The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Invalid string class label keyframes
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 489, 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 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2368, in __iter__
example = _apply_feature_types_on_example(
example, self.features, token_per_repo_id=self.token_per_repo_id
)
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2285, in _apply_feature_types_on_example
encoded_example = features.encode_example(example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 2162, in encode_example
return encode_nested_example(self, example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1446, in encode_nested_example
{k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1469, in encode_nested_example
return schema.encode_example(obj) if obj is not None else None
~~~~~~~~~~~~~~~~~~~~~^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1144, in encode_example
example_data = self.str2int(example_data)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1081, in str2int
output = [self._strval2int(value) for value in values]
~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1102, in _strval2int
raise ValueError(f"Invalid string class label {value}")
ValueError: Invalid string class label keyframesNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
AIC 2026 Dataset
Public dataset containing AIC keyframes, videos, CLIP features, keyframe mappings, media information, and object metadata.
Download on VAST / Linux Server
This dataset is public. No Hugging Face token or login is required.
1. Install Hugging Face CLI
pip install -U huggingface_hub
Check the installation:
hf --help
Download a specific file
Use:
hf download hvanphucs/aic2026 \
<FILE_PATH> \
--repo-type dataset \
--local-dir ./aic2026
For example, to download:
keyframes/Keyframes_L21.zip
run:
hf download hvanphucs/aic2026 \
keyframes/Keyframes_L21.zip \
--repo-type dataset \
--local-dir ./aic2026
The downloaded file will be available at:
./aic2026/keyframes/Keyframes_L21.zip
Another example:
hf download hvanphucs/aic2026 \
videos/Videos_L21_a.zip \
--repo-type dataset \
--local-dir ./aic2026
Download multiple specific files
Multiple files can be downloaded in one command:
hf download hvanphucs/aic2026 \
keyframes/Keyframes_L21.zip \
keyframes/Keyframes_L22.zip \
videos/Videos_L21_a.zip \
--repo-type dataset \
--local-dir ./aic2026
Download an entire folder
For example, download everything under keyframes/:
hf download hvanphucs/aic2026 \
--repo-type dataset \
--include "keyframes/**" \
--local-dir ./aic2026
Download all videos:
hf download hvanphucs/aic2026 \
--repo-type dataset \
--include "videos/**" \
--local-dir ./aic2026
Download all metadata:
hf download hvanphucs/aic2026 \
--repo-type dataset \
--include "metadata/**" \
--local-dir ./aic2026
You can also download multiple folders:
hf download hvanphucs/aic2026 \
--repo-type dataset \
--include "keyframes/**" \
--include "metadata/**" \
--local-dir ./aic2026
Download the entire dataset
To download everything:
hf download hvanphucs/aic2026 \
--repo-type dataset \
--local-dir ./aic2026
The directory structure will be preserved:
aic2026/
├── keyframes/
│ ├── Keyframes_L21.zip
│ ├── Keyframes_L22.zip
│ ├── ...
│ └── Keyframes_L30.zip
│
├── videos/
│ ├── Videos_L21_a.zip
│ ├── Videos_L22_a.zip
│ ├── ...
│ └── Videos_L30_a.zip
│
└── metadata/
├── clip-features-32-aic25-b1.zip
├── map-keyframes-aic25-b1.zip
├── media-info-aic25-b1.zip
└── objects-aic25-b1.zip
Download with Python
Install:
pip install -U huggingface_hub
Single file
from huggingface_hub import hf_hub_download
path = hf_hub_download(
repo_id="hvanphucs/aic2026",
repo_type="dataset",
filename="keyframes/Keyframes_L21.zip",
local_dir="./aic2026",
)
print(path)
Entire folder
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="hvanphucs/aic2026",
repo_type="dataset",
allow_patterns=["keyframes/**"],
local_dir="./aic2026",
)
Entire dataset
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="hvanphucs/aic2026",
repo_type="dataset",
local_dir="./aic2026",
)
VAST server example
For a VAST machine with a large data disk, it is recommended to download directly to the target storage location.
For example:
mkdir -p /data/aic2026
hf download hvanphucs/aic2026 \
--repo-type dataset \
--local-dir /data/aic2026
Or download only keyframes:
hf download hvanphucs/aic2026 \
--repo-type dataset \
--include "keyframes/**" \
--local-dir /data/aic2026
Replace /data/aic2026 with the actual storage path on your VAST machine.
Resume / re-run downloads
It is safe to run the same hf download command again.
Hugging Face stores download metadata under:
<local-dir>/.cache/huggingface/
This allows subsequent runs to avoid downloading files that are already up to date.
For large datasets, keeping this directory is recommended.
Example:
hf download hvanphucs/aic2026 \
--repo-type dataset \
--local-dir /data/aic2026
If the dataset is updated later, running the same command again will synchronize the local directory with the latest files available on Hugging Face.
- Downloads last month
- 289