[FFmpeg-devel] [PATCH 2/2] libavfi/dnn: add LibTorch as one of DNN backend

[Fu, Ting]

> -----Original Message-----
> From: ffmpeg-devel <ffmpeg-devel-bounces at ffmpeg.org> On Behalf Of
> Jean-Baptiste Kempf
> Sent: Tuesday, May 24, 2022 10:52 PM
> To: ffmpeg-devel <ffmpeg-devel at ffmpeg.org>
> Subject: Re: [FFmpeg-devel] [PATCH 2/2] libavfi/dnn: add LibTorch as one of
> DNN backend
> 
> Hello,
> 
> On Tue, 24 May 2022, at 16:03, Fu, Ting wrote:
> > I am trying to add this backend since we got some users who have
> > interest in doing PyTorch model(BasicVSR model) inference with FFmpeg.
> 
> I think you are missing my point here.
> We already have 3 backends (TF, Native, OpenVino) in FFmpeg.
> Those are not to support different hardware, but different tastes for users,

Hi Jean-Baptiste,

Yes, you are right, we already got three backends with FFmpeg DNN. But for now, the native backend is barely workable, due to its layers and operations weak support.
And we do support different hardware. Like, the OpenVINO backend supports inference with Intel GPU. For now, the TensorFlow and OpenVINO backend support some models, which include Super Resolution model, object detect model, object classify model. I think it's not only a teste difference for users, but an option for them to choose for their work implementation. AFAIK, there are some individuals and organizations who are using FFmpeg DNN.

> who prefer one API to another one.
> Where does it end? How many of those backends will we get? 10?
> 
> What's the value to do that development inside ffmpeg?
> 

I think you are concerning why we need such backend. Because the users want to infer the BasicVSR and other VSR(video super solution) model. Those models are most implemented with PyTorch. And it can cause several issues if we convert such model to the other AI model file. Besides, the video codec is an advantage of FFmpeg framework, which can support various of hardware acceleration. We would like to utilize this framework to enhance the performance of AI inference and improve the user experience.
What I want to emphasis is that the LibTorch backend is not for adding patches but an actual requirement.

Thank you.
Ting FU

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