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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: No 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 - 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.

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.

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