]]
Though for very small arrays the size overhead could be significant:
print len(x.tostring()), len(dumps(x))
# 4 171
For more on using Pickle, see here.
This is a slightly improvised answer for ajsp answer using XML-RPC.
On the server-side when you convert the data, convert the numpy data to a string using the
'.tostring()' method. This encodes the numpy ndarray as bytes string. On the client-side when you receive the data decode it using '.fromstring()' method. I wrote two simple functions for this. Hope this is helpful.
- ndarray2str -- Converts numpy ndarray to bytes string.
- str2ndarray -- Converts binary str back to numpy ndarray.
def ndarray2str(a):
# Convert the numpy array to string
a = a.tostring()
return a
On the receiver side, the data is received as a 'xmlrpc.client.Binary' object. You need to access the data using '.data'.
def str2ndarray(a):
# Specify your data type, mine is numpy float64 type, so I am specifying it as np.float64
a = np.fromstring(a.data, dtype=np.float64)
a = np.reshape(a, new_shape)
return a
Note: Only problem with this approach is that XML-RPC is very slow while sending large numpy arrays. It took me around 4 secs to send and receive a (10, 500, 500, 3) size numpy array for me.
I am using python 3.7.4.
