> On May 10, 2023, at 10:25, WenzheWang <wong...@foxmail.com> wrote:
>
> Dear Madam or Sir,
>
>
> Hope this email finds you well.
>
>
> I am writing this email since i recently found FFmepg remove DNN native
> backend, and i will be really grateful if you let me know if there is any
> new plan on libavfilter/dnn.
>
>
> I would like to explain to you again about the addition of dnn paddle backend.
>
> At present, ffmpeg only supports openvino and tensorflow backend. Among the
> current deep learning frameworks, TensorFlow is the most active in
> development. TensorFlow has 174k stars and pytorch has 66.5k. openvino is
> 4.2k, and the models that openvino can implement are relatively few. But in
> terms of attention on GitHub, there's no doubt that TensorFlow and pytorch
> are more promising. Currently, the paddle framework has reached 20.2k stars
> on github, which is much more widely used and active than frameworks such as
> mxnet and caffe.
Stars don't matter much here.
Just for reference, there is a thread before:
https://patchwork.ffmpeg.org/project/ffmpeg/patch/20220523092918.9548-2-ting...@intel.com/
>
> Tensoflow has a very rich ecosystem. The TensorFlow models library updates
> very quickly and has existing examples of deep learning applications for
> image classification, object detection, image generation text, and
> generation of adversus-network models. The dnn libavfilter module is
> undoubtedly very necessary for tensorflow backend to support. But the
> complexity of the TensorFlow API and the complexity of the training are
> almost prohibitive, making it a love-hate framework.
>
> PyTorch framework tends to be applied to academic fast implementation, and
> its industrial application performance is not good. For example, Pytorch
> framework makes a model to run on a server, Android phone or embedded
> system, and its performance is poor compared with other deep learning
> frameworks.
>
>
> PaddlePadddle is an open source framework of Baidu, which is also used by
> many people in China. It is very consistent with the usage habits of
> developers, but the practicability of the API still needs to be further
> strengthened. However, Paddle is the only deep learning framework I have
> ever used, which does not configure any third-party libraries and can be
> used directly by cloning make. Besides, Paddle occupies a small amount of
> memory and is fast. It also serves a considerable number of projects inside
> Baidu, which is very strong in industrial application. And PaddlePaddle
> supports multiple machine and multiple card training.
>
>
> Users' choice of different deep learning frameworks is a personal choice,
> and the reason why most of us chose paddle is because of its better support
> for embedded development and different hardware platforms and because the
> community is very active and has proposed industrial improvements and
> implementations for some advanced models. Especially for the GPU, it
> supports cuda and opencl, which means we can optimize the model no matter
> what kind of graphics card is used. In my opinion, more backend support can
> better improve dnn libavfilter modules.
>
> If there are any new changes in dnn libavfilter module, I will be very
> willing to adjust our implementation with the new planning and provide
> continuous maintenance.
>
>
>
>
> Best Regards,
> Wenzhe Wang
>
>
>
>
>
>
> WenzheWang
> wong...@foxmail.com
>
>
>
>
>
>
>
> ------------------ Original ------------------
> From: "WenzheWang"
> <wong...@foxmail.com>;
> Date: Tue, Apr 11, 2023 11:03 PM
> To: "ffmpeg-devel"<ffmpeg-devel@ffmpeg.org>;
>
> Subject: Re: [FFmpeg-devel] [PATCH v1] libavfi/dnn: add Paddle Inference
> as one of DNN backend
>
>
>
>
> Could you please briefly introduce the reason why not adding any dnn
> backend?
>
>
>
>
> Do you have any plan for the maintenance and development of the dnn backend
> in the future? From my understanding, the current backend of dnn has
> tensoflow, openvino and native, but this cannot meet the needs of users.
>
>
>
>
> Thus, I believe adding other dnn backends will be great for user experience,
> user growth, and industrial applications. In particular, various dnn backend
> can be adapted to different application environments, and there are some
> emerging inference engines that are faster and stronger, such as Pytorch and
> Paddle. In addition, from the practical point of view, it is not difficult
> for a deep learning practitioner to learn and use this framework, but how to
> choose a framework and apply it in practice, people pay more attention to the
> effect (recall and precision), and easy deployment, that is, high reasoning
> performance efficiency. The main reason why Paddle is relatively mainstream
> and why I want to add paddle backend is that it has a very high efficiency
> and performance. There are several projects maintained by Paddle, such as
> paddleDetection, paddleSeg, paddleGAN, paddleOCR and paddleCls have a lot of
> good pre-training models that migrate well to their own data and has
> excellent perfo
rm
> ance. Secondly, in terms of reasoning efficiency, Paddle supports many
> platforms and chips. Models trained using Paddle framework can be directly
> deployed, and custom device interfaces are open for independent development
> based on one's own hardware.
>
> FFmpeg itself already has very extensive support for codec. If FFmpeg could
> support the deployment of more reasoning model backend, it would have a wider
> application.
>
>
>
>
> In general, I hope that ffmpeg could support the backend of paddle or more.
> In any case that my code is not mature or proper, I would be grateful if
> professionals like you could offer me suggestions and comments. I will be
> absolutely honored if I could contribute to this project :)
>
>
>
>
> Best,
>
> Wenzhe Wang
>
>
>
>
> WenzheWang
> wong...@foxmail.com
>
>
>
>
>
>
>
> ------------------ Original ------------------
> From: "FFmpeg development discussions and patches" <j...@videolan.org>;
> Date: Sun, Apr 9, 2023 05:31 AM
> To: "ffmpeg-devel"<ffmpeg-devel@ffmpeg.org>;
>
> Subject: Re: [FFmpeg-devel] [PATCH v1] libavfi/dnn: add Paddle Inference
> as one of DNN backend
>
>
> On Thu, 6 Apr 2023, at 12:36, wong...@foxmail.com wrote:
> > PaddlePaddle (PArallel Distributed Deep LEarning) is a simple,
> > efficient and extensible deep learning framework that accelerates the
>
> Please don't add another DNN backend.
>
> --
> Jean-Baptiste Kempf - President
> +33 672 704 734
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