websurfx VS rav1e

GitHub release: https://github.com/neon-mmd/websurfx/releases/tag/v1.0.0

Sorry for being late to reach you out. Thanks for trying out Websurfx, but I can help you out in setting up Websurfx. Just a raise an issue here, or you can ask for help here at our discord, we would be glad in helping you out :).

Recently we decided to do error-handling and provide custom error-messages for the errors related to each engine code present under src/engines folder in one of my project websurfx when using error-stack and we wanted to use enums for it and we found that the error-stack project provides no guide, tutorial or example but thanks to one of our maintainers @xffxff, @xffxff provided a really cool solution to this problem and which helped me learn a lot so I decided to share with you all on what I learned from it in this post and how you can wrap errors with enums when using error-stack so stick till the end of the post.

Also, you can check out the docs for steps on how to do docker deployment. I have covered it over there in great depth.

git clone https://github.com/neon-mmd/websurfx.git

Before you look into the code, I would like to explain in brief what the code below does. The code below a function which builds a new random user-agent from the provided browsers and returns it as a string but it is too slow it takes 10 seconds to build and even with caching option enabled it takes around 5-7 seconds but I want to reduce the time it takes by as much as possible. Please provide me with some suggestions or code on how to improve this down in the comments or here in this issue I have opened in my project.

If you'd like to join the WebSurfx team and help shape the future of a privacy-centric search engine, please check out our project on GitHub: WebSurfx GitHub. Feel free to explore the code, open issues, or submit pull requests. Don't hesitate to introduce yourself and share your ideas!

Sure. You'll see it very often in codec implementations. From rav1e, a fast AV1 encoder mostly written in Rust: https://github.com/xiph/rav1e/tree/master/src/x86

Large portions of the algorithm have been translated into assembly for ARM and x86. Shaving even a couple percent off something like motion compensation search will add up to meaningful gains.

Or the current reference implementation of JPEG: https://github.com/libjpeg-turbo/libjpeg-turbo/tree/main/sim...

Again, if anything AOM would be the one restricting licenses to AV1 (if they chose to) except AOM has stated and also published AV1 in a way to allow license free access to development (which allows people to make forks of the official build like it's open source) and usage. (1)(2) I don't see why they would suddenly change this.

You can speed up the sampling process with --vmaf n_subsample=5, which in my experience works more accurately than either 2 or 4, possibly due to this bug/feature present in multiple encoders. You might also need to manually set the number of threads used for VMAF calculation with --vmaf n_threads=16, but YMMV.

That remember me of https://github.com/xiph/rav1e which is an AV1 encoder

I put in the request for ffmpeg passthrough mastering-display data a few years ago and haven't heard of any support yet.

It's getting there.. Initial steps for FFmepg: https://patchwork.ffmpeg.org/project/ffmpeg/list/?series=8444 rav1e: https://github.com/xiph/rav1e/pull/3000

It's entirely possible to re-use bits of other HW encoders for the first pass (motion estimation, etc).