zune-image

This workspace features a set of small,independent and performant image codecs that can be used for decoding and sometimes encoding images in a variety of formats.

The set of codecs aim to have the following features in order of priority

Performance: Performance should be on par with or better than reference libraries. For example, zune-jpeg should easily replace libjpeg-turbo without any noticeable speed loss.
Safety: Minimal unsafe code, with the sole exception of SIMD intrinsics which currently require unsafe.
Robustness: All decoders should be fuzz tested and found bugs fixed promptly.
Ease of use: Consistent API across decoders and encoders. Anyone, even your grandma should be able to decode supported formats
Fast compile times: No dependencies on huge crates. Minimal and relatively well commented code.

Formats

Image Format	Decoder	Encoder	`no_std` Support
jpeg	zune-jpeg	jpeg-encoder	Yes
png	zune-png	-	Yes
ppm	zune-ppm	zune-ppm	Yes
qoi	zune-qoi	zune-qoi	Yes
farbfeld	zune-farbfeld	zune-farbfeld	Yes
psd	zune-psd	-	Yes
jpeg-xl	jxl-oxide	zune-jpegxl	Yes [^1]
hdr	zune-hdr	zune-hdr	No [^2]

[^1] You lose threading capabilities.
[^2] Lack of existence of floor and exp in the core library.

Safety

This workspace allows only 1 type of unsafe: platform specific intrinsics (e.g. SIMD), and only where speed really matters.

All other types are explicitly forbidden.

Repository structure

crates Contain main image code, each crate is prefixed with zune-. The crates are divided into image formats, like zune-png deals with png decoding
zune-imageprocs deals with image processing routines, etc etc
tests: Image testing routines, they mainly read from test-images
benchmarks: Benchmarking routines, they test the library routines with other popular image libraries.
fuzz-corpus : Some interesting image files used for fuzzing.
test-images: Images for testing various aspects of the decoder
docs: Documentation on various parts of the library

Why yet another image library

Rust already has a good image library i.e https://github.com/image-rs/image

But I'll let the overall speed of operations (decoding, applying image operations like blurring) speak for itself when compared to other implementations.

Benchmarks.

Library benchmarks are available online and also reproducible offline

To reproduce benchmarks you can run the following commands

Tested, on Linux, but should work for most operating systems

git clone https://github.com/etemesi254/zune-image
cd ./zune-image
cargo bench --workspace

This will create a criterion directory in target which will contain benchmark results of most image decoding operations.

Fuzzing

Most decoders are tested in CI to ensure new changes do not introduce regressions.

Critical decoders are fuzz tested in CI once every day to catch any potential issue/bug.