Webcam capture with OpenCV and multiprocessing II

OpenCV with multiprocessing for a webcam capture using shared memory via Namespace:

import multiprocessing
import cv2


def cam_loop(namespace, event):
    cap = cv2.VideoCapture(0)

    while True:
        _ , img = cap.read()
        if img is not None:
            namespace.value = img
            event.set()

def show_loop(the_q, event):
    cv2.namedWindow('pepe')

    while True:
        event.wait()
        from_queue = namespace.value
        cv2.imshow('pepe', from_queue)
        k = cv2.waitKey(1)
        if k == ord('q') or k == 27:
            break

if __name__ == '__main__':

    logger = multiprocessing.log_to_stderr()
    logger.setLevel(multiprocessing.SUBDEBUG)

    mgr = multiprocessing.Manager()
    namespace = mgr.Namespace()

    event = multiprocessing.Event()

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

    show_process = multiprocessing.Process(target=show_loop,args=(namespace, event))
    show_process.start()

    cam_process.join()
    show_process.join()

Difficult to say what is the performance compared with  pipes or queues.

The cpu usage is high, 70+% if you sum up all processes, and I'm not even doing any image processing, nor gui.

I'm beginning to wonder if the multiprocessing via is going to be suitable for the core aspects of behave.

Next: bring Tkinter into this multiprocessing-opencv-webcam-capture scenario.