# alexlenail/NN-SVG

Publication-ready NN-architecture schematics.

Repository: https://github.com/alexlenail/NN-SVG
Canonical: https://ross.abutalabs.com/products/nn-svg
Homepage: http://alexlenail.me/NN-SVG/
Language: JavaScript
License: MIT
License Family: permissive
Topics: machine-learning, deep-learning, diagrams, drawing, d3, neural-network, svg, threejs
Last push: 2026-06-02T12:07:58+00:00

## Health v2 (maintenance only)
Score: 61/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 85, release rhythm 8, longevity 100
- inputs: {"age_days": 3912, "days_push": 92, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 5686, forks 751 (observed 2026-08-28T04:09:27.920460+00:00)

## What it is
A web-based tool for creating publication-ready neural network architecture diagrams parametrically, supporting FCNN, LeNet-style CNN, and AlexNet-style figures. Diagrams are highly customizable and exportable as SVG files for papers or web pages.

## Use cases
- draw neural network architecture diagrams for a paper
- create FCNN schematic figures
- generate CNN architecture diagrams like the LeNet paper
- make AlexNet-style deep network illustrations
- export neural network diagrams as SVG
- create diagrams for teaching deep learning

## When to choose
- you need publication-quality NN architecture figures without manual drawing
- you want parametric control over colors, sizes, and layout of network schematics
- you need SVG output for LaTeX papers or web pages

## When to avoid
- you need diagrams auto-generated from a trained model's actual architecture
- you need diagram types beyond FCNN and CNN styles
- you need programmatic/API access rather than an interactive web tool

## Facets
- artifact type: application
- maturity: stable
- function: data-visualization, graphics
- domain: machine-learning, deep-learning, data-visualization, education
- platform: browser
- tags: neural-network-diagrams, svg-export, academic-publishing, d3, threejs, schematics, web, javascript

## Member repositories
- alexlenail/NN-SVG (main) score 61

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:27.920460+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:54:14.048368+00:00, confidence not recorded.
  - readme: https://github.com/alexlenail/NN-SVG (fetched 2026-08-28T04:09:27.920460+00:00, sha 382c0d5431be)
  - homepage: http://alexlenail.me/NN-SVG/ (fetched 2026-08-29T08:49:27.449854+00:00, sha 23af94ced016)
  - site_page: http://alexlenail.me/NN-SVG/about.html (fetched 2026-08-29T08:49:27.458745+00:00, sha 5ff8d9b2c6d1)
- Data as of 2026-08-30T08:39:29.467469+00:00.