opencv and multiprocessing

Question

I'm looking to use the multiprocessing module for python to create one process that continually polls a webcam via opencv's python interface, sending any resulting images to a queue from which other processes can access them. However, I'm encountering a hang (python 2.7 on Ubuntu 12.04) whenever I try to do anything with the images retrieved by other processes from the queue. Here's a minimal example:

import multiprocessing
import cv

queue_from_cam = multiprocessing.Queue()

def cam_loop(queue_from_cam):
    print 'initializing cam'
    cam = cv.CaptureFromCAM(-1)
    print 'querying frame'
    img = cv.QueryFrame(cam)
    print 'queueing image'
    queue_from_cam.put(img)
    print 'cam_loop done'


cam_process = multiprocessing.Process(target=cam_loop,args=(queue_from_cam,))
cam_process.start()

while queue_from_cam.empty():
    pass

print 'getting image'
from_queue = queue_from_cam.get()
print 'saving image'
cv.SaveImage('temp.png',from_queue)
print 'image saved'

This code should run up to the print out of "saving image" but then hang. Any ideas how I can go about fixing this?

Answer 1

The simplest approach is to use the newer cv2 module that's based on NumPy arrays. That way you don't have to mess with manual pickling. Here's the fix (I just changed 4 lines of code):

import multiprocessing
import cv2

queue_from_cam = multiprocessing.Queue()

def cam_loop(queue_from_cam):
    print 'initializing cam'
    cap = cv2.VideoCapture(0)
    print 'querying frame'
    hello, img = cap.read()
    print 'queueing image'
    queue_from_cam.put(img)
    print 'cam_loop done'

cam_process = multiprocessing.Process(target=cam_loop,args=(queue_from_cam,))
cam_process.start()

while queue_from_cam.empty():
    pass

print 'getting image'
from_queue = queue_from_cam.get()
print 'saving image'
cv2.imwrite('temp.png', from_queue)
print 'image saved'

Answer 2

It appears that the solution was to convert the opencv iplimage object to string, then pickle it before adding it to the queue:

import multiprocessing
import cv
import Image
import pickle
import time

queue_from_cam = multiprocessing.Queue()

def cam_loop(queue_from_cam):
    print 'initializing cam'
    cam = cv.CaptureFromCAM(-1)
    print 'querying frame'
    img = cv.QueryFrame(cam)
    print 'converting image'
    pimg = img.tostring()
    print 'pickling image'
    pimg2 = pickle.dumps(pimg,-1)
    print 'queueing image'
    queue_from_cam.put([pimg2,cv.GetSize(img)])
    print 'cam_loop done'


cam_process = multiprocessing.Process(target=cam_loop,args=(queue_from_cam,))
cam_process.start()

while queue_from_cam.empty():
    pass

print 'getting pickled image'
from_queue = queue_from_cam.get()
print 'unpickling image'
pimg = pickle.loads(from_queue[0])
print 'unconverting image'
cv_im = cv.CreateImageHeader(from_queue[1], cv.IPL_DEPTH_8U, 3)
cv.SetData(cv_im, pimg)
print 'saving image'
cv.SaveImage('temp.png',cv_im)
print 'image saved'