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I'm kind of late but I've created powerful & threaded VidGear Video Processing python library that now provides real-time Video Stabilization with minimalistic latency and at the expense of little to no additional computational power requirement with Stabilizer Class. The basic idea behind it is to tracks and save the salient feature array for the given number of frames and then uses these anchor point to cancel out all perturbations relative to it for the incoming frames in the queue. Here's a basic usage example for your convenience:

# import libraries
from vidgear.gears import VideoGear
from vidgear.gears import WriteGear
import cv2

stream = VideoGear(source=0, stabilize = True).start() # To open any valid video stream(for e.g device at 0 index)

# infinite loop
while True:

    frame = stream.read()
    # read stabilized frames

    # check if frame is None
    if frame is None:
        #if True break the infinite loop
        break

    # do something with stabilized frame here

    cv2.imshow("Stabilized Frame", frame)
    # Show output window

    key = cv2.waitKey(1) & 0xFF
    # check for 'q' key-press
    if key == ord("q"):
        #if 'q' key-pressed break out
        break

cv2.destroyAllWindows()
# close output window

stream.stop()
# safely close video stream

More advanced usage can be found here: https://github.com/abhiTronix/vidgear/wiki/Real-time-Video-Stabilization#real-time-video-stabilization-with-vidgear