How to process video files with python OpenCV faster than file frame rate?
I can reproduce the behavior you describe (i.e. cv::VideoCapture >> image
locked to the frame rate of the recorded video) if opencv is compiled without ffmpeg support. If I compile opencv with ffmpeg support, I can read images from file as fast as my computer will allow. I think that in the absence of ffmpeg, opencv uses gstreamer and essentially treats the video file like its playing back a movie.
If you are using Linux, this link shows which packages you must install to get ffmpeg support for opencv.
Related videos on Youtube
Comments
-
Juha Syrjälä over 1 year
I have video file that I am trying to process one frame at a time,. I tried use VideoCapture class to do reading with following type of code. The problem is that if video file is recorded at 25 frames / second, the reading happens at same pace. How to get frames as fast as my computer can decode them?
I plan to process the video stream and then store it to a file.
import cv2 import sys import time cap = cv2.VideoCapture(sys.argv[1]) start = time.time() counter = 0 while True: counter += 1; image = cap.read()[1] if counter %25 == 0: print "time", time.time() - start
Output: It prints a timestamp once every 25 frames. Notice how timestamps change almost exactly by 1 second on every line => program processes about 25 frames per second. This with video file that is 25 frames/second.
time 1.25219297409 time 2.25236606598 time 3.25211691856 time 4.25237703323 time 5.25236296654 time 6.25234603882 time 7.252161026 time 8.25258207321 time 9.25195503235 time 10.2523479462
Probably VideoCapture is the wrong API for this kind of work, but what to use instead?
Using Linux, Fedora 20, opencv-python 2.4.7 and python 2.7.5.
-
Andrzej Pronobis almost 9 yearsI can confirm that I can indeed read from VideoCapture faster than the framerate, but I'm on OpenCV 3.0 compiled with ffmpeg.
-
Plankalkül almost 8 yearsThat seems to be the solution. Thanks