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liangdabiao/whiteboard-teacher-video — Turn explainer scripts into hand-drawn videos

liangdabiao/whiteboard-teacher-video is a Python skill that turns explainer scripts into videos by drawing them in code.

Repositoryliangdabiao/whiteboard-teacher-video ↗

liangdabiao/whiteboard-teacher-video is a Python skill that turns explainer scripts into videos by drawing them in code.

GitHub description: MG动画视频skill, 抖音爆款Vibe知识大赏知识短片 , 自动配音效,一键出片。图文讲解视频 skill —— 把讲解稿变成「手绘会动的画面」讲解视频。 图形由代码逐笔绘出、文字逐字写出、讲到哪画到哪。五套风格可选,本地 Chrome 渲染, 零生图 API 成本 ,任何改动秒级重渲。

stars
★ 436
Forks
58
Language
Python
License
NOASSERTION
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liangdabiao/whiteboard-teacher-video is a Python skill that turns an explainer script into a video where drawings and text appear in sequence. According to the README, it offers five styles and renders in local Chrome or Edge to produce an MP4 video and SRT subtitles. There is no published latest release information.

Instead of generating pixels with an image generation API, this skill builds the screen by drawing shapes and writing text in code. Every moment on screen is defined by a renderAt(t) function, so it can jump to a specific point in time or render in separate segments. It draws vector shapes with rough.js, displays formulas with KaTeX, captures the browser screen with playwright-core, and assembles the video with ffmpeg-static. It is designed so that rendering the same input again yields the same screen, and its distinguishing feature is that editing the script only redraws the affected segments. It is a fitting approach for anyone who wants to produce videos locally without generative image API costs.

That said, the subtitles assume Chinese, and the render engine has to be brought in from the sitor-ai/frametell repository as a sparse checkout. So there is a dependency on that repository, and it is hard to regard as a standalone configuration. The license is listed as NOASSERTION, so the terms of use cannot be confirmed from the information provided. The reproducible rendering approach stands out, but the Chinese subtitle assumption and the external engine dependency narrow the range of applicability.