Zignal

Zignal is a zero-dependency image processing library inspired by dlib.

Features

• Core Math: Matrices (SMatrix, Matrix, SVD), PCA, ND Geometry (SIMD Points, affine/projective transforms, convex hull), Statistics, Optimization.
• Computer Vision: Feature detection and matching (FAST, ORB), Edge detection (Shen-Castan), Hough Transform, Feature Distribution Matching (style transfer).
• Image Processing: Spatial transforms (resize, crop, rotate), morphology, convolution filters (blur, sharpen), thresholding, advanced Color Spaces (Lab, Oklab, Oklch, Xyb, Lms, etc.), Perlin noise generation.
• I/O & Graphics: Pure-Zig PNG/JPEG codecs, Canvas API (antialiasing, Bézier curves), Bitmap/PCF Fonts, Colormaps, Terminal graphics (Kitty/Sixel).
• Platform Support: Native Zig, first-class Python bindings, and WASM compilation for the web.

Status

Zignal is under active development and powers production workloads at Ameli for their makeup virtual try-on. The API continues to evolve, so expect occasional breaking changes between minor releases.

Installation

Zig

zig fetch --save git+https://github.com/arrufat/zignal

Then, in your build.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 you're creating a `module` using b.createModule, then:
module.addImport("zignal", zignal.module("zignal"));

Examples | Documentation

Python

pip install zignal-processing

Requires Python 3.10+, no external dependencies

Bindings | PyPI Package | Documentation

CLI

Zignal includes a command-line interface for common operations.

# Build the CLI
zig build

# Run commands
zig-out/bin/zignal <command> [options]

Available commands:

• display - View images in the terminal (supports Kitty, Sixel, etc.)
• resize - Resize images with various filters
• tile - Combine multiple images into a grid
• fdm - Apply style transfer (Feature Distribution Matching)
• info - Show image metadata

Examples

Interactive demos showcasing Zignal's capabilities:

• Color space conversions - Convert between RGB, HSL, Lab, Oklab, and more
• Face alignment - Facial landmark detection and alignment
• Perlin noise generation - Procedural texture generation
• Seam carving - Content-aware image resizing
• Feature distribution matching - Statistical color transfer
• Contrast enhancement - Autocontrast and histogram equalization side-by-side
• White balance - Automatic color correction
• Feature matching - ORB feature detection and matching between images
• Hough transform animation - Real-time visualization of line detection
• Metrics analyzer - PSNR and SSIM comparison for reference vs. distorted images

Sponsors

Special thanks to B Factory, Inc, the Founding Sponsor of Zignal. I originally developed this library internally for our virtual makeup try-on system, and B Factory graciously transferred ownership to the community to ensure its long-term maintenance and growth.