2 unstable releases

✓ Uses Rust 2018 edition

0.2.0 Jan 10, 2019
0.1.0 Nov 9, 2018

#30 in Images

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Implementation of GFWX image compression algorithm developed by Graham Fyffe. Library uses rayon for parallelization as a default feature.

Getting Started


To use the library you need to have Rust installed on your machine. The library works on stable Rust branch and doesn't require nightly.


gfwx-rs is available on crates.io. The recommended way to use it is to add a line into your Cargo.toml such as:

gfwx = "0.2"

or, if you don't want to use rayon:

gfwx = { version = "0.2", default-features = false }

Basic usage for compression:

extern crate gfwx;

fn main() {
    let image = ...;

    let builder = gfwx::HeaderBuilder {
        width: image.width(),
        height: image.height(),
        layers: 1,
        channels: image.channels(),
        quality: gfwx::QUALITY_MAX,
        chroma_scale: 8,
        block_size: gfwx::BLOCK_DEFAULT,
        filter: gfwx::Filter::Linear,
        encoder: gfwx::Encoder::Turbo,
        intent: gfwx::Intent::RGBA,
        metadata_size: 0,
    let header = builder.build().unwrap();

    let buffer = vec![0; 2 * image.len()]; // 2 times original size should always be enough
    header.encode(&mut buffer)?;
    let gfwx_size = gfwx::compress_simple(
        &gfwx::ColorTransformProgram::new(), // no color transform
        &mut buffer,

Basic usage for decompression:

extern crate gfwx;

fn main() {
    let mut compressed = ...;

    let header = gfwx::Header::decode(&mut compressed).unwrap();

    let mut decompressed = vec![0; header.get_estimated_decompress_buffer_size()];
    let next_point_of_interest = gfwx::decompress_simple(
        &mut compressed,
        0, // no downsamping
        false, // do not test, full decompress
        &mut decompressed,


Running the tests

Unit tests

To run unit tests:

cargo test

There are also tests for the case when build should fail. You can run them with

cargo test --features test_build_fails

Functional tests

To run functional tests, that use actual images, you can use ci/func_tests.sh:

ci/func_tests.sh ci/test_images/

This command will build reference application, build examples and run functional tests using prepared images in ci/test_images/ folder in the /tmp/gfwx directory (so working directory stays clean).


There are also criterion benchmarks which you can run with

cargo bench


Examples folder contains 3 applications:

  1. compress - compresses an input image to gfwx
  2. decompress - decompresses a gfwx file
  3. compare - compares two images excluding metadata. Useful for comparing the input image and the decompressed one, because they may have the same "pixels" but different metadata, which means these files will have different checksum


Library supports all features of original implementation except:

  • It only supports u8 data, when original implementation supports 8-bit and 16-bit data both signed and unsigned
  • Bayer mode is not supported

However, original implementation supports only channels in interleaved format (for example, [R1, G1, B1, R2, B2, G2, ...]) and always transform channels to planar format. This is not suitable for color spaces which already use planar channel format (for example, YUV420).

For this type of data, our library provides low-level compress_aux_data and decompress_aux_data functions. This functions do not encode header, execute and encode ColorTransformProgram and accept 16-bit image data in planar channels format with boost already applied.

These functions are a little bit more complex to use, but provide more flexibility in case you need only image data compression and decompression. You can manually encode the header with Header::encode(), encode ColorTransformProgram with ColorTransformProgram::encode() and execute it and apply boost with ColorTransformProgram::transform() (for planar channels) and ColorTransformProgram::transform_and_to_planar() (for interleaved channels). Also, instead of using ColorTransformProgram you can use interleaved_to_planar() and planar_to_interleaved() that also can skip some channels during transformation (for example, skip Alpha channel in RGBA).

You can find a complete example on how to use these functions in examples/test_app.rs or by looking into compress_simple and decompress_simple implementation in src/lib.rs.


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