image-png VS zune-image

Encoding images to PNG with the "fast" compression mode is now an order of magnitude faster. This is achieved using a custom Zlib compression implementation that leverages assumptions about the patterns in PNG data to get reasonable compression ratios at phenomenal speeds.

However, the latest release of the png crate - published less than a day ago - has an ultrafast compression mode that's slightly faster than the QOI reference implementation at a comparable compression ratio. So basically you get the properties of QOI in a much more widely used image format.

In other areas, miniz_oxide is faster than miniz, Symphonia is faster than ffmpeg on most codecs, the not-yet-announced zune-png beats both libpng and the more heavily optimized libspng, and the png crate is getting considerable improvements too and also beats libpng.

gif, png, zune-jpeg are on par with their C counterparts in terms of performance

Fun fact: libpng-sys was so difficult to create safe Rust wrapper for that people just wrote their own, 100% safe Rust PNG decoder: https://github.com/image-rs/image-png

I didn't get time to finish the full spec for my attempt at a PNG decoder but it was working on common cases and was faster than image-png at the time https://users.rust-lang.org/t/new-rust-png-decoding-library/30952. I suspect it's not the case anymore since it changes it's deflate crate usage. Here is the perf issue on the image crate https://github.com/image-rs/image-png/issues/114. My code was way simpler than the one in the image crate so that might still be worth a read if you are interested.

The crate actually forbids unsafe. There's nothing necessarily wrong with unsafe code, but not having it provides a nice assurance. Plus if you are willing to tolerate (well audited) unsafe code then you may well be better off just using libpng.

Thanks to the zune-image library, serde-numpy is now supporting PNG and JPEG. Enabling faster io for neural net training loops and other image processing in python

It has been extensively tested on 600,000 real world images, as well as fuzzed in various ways, and is now ready for production use!

I might have misunderstood what you've written, but is there a reason you can't use https://github.com/etemesi254/zune-image as a JPEG decoder? It has minimal use of unsafe and is performant.

It uses SIMD for colorspace conversion and IDCT, the code can be found here and here.

You can see a Github Action that zune-inflate uses here, it's mostly self-explanatory.

I've just added a roundtrip fuzzer to the Rust translation of it so that we can start weeding out the bugs: https://github.com/etemesi254/zune-image/pull/13 Right now it finds some decoding failures in a few seconds.