awesome-repositories.com
博客
MCP
awesome-repositories.com

通过 AI 驱动的搜索,发现最优秀的开源仓库。

探索精选搜索开源替代品自托管软件博客网站地图
项目关于排名机制媒体报道MCP 服务器
法律隐私政策服务条款
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·
visioncortex avatar

visioncortex/vtracer

0
View on GitHub↗
5,452 星标·371 分支·Rust·mit·3 次浏览www.visioncortex.org/vtracer↗

Vtracer

vtracer is a raster to SVG converter and image vectorization pipeline. It transforms high-resolution scans and pixel-based images into scalable vector graphics by tracing shapes and colors.

The tool includes a specialized pixel art vectorizer that converts low-resolution raster graphics into vector shapes while preserving a pixelated aesthetic. It also functions as a Bezier curve fitting tool to simplify dense point sets into smooth curves, reducing the complexity of vector paths.

The project covers large scale image vectorization for gigapixel-scale data, color clustering and patch segmentation, and vector path optimization to reduce node counts. It allows for the organization of sequential image processing stages into reusable workflows.

Features

  • Raster to Vector Converters - Process gigapixel-scale raster images and convert them into vector graphics using a linear-time fitting algorithm.
  • Raster-to-Vector Conversions - Transforms colored high-resolution scans or pixel art into compact SVG files using color clustering and curve fitting.
  • Color Segmentation - Segments images into solid patches based on color deviation thresholds before vectorization.
  • Curve Fitting - Uses a linear-time curve fitting algorithm to process gigapixel-scale data into smooth Bezier curves.
  • Image Outline Tracing - Converts pixel clusters into raw paths by walking the image tree and combining collinear steps.
  • Image Processing Pipelines - Organizes image processing stages into a linear workflow for raster-to-vector transformations.
  • Large Scale Processing - Processes gigapixel-scale raster images using high-performance fitting algorithms for large-scale vectorization.
  • Path Tracing Algorithms - Converts pixel clusters into raw vector paths by traversing the image structure and merging collinear steps.
  • Pixel Art Vectorization - Transforms low-resolution raster art into vector graphics while simulating a pixelated rendering style.
  • Path Optimizations - Simplifies complex paths and reduces node counts to create cleaner outlines and more efficient SVG files.
  • Raster-to-SVG Transformers - Converts raster images into compact SVG files using advanced curve fitting and color clustering.
  • Bézier Curve Interpolations - Transforms dense point sets into smooth Bezier curves by determining optimal splice points.
  • Vectorization - Transforms low-resolution raster art into vector graphics while preserving a pixelated aesthetic.
  • Pixel-Symmetry Vectorization - Simulates a pixelated aesthetic by tracing individual pixel boundaries instead of smoothing them.
  • Vector Outline Simplifications - Reduces the number of points and nodes in vector images to optimize shape detail and color density.
  • Vector Path Optimizations - Reduces the complexity of vector paths by removing staircases and limiting subpath penalties.
  • Vector Path Simplifications - Implements Bezier-based simplification to reduce node density and file size in vector paths.
  • Graphics & Design - Raster-to-vector graphics converter.
  • Image Processing - Raster-to-vector graphics converter.

Star 历史

visioncortex/vtracer 的 Star 历史图表visioncortex/vtracer 的 Star 历史图表

AI 搜索

探索更多 awesome 仓库

用简单的语言描述您的需求 —— AI 将根据相关性为您从数千个精选开源项目中进行排序。

Start searching with AI

常见问题解答

visioncortex/vtracer 是做什么的?

vtracer is a raster to SVG converter and image vectorization pipeline. It transforms high-resolution scans and pixel-based images into scalable vector graphics by tracing shapes and colors.

visioncortex/vtracer 的主要功能有哪些?

visioncortex/vtracer 的主要功能包括:Raster to Vector Converters, Raster-to-Vector Conversions, Color Segmentation, Curve Fitting, Image Outline Tracing, Image Processing Pipelines, Large Scale Processing, Path Tracing Algorithms。

visioncortex/vtracer 有哪些开源替代品?

visioncortex/vtracer 的开源替代品包括: yqnn/svg-path-editor — This project is a vector path manipulator and SVG geometry transformer that provides a visual interface for modifying… joanrod/star-vector — Star-vector is a suite of vision-language systems designed to generate scalable vector graphics from text or image… rednote-hilab/dots.ocr — dots.ocr is a suite of software utilities for document layout analysis, multilingual optical character recognition,… bradlarson/gpuimage2 — GPUImage2 is a Swift framework for applying real-time filters and effects to images and video using the GPU. It… path/fastimagecache — FastImageCache is an iOS image caching library that provides a persistent disk-based image store. It utilizes a… oliver-moran/jimp — Jimp is a JavaScript image processing library and Node.js manipulation tool designed to perform image transformations…

Vtracer 的开源替代方案

相似的开源项目,按与 Vtracer 的功能重合度排序。
  • yqnn/svg-path-editorYqnn 的头像

    Yqnn/svg-path-editor

    5,222在 GitHub 上查看↗

    This project is a vector path manipulator and SVG geometry transformer that provides a visual interface for modifying SVG path data. It serves as a utility for adding, removing, and converting path segments without writing coordinate code by hand. The tool functions as an SVG path optimizer, reducing path data length and cleaning up coordinate systems. It also includes a geometry transformer for applying scaling, rotation, and translation to vector shapes. The software includes capabilities for visual path manipulation and global geometry transformations. It also provides viewport control to

    TypeScriptsvgsvg-editorsvg-parser
    在 GitHub 上查看↗5,222
  • joanrod/star-vectorjoanrod 的头像

    joanrod/star-vector

    4,462在 GitHub 上查看↗

    Star-vector is a suite of vision-language systems designed to generate scalable vector graphics from text or image inputs. It utilizes a vision-language foundation model to treat the creation of visual elements as a structured code generation task. The system employs a multimodal architecture that maps visual patterns and shapes to corresponding structural elements in a vector code sequence. It incorporates a render-loop feedback mechanism and reinforcement learning to iteratively refine the fidelity of the generated graphics by comparing rendered outputs against target images. The project c

    Pythonllmmultimodal-large-language-modelssvg
    在 GitHub 上查看↗4,462
  • rednote-hilab/dots.ocrrednote-hilab 的头像

    rednote-hilab/dots.ocr

    7,695在 GitHub 上查看↗

    dots.ocr is a suite of software utilities for document layout analysis, multilingual optical character recognition, and scene text digitization. It functions as an engine for extracting digital text and structured layout data from images and PDFs across various human scripts. The project includes a specialized transformer for converting charts, diagrams, and chemical formulas from raster images into scalable vector graphics. It also provides a pipeline to transform extracted text and structural layout from documents and web screenshots into formatted Markdown files. The system covers capabil

    Python
    在 GitHub 上查看↗7,695
  • path/fastimagecachepath 的头像

    path/FastImageCache

    8,068在 GitHub 上查看↗

    FastImageCache is an iOS image caching library that provides a persistent disk-based image store. It utilizes a persistent bitmap cache to store images in uncompressed formats and incorporates an image pre-processing pipeline to optimize assets before they are committed to storage. The library optimizes rendering performance by using memory-mapped image tables for constant-time retrieval and byte-aligned data layouts to prevent memory copies. It organizes images of identical dimensions into shared tables and manages disk space through a least-recently-used cache eviction system. The project

    Objective-C
    在 GitHub 上查看↗8,068
查看 Vtracer 的所有 30 个替代方案→