mirror of
https://github.com/showlab/Code2Video.git
synced 2026-08-28 06:54:58 +00:00
229 lines
7.2 KiB
Markdown
229 lines
7.2 KiB
Markdown
|
||
# Code2Video: Video Generation via Code
|
||
|
||
<!-- <p align="center">
|
||
<img src="figures/logo.png" alt="Logo" width="30" style="vertical-align: middle; margin-right: 10px;"/>
|
||
<span style="font-size: 1.8em; font-weight: bold;">Code2Video: Agentic Code-Centric Framework for Educational Video Generation</span>
|
||
</p> -->
|
||
|
||
<!-- <p align="center">
|
||
<img src="figures/logo.png" alt="Logo" width="30"/>
|
||
</p> -->
|
||
|
||
<!-- <p align="center">
|
||
<img src="figures/logo.png" alt="Logo" width="30" style="vertical-align: middle; margin-right: 10px;"/>
|
||
<span style="font-size: 1.8em; font-weight: bold;"><em> From code to classroom-ready videos, powered by agents that teach.</em></span>
|
||
</p> -->
|
||
|
||
<p align="center">
|
||
<img src="https://github.com/showlab/Code2Video/raw/main/assets/code2video-demo.gif" alt="Code2Video Demo Animation" width="75%">
|
||
</p>
|
||
|
||
<p align="center">
|
||
<em>Generate Educational video by Python manim code.</em>
|
||
</p>
|
||
|
||
<!-- <p align="center">
|
||
<em>From code to classroom-ready videos, powered by agents that teach.</em>
|
||
</p>
|
||
|
||
<p align="center">
|
||
<em>教学相长，代码为梁；知识作航，动画生光</em>
|
||
</p> -->
|
||
|
||
|
||
<p align="center">
|
||
<a href="https://scholar.google.com.hk/citations?user=9lIMS-EAAAAJ&hl=zh-CN&oi=sra">Yanzhe Chen</a>,
|
||
<a href="https://qhlin.me/">Kevin Qinghong Lin</a>,
|
||
<a href="https://scholar.google.com/citations?user=h1-3lSoAAAAJ&hl=en">Mike Zheng Shou</a> <br>
|
||
Show Lab @ National University of Singapore
|
||
</p>
|
||
|
||
|
||
<p align="center">
|
||
<a href="https://arxiv.org/abs/2510.01174">📄 Paper</a> |
|
||
<a href="https://huggingface.co/papers/2510.01174">🤗 Daily Paper</a> |
|
||
<a href="https://huggingface.co/datasets/YanzheChen/MMMC">🤗 Dataset</a> |
|
||
<a href="https://showlab.github.io/Code2Video/">🌐 Project Website</a> |
|
||
<a href="https://twitter.com/intent/tweet?text=Check%20out%20Code2Video!">💬 X (Twitter)</a>
|
||
</p>
|
||
|
||
---
|
||
|
||
### Table of Contents
|
||
- [🌟 Overview](#-overview)
|
||
- [🚀 Quick Start: Code2Video](#-how-to-create----code2video)
|
||
- [1. Requirements](#1-requirements)
|
||
- [2. Configure LLM API Keys](#2-configure-llm-api-keys)
|
||
- [3. Run Agents](#3-run-agents)
|
||
- [4. Project Organization](#4-project-organization)
|
||
- [📊 Evaluation: MMMC](#-how-to-evaluate----mmmc)
|
||
- [🙏 Acknowledgements](#-acknowledgements)
|
||
- [📌 Citation](#-citation)
|
||
|
||
---
|
||
|
||
## 🌟 Overview
|
||
|
||
<p align="center">
|
||
<img src="figures/first.png" alt="Overview" width="90%">
|
||
</p>
|
||
|
||
**Code2Video** is an **agentic, code-centric framework** that generates high-quality **educational videos** from knowledge points.
|
||
Unlike pixel-based text-to-video models, our approach leverages executable **Manim code** to ensure **clarity, coherence, and reproducibility**.
|
||
|
||
**Key Features**:
|
||
- 🎬 **Code-Centric Paradigm** — executable code as the unified medium for both temporal sequencing and spatial organization of educational videos.
|
||
- 🤖 **Modular Tri-Agent Design** — Planner (storyboard expansion), Coder (debuggable code synthesis), and Critic (layout refinement with anchors) work together for structured generation.
|
||
- 📚 **MMMC Benchmark** — the first benchmark for code-driven video generation, covering 117 curated learning topics inspired by 3Blue1Brown, spanning diverse areas.
|
||
- 🧪 **Multi-Dimensional Evaluation** — systematic assessment on efficiency, aesthetics, and end-to-end knowledge transfer.
|
||
|
||
---
|
||
|
||
## 🚀 Try Code2Video
|
||
|
||
<p align="center">
|
||
<img src="figures/approach.png" alt="Approach" width="85%">
|
||
</p>
|
||
|
||
### 1. Requirements
|
||
|
||
```bash
|
||
pip install -r requirements.txt
|
||
````
|
||
|
||
### 2. Configure LLM API Keys
|
||
|
||
Fill in your **API credentials** in `gpt_config.json`.
|
||
|
||
* **LLM API**:
|
||
* Required for Planner & Coder.
|
||
* Best Manim code quality achieved with **Claude-4-Opus**.
|
||
* **VLM API**:
|
||
* Required for Planner Critic.
|
||
* For layout and aesthetics optimization, provide **Gemini API key**.
|
||
* Best quality achieved with **gemini-2.5-pro-preview-05-06**.
|
||
|
||
* **Visual Assets API**:
|
||
|
||
* To enrich videos with icons, set `ICONFINDER_API_KEY` from [IconFinder](https://www.iconfinder.com/account/applications).
|
||
|
||
### 3. Run Agents
|
||
|
||
We provide two shell scripts for different generation modes:
|
||
|
||
#### (a) Any Query
|
||
|
||
Script: `run_agent_single.sh`
|
||
|
||
Generates a video from a single **knowledge point** specified in the script.
|
||
|
||
```bash
|
||
sh run_agent_single.sh --knowledge_point "Linear transformations and matrices"
|
||
```
|
||
|
||
**Important parameters inside `run_agent_single.sh`:**
|
||
|
||
* `API`: specify which LLM to use.
|
||
* `FOLDER_PREFIX`: output folder prefix (e.g., `TEST-single`).
|
||
* `KNOWLEDGE_POINT`: target concept, e.g. `"Linear transformations and matrices"`.
|
||
|
||
---
|
||
|
||
#### (b) Full Benchmark Mode
|
||
|
||
Script: `run_agent.sh`
|
||
|
||
Runs all (or a subset of) learning topics defined in `long_video_topics_list.json`.
|
||
|
||
```bash
|
||
sh run_agent.sh
|
||
```
|
||
|
||
**Important parameters inside `run_agent.sh`:**
|
||
|
||
* `API`: specify which LLM to use.
|
||
* `FOLDER_PREFIX`: name prefix for saving output folders (e.g., `TEST-LIST`).
|
||
* `MAX_CONCEPTS`: number of concepts to include (`-1` means all).
|
||
* `PARALLEL_GROUP_NUM`: number of groups to run in parallel.
|
||
|
||
### 4. Project Organization
|
||
|
||
A suggested directory structure:
|
||
|
||
```
|
||
src/
|
||
│── agent.py
|
||
│── run_agent.sh
|
||
│── run_agent_single.sh
|
||
│── api_config.json
|
||
│── ...
|
||
│
|
||
├── assets/
|
||
│ ├── icons/ # downloaded visual assets cache via IconFinder API
|
||
│ └── reference/ # reference images
|
||
│
|
||
├── json_files/ # JSON-based topic lists & metadata
|
||
├── prompts/ # prompt templates for LLM calls
|
||
├── CASES/ # generated cases, organized by FOLDER_PREFIX
|
||
│ └── TEST-LIST/ # example multi-topic generation results
|
||
│ └── TEST-single/ # example single-topic generation results
|
||
```
|
||
|
||
|
||
---
|
||
|
||
## 📊 Evaluation -- MMMC
|
||
|
||
We evaluate along **three complementary dimensions**:
|
||
|
||
1. **Knowledge Transfer (TeachQuiz)**
|
||
|
||
```bash
|
||
python3 eval_TQ.py
|
||
```
|
||
|
||
2. **Aesthetic & Structural Quality (AES)**
|
||
|
||
```bash
|
||
python3 eval_AES.py
|
||
```
|
||
|
||
3. **Efficiency Metrics (During Creating)**
|
||
|
||
* Token usage
|
||
* Execution time
|
||
|
||
|
||
👉 More data and evaluation scripts are available at:
|
||
[HuggingFace: MMMC Benchmark](https://huggingface.co/datasets/YanzheChen/MMMC)
|
||
|
||
---
|
||
|
||
## 🙏 Acknowledgements
|
||
|
||
* Video data is sourced from the **[3Blue1Brown official lessons](https://www.3blue1brown.com/#lessons)**.
|
||
These videos represent the **upper bound of clarity and aesthetics** in educational video design and inform our evaluation metrics.
|
||
* We thank all the **Show Lab @ NUS** members for support!
|
||
* This project builds upon open-source contributions from **Manim Community** and the broader AI research ecosystem.
|
||
* High-quality visual assets (icons) are provided by **[IconFinder](https://www.iconfinder.com/)** and **[Icons8](https://icons8.com/icons)**, which were used to enrich the educational videos.
|
||
|
||
|
||
---
|
||
|
||
## 📌 Citation
|
||
|
||
If you find our work useful, please cite:
|
||
|
||
```bibtex
|
||
@misc{code2video,
|
||
title={Code2Video: A Code-centric Paradigm for Educational Video Generation},
|
||
author={Yanzhe Chen and Kevin Qinghong Lin and Mike Zheng Shou},
|
||
year={2025},
|
||
eprint={2510.01174},
|
||
archivePrefix={arXiv},
|
||
primaryClass={cs.CV},
|
||
url={https://arxiv.org/abs/2510.01174},
|
||
}
|
||
```
|
||
|