https://github.com/bfactory-ai/zignal
Image processing library
https://github.com/bfactory-ai/zignal
image-processing webassembly zig zig-package
Last synced: 2 days ago
JSON representation
Image processing library
- Host: GitHub
- URL: https://github.com/bfactory-ai/zignal
- Owner: bfactory-ai
- License: mit
- Created: 2024-04-13T06:47:14.000Z (about 1 year ago)
- Default Branch: master
- Last Pushed: 2025-05-05T06:31:03.000Z (3 days ago)
- Last Synced: 2025-05-05T07:33:15.543Z (3 days ago)
- Topics: image-processing, webassembly, zig, zig-package
- Language: Zig
- Homepage: https://bfactory-ai.github.io/zignal/
- Size: 406 KB
- Stars: 95
- Watchers: 5
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-zig - bfactory-ai/zignal
- awesome-zig - zignal🗒️Image processing library
README
# Zignal
[](https://github.com/bfactory-ai/zignal/actions/workflows/test.yml)
[](https://github.com/bfactory-ai/zignal/actions/workflows/documentation.yml)
Zignal is an image processing library heavily inspired by the amazing [dlib](http://dlib.net).
## Disclaimer
This library is in early stages of development and being used internally.
As a result, the API might change often.
## Installation
```console
zig fetch --save https://github.com/bfactory-ai/zignal/archive/.tar.gz
```
or
```console
zig fetch --save https://github.com/bfactory-ai/zignal/archive/master.tar.gz
```
Then, in your `build.zig`
```zig
const zignal = b.dependency("zignal", .{ .target = target, .optimize = optimize });
// And assuming that your b.addExecutable `exe`:
exe.root_module.addImport("zignal", zignal.module("zignal"));
// If your creating a `module` using b.createModule, then:
module.addImport("zignal", zignal.module("zignal"));
```
## Motivation
This library is used by [Ameli](https://ameli.co.kr/) for their makeup virtual try on.
## Features
Initially, the features in this library are the ones required to get the virtual try on for makeup working.
However, we hope that it can be a foundation from which we can build a high quality image processing library, collaboratively.
Current features include:
- color space conversions
- simple matrix struct with common linear algebra operations
- singular value decomposition (SVD) ported from dlib
- geometry
- points and rectangles
- projective, affine and similarity transforms
- convex hull
- simple image struct with common operations
- resize
- rotate
- crop
- blur
- sharpen
- views (called `sub_image` in dlib or `roi` in OpenCV.)
- drawing and filling functions
- lines
- circles
- polygons
## Examples
One of the greatest things about dlib is the large amount of examples illustrating how to use many of that library features.
I plan to showcase most of the features of this library as simple HTML/JS + Wasm examples, which can be accessed from [here](https://bfactory-ai.github.io/zignal/examples/).
Currently, there are examples for:
- [Color space conversions](https://bfactory-ai.github.io/zignal/examples/colorspace.html)
- [Face alignment](https://bfactory-ai.github.io/zignal/examples/face-alignment.html)
- [Perlin noise generation](https://bfactory-ai.github.io/zignal/examples/perlin-noise.html)
- [Seam carving](https://bfactory-ai.github.io/zignal/examples/seam-carving.html)
## Acknowledgements
First of all, this project would not have been possible without the existence of [dlib](http://dlib.net).
In fact, the first version of the virtual makeup try on was written in C++ with dlib and Emscripten.
However, we decided to give Zig a go, even if that meant rewriting the world, but we have no dependencies now.
Finally, [B factory, Inc](https://www.bfactory.ai/), which is my employer and graciously agreed to release this library to the public.