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alexlenail/NN-SVG has 5,695 GitHub stars and 746 forks. GitHot measured 0 stars in 24 hours. Last checked 2026-11-08 16:59 UTC. Last push 2026-06-02.

这些数字如何统计

可直接用于发表的神经网络架构示意图。

实测星标增长

24小时
0
7天
更新延迟
15天
更新延迟
1个月
更新延迟

各周期内的星标净变化,周期相互重叠,并非每日新增。缺失的测量保持空白。星标代表关注度,不代表软件质量。

README.md

原文

NN-SVG

License: MIT status | Docs | Contributing

Illustrations of Neural Network architectures are often time-consuming to produce, and machine learning researchers all too often find themselves constructing these diagrams from scratch by hand.

NN-SVG is a tool for creating Neural Network (NN) architecture drawings parametrically rather than manually. It also provides the ability to export those drawings to Scalable Vector Graphics (SVG) files, suitable for inclusion in academic papers or web pages.

The tool provides the ability to generate figures of three kinds: classic Fully-Connected Neural Network (FCNN) figures, Convolutional Neural Network (CNN) figures of the sort introduced in the LeNet paper, and Deep Neural Network figures following the style introduced in the AlexNet paper. The former two are accomplished using the D3 javascript library and the latter with the javascript library Three.js. NN-SVG provides the ability to style the figure to the user's liking via many size, color, and layout parameters.

I hope this tool will save machine learning researchers time, and I hope this software might also serve as a pedagogical tool in some contexts.

Citation

LeNail, (2019). NN-SVG: Publication-Ready Neural Network Architecture Schematics.
Journal of Open Source Software, 4(33), 747, https://doi.org/10.21105/joss.00747

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