Hi Mujtaba That sounds interresting
Its best you discuss the exact qualification task with whoever would be the Mentor of this. But in absence of better ideas I suggest you do something that is closer to the area your project would be than "Improving Fate (self tests) coverage" For example you could write/add an avfilter that connects to some external AI filters. This would also allow us to later in the summer evaluate the performce of your local filters within FFmpeg. also, to send mails successfully to ffmpeg-devel, you must subscribe otherwise the mails will be held as potential spam. (which will delay them alot) PS: also make sure you submit a project proposal before googles deadline, in case you have not yet. thx On Mon, Mar 30, 2026 at 11:33:52PM +0500, Cloakedmenace wrote: > Hi FFmpeg Development Community, > > My name is Mujtaba Shah, and I am a final-year Computer Science student. I > am writing to propose a custom GSoC 2026 project focused on expanding > FFmpeg’s machine learning capabilities, specifically by introducing an > AI-powered video evaluation filter within libavfilter. > > *The Concept:* While FFmpeg has made great strides with its DNN module and > the modernized LibTorch backend, there is a growing demand for local, > privacy-respecting video analysis. My proposal is to build a filter that > integrates offline, local vision models directly into the FFmpeg pipeline. > This would allow users to perform automated video evaluations—such as frame > tagging, scene detection, or metadata extraction—entirely from the command > line without relying on external API calls. > > *Proposed Scope of Work:* > > - > > Extend the existing DNN backend infrastructure to support a broader > range of localized AI vision models for direct video evaluation. > - > > Implement a new filter within libavfilter designed specifically for > automated visual analysis and tagging of video streams. > - > > Develop a robust FATE test suite to ensure the filter’s stability and > accuracy across different environments. > - > > Ensure seamless, zero-copy interactions where possible to maintain high > throughput and low CPU-GPU latency. > > *Why I Am a Good Fit:* I have a strong background in AI, machine learning, > and systems architecture. In my recent work, I have built specialized > pipelines for the automated AI evaluation of video submissions and have > hands-on experience configuring and deploying completely offline, > uncensored AI models. This practical experience aligns perfectly with the > goal of bringing robust, localized machine learning analysis directly into > FFmpeg’s media processing workflows. > > *Next Steps & Qualification:* I understand that proposing a custom project > requires finding a dedicated mentor. I would love to hear your thoughts on > this idea's feasibility and whether anyone in the community would be > interested in mentoring this effort. > > In the meantime, to demonstrate my familiarity with the codebase and build > systems, I am currently looking into the "Improving Fate (self tests) > coverage" tasks as my qualification requirement. > > Thank you for your time and for maintaining such an incredible project. I > look forward to your feedback! > > Best regards, > > Mujtaba Shah -- Michael GnuPG fingerprint: 9FF2128B147EF6730BADF133611EC787040B0FAB What is kyc? Its a tool that makes you give out your real ID, while criminals give out a forged ID card.
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