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Performance Improvement for ThresholdDetector #64
Description
Hi,
Frame averaging currently is done via
numpy.sum(frame[:,:,:]) / num_pixel_valuesI've experimented a bit and found that a substantial improvement can be made by using OpenCV built-in methods for this purpose. For example:
cv2.mean(cv2.mean(frame))[0] / 3
The resulting compute_frame_average() method runs ~10% faster on the test video.
Example:
# Test with the proposed change
$ scenedetect -i goldeneye.mp4 -s output.csv -l
[PySceneDetect] Detecting scenes (threshold mode)...
[PySceneDetect] Parsing video goldeneye.mp4...
[PySceneDetect] Video Resolution / Framerate: 1280 x 544 / 23.976 FPS
Verify that the above parameters are correct (especially framerate, use --force-fps to correct if required).
[PySceneDetect] Processing complete, found 0 scenes in video.
[PySceneDetect] Processed 1980 / 1980 frames read in 7.8 secs (avg 254.5 FPS).
# Test with current method
$ scenedetect -i goldeneye.mp4 -s output.csv -l
[PySceneDetect] Detecting scenes (threshold mode)...
[PySceneDetect] Parsing video goldeneye.mp4...
[PySceneDetect] Video Resolution / Framerate: 1280 x 544 / 23.976 FPS
Verify that the above parameters are correct (especially framerate, use --force-fps to correct if required).
[PySceneDetect] Processing complete, found 0 scenes in video.
[PySceneDetect] Processed 1980 / 1980 frames read in 8.6 secs (avg 229.4 FPS).
Unit-Testing for performance of the proposed vs existing solution
print(frame.shape)
print("Proposed Solution results:")
%timeit compute_frame_average_PROPOSED(frame)
print("Existing Solution results:")
%timeit compute_frame_average_EXISTING(frame)
results in:
(1080, 1980, 3)
Proposed Solution results:
100 loops, best of 3: 4.92 ms per loop
Existing Solution results:
100 loops, best of 3: 6.32 ms per loop
Activity
[-]Performance Improvement proposal[/-][+]Performance Improvement for ThresholdDetector[/+]Breakthrough commentedon Jul 29, 2018
Excellent, thank you for this submission! These improvements will be added to the next official PySceneDetect release (v0.5), and have also been merged into the current master branch.
I will leave this issue open until I have merged your changes into my development branch (v0.5-dev).
Breakthrough commentedon Aug 1, 2018
After review, I will defer this enhancement to the backlog for a release in v0.5.1/v0.6 pending further testing, to expedite the release of v0.5.
Breakthrough commentedon Feb 17, 2022
I just did a quick test of this again, and seem to get very close results.
Would you be able to re-test this with a newer version of OpenCV and let me know if you still get the same results?
Breakthrough commentedon Feb 17, 2022
Also just to clarify, I was calling
frame.mean()instead of usingcv2.mean()as in your example.Breakthrough commentedon Jul 17, 2023
I wasn't able to see any notable performance improvement, so I'll close this issue out. However, feel free to submit a pull request should you find any other optimizations. Thank you!