Summary
SVT-AV1-PSY, a community fork of the SVT-AV1 video encoder, was created to enhance perceptual quality and ease of use for AV1 encoding. I co-created and currently maintain the project. It gained significant traction through our perceptual fidelity enhancements for videos and still images, but due to life circumstances, myself and another main contributor are stepping back from our involvement. our new goal is merging as many of our features as possible into SVT-AV1.
Why?
If you aren't familiar with codecs or AV1, I'm not sure why you're on my site. Nevertheless, here's some background:
- AV1 is a modern video codec, meant to make videos smaller and better looking
- Unlike H.264 and H.265, AV1 is royalty-free, meaning you don't have to pay to use it
- There are three very popular AV1 encoders that can be used to produce AV1 video: libaom, rav1e, and SVT-AV1
Encoders
There are three main AV1 encoders, as mentioned above: libaom from Google, rav1e from xiph, and SVT-AV1 from Intel, Netflix, Meta, and others. Historically, SVT-AV1 has been noteworthy for its impressive speed and parallelism, while libaom was known for its great quality and class-leading still image performance (AV1 has an image format associated with it called AVIF).
Forks
The libaom team at Google is largely insulated from community influence; this means a random individual submitting some new code has a low chance of it being accepted. This led to a community culture of forking, with the first noteworthy fork being aom-av1-psy by BlueSwordM.
The goal of this fork was to enhance libaom (aomenc) with better perceptual quality. This means that the encoder would be able to make better decisions about what to keep and what to throw away according to our eyes, instead of chasing metric scores that, while important, don't always reflect the characteristics of the human visual system. BlueSwordM retired aom-av1-psy in September of 2022 to focus on other work.
Perceptual fidelity is not a new concept; encoders like x264 and x265 have a number of perceptually focused features like "psy-rd" and "psy-trellis" (you can read more about these elsewhere). x264 and x265 are very mature encoders for older formats, so mainstream AV1 encoders haven't had the same level of development in this area. This helped aom-av1-psy become very popular among AV1 enthusiasts, and its legacy lives on in the form of two newer forks: aom-av1-lavish (retired as of June 2024) and aom-psy101 (still maintained at the time of writing).
Usually, forks were maintained by a single individual – all of the forks I've mentioned so far have been or currently are. Coding isn't the only thing that goes into maintaining a project, so a solo dev is often responsible for documentation, community management, releases, bug reports, feature requests, testing, and more. This puts pressure on a singular developer to manage a rather complex project with a lot of eyes on it, which is difficult and has often led to project maintenance issues.
All of this had been swirling around in my head at the time, because compiling aom-av1-lavish by collecting the latest experimental patches floating around Discord was kind of difficult and I was keenly interested in what a new project isolated from the aom-av1-psy legacy might look like. This brings us to SVT-AV1-PSY.
How It Started
I had entertained little discussions with friends about what kind of potential SVT-AV1 might have in 2023. The community often doesn't care much about speed versus perceptual quality, so many weren't that invested in seeing what could come out of SVT-AV1 as the aomenc forks were (and have always been) quite good. The rav1e encoder already had a perceptual lean, so many thought the path forward was clearly to invest as much community time as possible into rav1e. I thought this would be a herculean effort that would likely not pay off, and I was convinced that SVT-AV1 had something to offer with the incredible year over year speed improvements we kept on seeing. However, I never once thought of forking.
Coincidentally, at this point a perceptual quality-related issue appeared in the SVT-AV1 GitLab repository. This piqued my attention immediately, and the initial results that Variance Boost was producing looked extremely promising. While the author, Julio Barba, was sharing patch files to communicate with the dev team, excited community members were manually patching the source code and building the encoder to test it out. I was one of those people, and I was very impressed with the results, but the patching workflow was cumbersome and reminded me of my current woes with aom-av1-lavish. So, I hastily put together a GitHub repository with the patch applied to the SVT-AV1 source code alongside some minor tweaks from an SVT-AV1 fork maintained by BlueSwordM. I called it SVT-AV1-PSY, named after aom-av1-psy.
Julio ended up appearing across the various AV1 Discord servers run by community members, and BlueSwordM was able to get in touch with me about how I was integrating and testing his work. I offered to maintain the project while Julio and BlueSwordM would act as the primary contributors, so they could focus on code while I dealt with everything else. We made our first release in February of 2024, and the project began to gain traction from there.
How It's Going
Although I didn't intend to do much programming to start, it was too tantalizing, and I had just begun learning C in October of 2023 so I thought I would try my hand. In the end, everyone on the dev team ended up contributing code, and we also attracted the attention of Clybius – the maintainer of aom-av1-lavish – who stopped working on his aom-av1-psy fork to join us. Trix, a noteworthy encoder known for their work with animation, also joined the team and provided us with a lot of valuable feedback through their extensive testing in the SVT-AV1 Deep Dive blog series.
I could not have asked for a better group of people to work with. The amount I have learned through them, especially Julio, has been immeasurable, and I wouldn't be nearly as competent as I am now without them. I am very grateful for their time and effort, and I am proud of what we have accomplished together.
Here's a short list of what has been achieved with SVT-AV1-PSY:
- We've authored over 20 highly effective features, aimed at improving perceptual quality and ease of use
- We have produced a total of 13 releases at the time of writing, introducing our own release cadence to help push finished features to users faster
- We've built a community of over 500 members on the AV1 for Dummies Discord server, where discussion mainly revolves around SVT-AV1-PSY and related projects
- We've racked up over 250 stars on GitHub at the time of writing (more than SVT-AV1! Though that's likely due to GitHub vs GitLab)
- We have a website for showing off our results, where we notably demonstrate our AVIF performance. At its inception, AVIF with SVT-AV1-PSY was the best in the world by a wide margin; libaom is competitive now due to the introduction of our breakthrough changes into libaom
- We've recently forged a relationship with the incredibly responsive and talented mainline SVT-AV1 team, and we are working to get our features merged into the mainline encoder so everyone can enjoy them
SVT-AV1-PSY is the most popular community fork of a major AV1 encoder, and I am very proud of what we have accomplished. I am excited to see where we go from here, and I am grateful for the opportunity to have worked with such talented and dedicated individuals. I am also grateful for the community that has supported us, and I hope we can continue to provide you even more exciting compression technology in the future.
How It Ended (?)
Full disclosure, SVT-AV1-PSY isn't "ending," per se – that was just some clickbait. We are in the process of getting as many of our features as possible merged into the mainline SVT-AV1 encoder, and we are working closely with the mainline team to see that through. What's happening next is that we are slowly rolling back our involvement in SVT-AV1-PSY.
Due to life, work, and other extenuating circumstances, both myself and Julio are going to be taking a step back from heavily contributing to the project for the time being. I am still going to be around to help out as the maintainer, but we are going to be less active in the day-to-day operations of the project. As of January 2025, I'm going to be stepping back from authoring perceptual quality and performance changes for reasons I will disclose soon; my involvement will mostly consist of maintaining the project and helping out with the mainline integration going forward through December.
Hopefully this isn't a disappointing announcement; I think it is incredibly exciting that the community is in a position to contribute to mainline SVT-AV1 directly, and a fork only serves to duplicate efforts on that front. SVT-AV1-PSY was always meant to be a temporary project, and started as a playground for testing new features that may not have been production-ready immediately. I am very proud of what we have accomplished, and I am excited to see what the future holds for SVT-AV1.
Next Steps
I am a big believer in the idea that breakthrough compression performance enables brand-new applications for multimedia tech, and compression doesn't solely exist to make video files smaller for the benefit of the corporate bottom line. Saying good compression only exists to save X% bandwidth is akin to saying post production only exists to drive X% more sales; post production and visual art are creative and expressive, and compression is a tool to enable that creativity in ways that we likely can't imagine yet.
I am humbled to be a part of a community that is pushing the boundaries of what is possible with video compression, and to have contributed my drop in the bucket with SVT-AV1-PSY. I am excited to see where things go from here, and I'm hopefully not leaving the multimedia compression world anytime soon.
Thank you to Julio, BlueSwordM, and Clybius for all of your help, and thank you to the community for your support. I am excited to see what the future holds!