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Ping! Any update on this?

I found that the pretrained model work better with the flow images which are extracted after resizing the rgb frames.
And I used OpenCV3.3 (or 4.0 may work) instead of 3.4 since I found there some difference for the cv::cuda::OpticalFlowDual_TVL1.
I have got compatible accuracy for the fusion results while the flow results is still slightly worse.

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Ping! Any update on this?

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Thank you very much for the feedback. This is helpful. I'll look into that.

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Has anyone tried calculating optical flow using python opencv? I can't seem to get good results with that preprocessing, but might also be my lack of understing about parameters to use. I'm using opencv 4.1.0:
optical_flow = cv2.optflow.createOptFlow_DualTVL1()
flow_frame = optical_flow.calc(prev, curr, None)
flow_frame = np.clip(flow_frame, -20, 20)
flow_frame = flow_frame / 20.0

Thanks for any comments!

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Actually, the code I used above works fine and produces good results on the example vid. But would still be nice to get pointers if this is missing something from the original preprocessing. Thanks

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Actually, the code I used above works fine and produces good results on the example vid. But would still be nice to get pointers if this is missing something from the original preprocessing. Thanks

I think your code is correct. But the python interface is too slow. Do you have any idea how to speedup? Actually, I used the C++ interface of OpenCV for flow extraction.

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Yes, it's slow, on my desktop flow calc runs at about 4 fps. I just wanted to reproduce for now. Don't know if it's possible to bring it up to 25 fps with Python - I'd guess that it isn't. Is the speed fine with C++?

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Hello, does anyone know how the frame sampling was done? Is it just nearest sampling?

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Yes, it's slow, on my desktop flow calc runs at about 4 fps. I just wanted to reproduce for now. Don't know if it's possible to bring it up to 25 fps with Python - I'd guess that it isn't. Is the speed fine with C++?

it is fine with C++. it runs at about 40~50fps on 2080ti with the opencv cuda interface.

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Hello, does anyone know how the frame sampling was done? Is it just nearest sampling?

Hi do you have any ideas? I am also wondering how the video resampling is done...

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Just to reply to the resampling question: This is what I did to my videos which were originally 1280x720 and 30fps (using ffmpeg on ubuntu command line):

ffmpeg -y -r 30 -i input.avi -r 25 -filter:v scale=456x256 -sws_flags bilinear output.avi

Output of this should be a bilinearly interpolated video with 25fps and smaller side of video at 256px, as described in the paper and/or README file.

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Hi Joao,

the preprocessing code has been released as part of mediapipe, see here:
https://github.com/google/mediapipe/tree/master/mediapipe/examples/desktop/media_sequence

If I follow the steps and use kinetics_dataset.py on v_CricketShot_g04_c01,avi, I do not get rgb and flow files. Please do elaborate on how to preprocess the avi file to generate the rgb and flow data.

Thanks for your help

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Thanks Joao,
Just to clarify, I am following the steps outlined under "custom videos in the Kinetics format". I change VIDEO_PATH to point to the avi, build the media_sequence_demo and run kinetics_dataset.py. I do see an output file kinetics_700_custom_25fps_rgb_flow-00000-of-00001. I am not sure about the next step.

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I was hoping that it will generate the rgb & flow files in a format that I can then use as an input to evaluate_sample. Not sure if that is the intent of the release of the preprocessing code.

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