gnipbao GitHub avatar

whiteboard-video-engine

gnipbao

A local-first whiteboard sketch video engine that converts SVG, line art, illustrations, and photos into MP4 videos with stroke-by-stroke drawing animation.

Stars

73

7-day growth

No data

Forks

16

Open issues

0

License

MIT

Last updated

2026-07-01

AI repository intelligence
FR-AI / ANALYSIS

Why it is worth attention

It bridges the gap between static images and engaging hand-drawn explainer videos, using local neural networks for line extraction and offering multiple hand gestures, contour coloring, and CLI-first design for automation.

Who it is for

  • Content creators and educators who want to produce whiteboard animation videos
  • Developers integrating video generation into scripts or AI agents (e.g., Codex)
  • Artists and illustrators looking to animate their line art
  • Automation engineers building pipeline for tutorial or marketing content

Use cases

  • Creating educational whiteboard videos from hand-drawn SVG or illustrations
  • Converting photos or comic art into animated sketch-style presentations
  • Automating video production in CI/CD or content generation workflows
  • Prototyping animated explainers with customizable hand gestures and coloring effects

Strengths

  • Supports multiple input types: SVG, line art, illustrations, and photos via built-in neural line extraction
  • Offers four fixed hand gestures and contour-oriented coloring modes for realistic handwriting feel
  • CLI-first architecture enables easy scripting, automation, and integration with tools like Codex
  • Provides stroke ordering, path smoothing, and short line merging for clean animation

Considerations

  • Requires manual download of upstream model repositories and weights (not included in the repo)
  • Depends on external tools: FFmpeg and optional PyTorch for line extraction models
  • Hand gestures are limited to four fixed angles (asian, black, children, white) with no custom gesture support mentioned
  • Performance and quality on complex photographs may require parameter tuning and provider selection

README quick start

安装

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