The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
source_key: string
archive_path: string
bytes: int64
sha256: string
source_etag: string
run: string
purpose: string
to
{'purpose': Value('string'), 'run': 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
source_key: string
archive_path: string
bytes: int64
sha256: string
source_etag: string
run: string
purpose: string
to
{'purpose': Value('string'), 'run': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
OmniDex
OmniDex: Scaling Dexterous Hand Grasping to Diverse Cluttered Scenes.
Upload in progress. This public repository is receiving the full STD data and its object/support assets. Files become available progressively. The release is complete only when std/1.0.0/release.json reports uploaded_verified_public. File counts and total sizes are being measured; this page does not claim a complete release yet.
Layout
assets/r1/
visual/{train,test}/
collision/{train,test}/
supports/
std/1.0.0/
train/{observations,annotations}/
test/{observations,annotations}/
grasp_seeds/{train,test}/
manifests/
splits/
README.md
croissant.json
Large components are packaged into numbered archives, generally around 5 GiB of source files per shard. Observations use .tar; other components use .tar.zst. A scene or an object directory is kept within one archive. Each archive has a per-file size and SHA256 sidecar. Original annotation values and component-relative paths are preserved.
Mapping to the original data
| Original directory | Published component |
|---|---|
train/output, test/output |
std/1.0.0/{train,test}/observations |
train/scene_best, test/scene_best |
std/1.0.0/{train,test}/annotations |
train/raw_lift, test/raw_lift |
std/1.0.0/grasp_seeds/{train,test} |
train/norm_ds, test/norm_ds |
assets/r1/visual/{train,test} |
train/raw, test/raw |
assets/r1/collision/{train,test} |
table_best |
assets/r1/supports |
All original annotation groups are retained. Canonical scenes use exact split/group/scene identities. Extra annotation groups are indexed separately rather than silently merged into train/test observations.
Download after the release completes
Install Python huggingface_hub and the zstd command, then download the helper:
python download_dataset.py --dataset std --release 1.0.0 --with-assets --restore-original-layout --output ./OmniDex
To use HF Mirror, add --endpoint https://hf-mirror.com. The helper checks archive SHA256 hashes and restores OmniDex/data/train/output, scene_best, norm_ds, raw, raw_lift and test equivalents. Stored absolute paths in original annotation files need path remapping; the helper includes resolve_original_path for this purpose. It does not execute serialized annotation payloads.
Versions and additional datasets
STD lives under std/1.0.0 and references shared assets under assets/r1. Additional datasets or versions can use independent configuration files and release directories. See the uploader guide and configuration template. No unverified v2/v3/v4 source paths are assumed.
Release status and terms
Transfer completion, metadata validation, and license documentation are separate statuses. Croissant metadata and complete manifests will be generated after verified transfer. Schema validation, author review, and upstream asset license/provenance documentation remain pending. Original upstream asset terms continue to apply; this repository does not assign a blanket new license to third-party models or textures. See third-party notices.
_transport_tests/ contains synthetic transport test files, not benchmark samples.
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