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Datasets:
anim2code
/
dataset

Tasks:
Video-Text-to-Text
Languages:
English
Size:
1K<n<10K
ArXiv:
Tags:
code
html
css
javascript
animation
web
License:
Dataset card Files
xet
 Community
dataset
File size: 4,261 Bytes
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---
license: cc-by-4.0
pretty_name: Animation2Code
task_categories:
  - video-text-to-text
language:
  - en
tags:
  - code
  - html
  - css
  - javascript
  - animation
  - web
  - codepen
  - video-to-code
  - benchmark
size_categories:
  - 1K<n<10K
---

# Animation2Code

**Animation2Code** is a benchmark for video-to-code generation of web animations. It contains 1,069 examples, each with a rendered web animation video and self-contained HTML/CSS/JavaScript that produced it.

- **Paper:** *Animation2Code: Evaluating Temporal Visual Reasoning in Video-to-Code Generation* (NeurIPS 2026)
- **Project page:** https://anya-ji.github.io/animation2code-website/

## Dataset Structure

```
data/
├── train/   769 examples
├── val/      86 examples
└── test/    214 examples
    └── codepen-<collection_id>-<pen_id>[-<k>]/
        ├── animation.mp4
        ├── full.html
        └── metadata.json
```

Each example directory contains exactly three files:

| File | Description |
|------|-------------|
| `animation.mp4` | The rendered reference video (the task input). H.264 (`yuv444p`), 1024×768, 30 fps, about 2–8 s. |
| `full.html` | A self-contained HTML document with inline `<style>` and `<script>` tags (the ground-truth target). |
| `metadata.json` | Provenance and dependency information (see below). |

### Example IDs
`codepen-<collection_id>-<pen_id>` names the CodePen collection and pen the example came from. When a single pen contained several independent animations, it was split into sub-examples with a `-<k>` suffix (e.g. `codepen-DrPkOq-poyOMgr-1` … `-4`). All sub-examples of a pen are in the same split.

### Metadata fields

In `metadata.json`:

| Field | Presence | Description |
|-------|----------|-------------|
| `title` | always | Pen title given by the original author. |
| `url` | always | Canonical CodePen URL, kept for attribution. |
| `external_resources` | 486 / 1,069 | `{"scripts": [...], "stylesheets": [...]}`: URLs of external libraries and stylesheets the pen loads. These are **not** inlined into `full.html` and must be loaded from the network when rendering. |
| `jquery_translated` | 41 / 1,069 | The jQuery URL that was removed when the pen's jQuery code was translated to vanilla JavaScript. |

Example:

```json
{
  "title": "Merry Christmas Tree!",
  "url": "https://codepen.io/chrisgannon/pen/dypvKvR",
  "external_resources": {
    "scripts": [
      "https://unpkg.co/gsap@3/dist/gsap.min.js",
      "https://s3-us-west-2.amazonaws.com/s.cdpn.io/16327/MorphSVGPlugin3.min.js"
    ]
  }
}
```

## Usage

The data is stored as raw files (one directory per example), so download it with `huggingface_hub`:

```python
import json
from pathlib import Path
from huggingface_hub import snapshot_download

root = Path(snapshot_download("anim2code/dataset", repo_type="dataset"))
# For a single split only: snapshot_download(..., allow_patterns="data/test/*")

for ex_dir in sorted((root / "data" / "test").iterdir()):
    video_path = ex_dir / "animation.mp4"
    html = (ex_dir / "full.html").read_text()
    meta = json.loads((ex_dir / "metadata.json").read_text())
```

Or with the CLI:

```bash
hf download anim2code/dataset --repo-type dataset --local-dir anim2code_data
```

## Dataset Statistics

| Split | Examples |
|-------|----------|
| train | 769 |
| val   | 86 |
| test  | 214 |
| **total** | **1,069** |

**Durations:** 2–8 s (mean 5.1 ± 2.4 s). Looping animations are captured for at least one full cycle.

## License

This dataset is released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). The original code comes from public CodePen pens, which are MIT-licensed ([CodePen licensing](https://blog.codepen.io/documentation/licensing/)). Each example's `metadata.json` keeps the original pen URL so the original author can be credited.

## Citation

```bibtex
@article{ji2026animation2code,
  title         = {Animation2Code: Evaluating Temporal Visual Reasoning in Video-to-Code Generation},
  author        = {Ji, Anya and Mudunuri, Abhijith Varma and Chan, David M. and Suhr, Alane},
  year          = {2026},
  eprint        = {2606.28593},
  archivePrefix = {arXiv},
  url           = {https://arxiv.org/abs/2606.28593},
}
```