Create README.md

README.md

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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/
+- **Mirror:** [Harvard Dataverse](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/RUX7KA) (doi:10.7910/DVN/RUX7KA)
+
+## 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},
+}
+```