visioncortex/vtracer

Raster to Vector Graphics Converter

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Summary Information

Updated 12 minutes ago
Added to GitGenius on September 9th, 2026
Created on October 23rd, 2020
Open Issues & Pull Requests: 13 (+0)
GitHub issues: Disabled - open counts may still include pull requests.
Number of forks: 481
Total Stargazers: 6,994 (+0)
Total Subscribers: 65 (+0)

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Detailed Description

VTracer is a raster to vector graphics converter that transforms bitmap images into scalable SVG files.

The tool solves the problem of converting photographs and scanned images into compact vector graphics. It employs a linear image processing pipeline designed to handle colored images while tracing curves faithfully to high-resolution input. Unlike Potrace, which works only with monochrome images and performs expensive optimal-polygon searches, VTracer skips that computational step in favor of speed. Compared to Adobe Illustrator's Image Trace, the tool produces significantly more compact output by adopting a stacking strategy that avoids generating shapes with holes.

VTracer suits projects involving high-resolution image conversion, historic blueprint digitization, and pixel art upscaling. The desktop application offers native-speed processing on large images, curve inspection and simplification, watershed clustering for edge-aware regions, adaptive black-and-white thresholding for uneven scans, and the ability to snap output to fixed color palettes. The console application provides command-line access to the same conversion engine. The tool is available as a Rust library, Python package, and Node package, making it accessible across different development environments.

The project maintains active development with regular refinement of its tracing and clustering algorithms. The tool has evolved to handle both extreme cases—gigapixel-scale scans and low-resolution pixel art—within a single unified pipeline. Desktop and console interfaces are actively maintained alongside the library bindings, indicating sustained investment in multiple usage patterns.