threaded-videocapture 1.0.0

OpenCV VideoCapture running in a background thread

Threaded-VideoCapture

A direct drop-in replacement for OpenCV's VideoCapture that runs in a background thread, allowing the main thread to do useful work instead of waiting on frames.

This library is useful if your code spend a lot of time waiting for new frames, or if you are processing a stream in realtime and cannot process frames fast enough to keep up with the stream.

Threaded-VideoCapture requires opencv-python 4.0.0.21 or greater. It has been tested on Python 3.6, 3.7, 3.8. 3.9, 3.10, and 3.11.

It is a young library. Therefore bugs may exist, and useful features may be missing. Bug reports, feature requests, and pull requests are therefore highly appreciated!

How to install

PyPi package is currently being worked on and should be ready before December 2022. For now, you can download this repository directly.

Simple example

Threaded-VideoCapture can be used exactly like the normal VideoCapture:

import cv2
from threaded_videocapture import ThreadedVideoCapture

with ThreadedVideoCapture(0) as tvc:  # Open webcam stream
    while True:
        ret, frame = tvc.read()
        if ret:  # ret is True if a frame was obtained with tvc.read()
            cv2.imshow('frame', frame) 
        if ret is None:  # ret is None if tvc has stopped.
            print("End of stream.")
            break
        if cv2.waitKey(1) == ord('q'):
            break

Documentation

ThreadedVideoCapture creates a background thread with a VideoCapture instance in it. This instance will continuously read frames and place them on a FIFO queue. When you call ThreadedVideoCapture.read(), the oldest frame is returned from the queue. If there are no frames in the queue, a (False, None) tuple is returned.

An instantiated ThreadedVideoCapture will eventually stop yielding frames. This is normal, and occurs for example when:

• There are no more frames in the video file
• A stream times out
• An exception occurs

When ThreadedVideoCapture stops, it will place a (None, None) tuple on the queue. This signifies that ThreadedVideoCapture.read() will never yield new frames until a new source has been opened with ThreadedVideoCapture.open(). This can also be checked with ThreadedVideoCapture.is_alive().

Instantiation parameters

ThreadedVideoCapture takes additional parameters compared to VideoCapture during instantiation: frame_queue_size, timeout, poll_rate, and logger. They are explained here.

Frame queue size

Frames read by the VideoCapture instance in the background thread will be placed on a queue, as explained above. When the queue becomes full, the oldest item is deleted to make room for the new frame. The length of the queue can be specified when instantiating ThreadedVideoCapture to suit your needs. Be default, the queue length is 1, meaning that only the most recent frame is available.

Timeout

If ThreadedVideoCapture does not receive a new frame within a specified time, it will time out and quit. This is useful for example when you are capturing a stream and you do not know when it will end. You can set the timeout value both when instantiating, and at any other time. By default, the timeout is set to 1 second. The following example shows how to start a ThreadedVideoCapture that will wait indefinitely for a single frame, then change its timeout and quit if no frames are received within the timeout value.

with ThreadedVideoCapture(0, timeout=0) as tvc:  # Open webcam stream with timeout disabled.
    # Poll for a single frame for eternity due to no timeout
    while True:
        ret, frame = cap.read() 
        if ret:
            break
    
    tvc.timeout = 2.5 # Set timeout to 2.5 seconds
    # Poll for frames for 2.5 seconds before ThreadedVideoCapture times out
    while True:
        ret, frame = tvc.read() 
        if ret is None:  # ret is only None if tvc has stopped.
            print("ThreadedVideoCapture has timed out.")
            break
    

Polling rate

You can limit how often the VideoCapture instance calls grab() by specifying the polling rate at instantiation, or at any other time. By default, it is not limited.

Logger

The Threaded-VideoCapture library uses Pythons excellent logging library to log events. By default ThreadedVideoCapture uses its own logger named 'TVC', but you can provide it with a custom logger object at instantiation. The logger is found at ThreadedVideoCapture.logger.

Reusing a ThreadedVideoCapture instance

You can open a new video source without having to close your original ThreadedVideoCapture instance and creating a new one. Simply call ThreadedVideoCapture.open() with your new source parameters. This will release the VideoCapture instance for your old source, join the background thread, and create a new VideoCapture in its own thread for the new video source. Example:

# Example showing how to switch to a different webcam after 1 second with the same ThreadedVideoCapture instance.

from time import time
with ThreadedVideoCapture(0) as tvc:  # Open webcam 0 stream
    tick = time()
    while True:
        ret, frame = tvc.read()
        if ret:  # ret is True if a frame was obtained with tvc.read()
            cv2.imshow('frame', frame) 
        if cv2.waitKey(1) == ord('q'):
            break
        # After one second of opening the stream from webcam 0, we switch seamlessly to webcam 1.
        if time() - tick > 1:
            tvc.open(1)

Statistics

The current frames per second (FPS) and actual polling rate can be obtained with ThreadedVideoCapture.fps and ThreadedVideoCapture.actual_poll_rate. These values are updated once per second.