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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
title: string
url: string
external_resources: struct<scripts: list<item: string>>
  child 0, scripts: list<item: string>
      child 0, item: string
to
{'title': Value('string'), 'url': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              title: string
              url: string
              external_resources: struct<scripts: list<item: string>>
                child 0, scripts: list<item: string>
                    child 0, item: string
              to
              {'title': Value('string'), 'url': Value('string')}
              because column names don't match

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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.

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:

{
  "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:

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:

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. The original code comes from public CodePen pens, which are MIT-licensed (CodePen licensing). Each example's metadata.json keeps the original pen URL so the original author can be credited.

Citation

@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},
}
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Paper for anim2code/dataset