How avoid libv4l2 resource busy on parallel exicution of python-opencv code?

Question

I trying to stream a webcam parallel process method. One of the function shows an error libv4l2 resource busy. Tried with using a narrow delay between the functions it's works fine. And when i use two camera it's also works. I think the problem with the settings of the libv4l2 or something. How solve this issue ?

import threading
from threading import Thread
import cv2
import numpy as np

def func1():
    video = cv2.VideoCapture(0)
    success, image = video.read()
    print success

def func2():
    video = cv2.VideoCapture(0)
    success, image = video.read()
    print success

if __name__ == '__main__':
    Thread(target = func1).start()
    Thread(target = func2).start()

And it's output like this.

VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
libv4l2: error setting pixformat: Device or resource busy
HIGHGUI ERROR: libv4l unable to ioctl S_FMT
libv4l2: error setting pixformat: Device or resource busy
libv4l1: error setting pixformat: Device or resource busy
HIGHGUI ERROR: libv4l unable to ioctl VIDIOCSPICT

False
True

Answer 1

Firstly I would highly recommend to check if your device i.e. the web-cam does provide the parallel input/ouput control at all.

Apparently it doesn't because you get the input/ouput control command failures

HIGHGUI ERROR: libv4l unable to ioctl S_FMT
HIGHGUI ERROR: libv4l unable to ioctl VIDIOCSPICT

You have to implement another abstraction layer which will do the splitting/duplication of the video stream for you. But not on device level as you are doing it now.

Similar problem has been discussed and resolved here