Exoquant is a very high quality image quantization library written in Rust featuring code for basic color quantization, K-Means palette optimization and remapping and dithering with Floyd-Steinberg and ordered ditherers.
This version of the library is a much improved rewrite of a C library of the same name written back in 2004.
Add exoquant as a dependency to your Cargo.toml:
toml
[dependencies]
exoquant = "0.2.0"
For simple use cases, there is a convenience function that simply takes true color image data + a few options as input and returns the palette and indexed image data as output:
```rust use exoquant::*; let image = testdata::test_image();
let (palette, indexeddata) = convertto_indexed(&image.pixels, image.width, 256, &optimizer::KMeans, &ditherer::FloydSteinberg::new()); ```
The low-level API gives you full control over the quantization workflow. It allows for use-cases like:
Using the low-level API to quantize an image looks like this:
```rust use exoquant::*; use exoquant::optimizer::Optimizer;
let image = testdata::test_image();
let histogram = image.pixels.iter().cloned().collect();
let colorspace = SimpleColorSpace::default(); let optimizer = optimizer::KMeans; let mut quantizer = Quantizer::new(&histogram, &colorspace); while quantizer.numcolors() < 256 { quantizer.step(); // very optional optimization, !very slow! // you probably only want to do this every N steps, if at all. if quantizer.numcolors() % 64 == 0 { quantizer = quantizer.optimize(&optimizer, 4); } }
let palette = quantizer.colors(&colorspace); // this optimization is more useful than the above and a lot less slow let palette = optimizer.optimize_palette(&colorspace, &palette, &histogram, 16);
let ditherer = ditherer::FloydSteinberg::new(); let remapper = Remapper::new(&palette, &colorspace, &ditherer); let indexed_data = remapper.remap(&image.pixels, image.width); ```