Capturing a video stream from a camera in python can be done with openCV. However, when doing this operation on the main thread, performance won’t be great, especially when capturing in HD quality. By using the VideoCaptureThreading class, the video capture operation runs in a separate (green) thread. The performance increases dramatically as shown below (on a MacBook Pro) :

For 640×480:

[i] Frames per second: 28.71, with_threading=False
[i] Frames per second: 81.67, with_threading=True

For 1280×720

[i] Frames per second: 15.02, with_threading=False
[i] Frames per second: 52.04, with_threading=True

The VideoCaptureThreading class contains:

• an __init__ function that opens the video capture stream, sets the frame dimensions and creates a lock object for thread save assigning and copying of the frames.
• a start function to create and start the thread
• an update function that will be called in a separate thread.
• a read function that we will call from our code to retrieve a new frame.
• a stop function to stop (join) the thread
• an __exit__ function to clean up some resources.

The beautiful part of this class is that it enables you to update existing code with minimal change. You only have to add
from gfd.py.video.capture import VideoCaptureThreading and change the line containing

cap = cv2.VideoCapture()

to

cap = VideoCaptureThreading()

and add

cap.start()

and

cap.stop()

at the beginning and end of the capture read() loop. That’s it, very easy. An example can be found in the test folder of this project.

In the root folder of this repository, run the following commands:

$ export PYTHONPATH=`pwd`/main
$ python test/videocapturethreading.py