Constant camera grabbing with OpenCV & Python multiprocessing

I’m after constantly reading images from an OpenCV camera in Python and reading from the main program the latest image. This is needed because of problematic HW.

After messing around with threads and getting a very low efficiency (duh!), I’d like to switch to multiprocessing.

Here’s the threading version:

class WebcamStream:
    # initialization method
    def __init__(self, stream_id=0):
        self.stream_id = stream_id  # default is 0 for main camera

        # opening video capture stream
        self.camera = cv2.VideoCapture(self.stream_id)
        self.camera.set(cv2.CAP_PROP_FRAME_WIDTH, 3840)
        self.camera.set(cv2.CAP_PROP_FRAME_HEIGHT, 2880)

        if self.camera.isOpened() is False:
            print("[Exiting]: Error accessing webcam stream.")
            exit(0)

        # reading a single frame from camera stream for initializing
        _, self.frame = self.camera.read()

        # self.stopped is initialized to False
        self.stopped = True

        # thread instantiation
        self.t = Thread(target=self.update, args=())
        self.t.daemon = True  # daemon threads run in background

    # method to start thread
    def start(self):
        self.stopped = False
        self.t.start()

    # method passed to thread to read next available frame
    def update(self):
        while True:
            if self.stopped is True:
                break
            _, self.frame = self.camera.read()
        self.camera.release()

    # method to return latest read frame
    def read(self):
        return self.frame

    # method to stop reading frames
    def stop(self):
        self.stopped = True

And –

if __name__ == "__main__":
    main_camera_stream = WebcamStream(stream_id=0)
    main_camera_stream.start()
    frame = main_camera_stream.read()

Can someone please help me translate this to multiprocess land ?

Thanks!

Answer

I’ve written several solutions to similar problems, but it’s been a little while so here we go:

I would use shared_memory as a buffer to read frames into, which can then be read by another process. My first inclination is to initialize the camera and read frames in the child process, because that seems like it would be a “set it and forget it” kind of thing.

import numpy as np
import cv2
from multiprocessing import Process, Queue
from multiprocessing.shared_memory import SharedMemory

def produce_frames(q):
    #get the first frame to calculate size of buffer
    cap = cv2.VideoCapture(0)
    success, frame = cap.read()
    shm = SharedMemory(create=True, size=frame.nbytes)
    framebuffer = np.ndarray(frame.shape, frame.dtype, buffer=shm.buf) #could also maybe use array.array instead of numpy, but I'm familiar with numpy
    framebuffer[:] = frame #in case you need to send the first frame to the main process
    q.put(shm) #send the buffer back to main
    q.put(frame.shape) #send the array details
    q.put(frame.dtype)
    try:
        while True:
            cap.read(framebuffer)
    except KeyboardInterrupt:
        pass
    finally:
        shm.close() #call this in all processes where the shm exists
        shm.unlink() #call from only one process

def consume_frames(q):
    shm = q.get() #get the shared buffer
    shape = q.get()
    dtype = q.get()
    framebuffer = np.ndarray(shape, dtype, buffer=shm.buf) #reconstruct the array
    try:
        while True:
            cv2.imshow("window title", framebuffer)
            cv2.waitKey(100)
    except KeyboardInterrupt:
        pass
    finally:
        shm.close()

if __name__ == "__main__":
    q = Queue()
    producer = Process(target=produce_frames, args=(q,))
    producer.start()
    consume_frames(q)