The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 134, in _split_generators
analyze(archives, downloaded_dirs, split_name)
~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 88, in analyze
if os.path.isfile(downloaded_files_or_dirs[0]):
~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/streaming.py", line 73, in wrapper
return function(*args, download_config=download_config, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 745, in xisfile
fs, *_ = url_to_fs(path, **storage_options)
~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/fsspec/core.py", line 408, in url_to_fs
fs = filesystem(protocol, **inkwargs)
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 303, in filesystem
return cls(**storage_options)
File "/usr/local/lib/python3.14/site-packages/fsspec/spec.py", line 81, in __call__
obj = super().__call__(*args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/fsspec/implementations/zip.py", line 62, in __init__
self.zip = zipfile.ZipFile(
~~~~~~~~~~~~~~~^
self.fo,
^^^^^^^^
...<3 lines>...
compresslevel=compresslevel,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/zipfile/__init__.py", line 1472, in __init__
self._RealGetContents()
~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/zipfile/__init__.py", line 1535, in _RealGetContents
endrec = _EndRecData(fp)
File "/usr/local/lib/python3.14/zipfile/__init__.py", line 375, in _EndRecData
return _EndRecData64(fpin, filesize - sizeEndCentDir, endrec)
File "/usr/local/lib/python3.14/zipfile/__init__.py", line 303, in _EndRecData64
raise BadZipFile("zipfiles that span multiple disks are not supported")
zipfile.BadZipFile: zipfiles that span multiple disks are not supported
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
InsertTac-uSkin
FR3 single-left-arm teleoperation dataset with dual uSkin tactile sensors. Task: pick up a test tube and insert it into a test tube rack.
- 200 trajectories, 112,854 frames total.
- Two RGB cameras (external + left wrist), 480x640.
- Dual XELA uSkin uSPa46 3-axis tactile sensors (left & right gripper fingers), 24 taxels x 3 axes each.
- Stored in the FTP-1 / Open-X-Tactile ReplayBuffer zarr format.
Format
Follows the Open-X-Tactile (OXT) specification. For the full data format, key
definitions, and coordinate conventions, see https://open-x-tactile.github.io/ .
See supplementary_tactile_note.json for the meaning of each tactile dimension.
Data processing (please read)
- Timestamps are synthesized. RGB (dual 480x640 @30Hz) and uSkin (CAN bus)
have different native rates.
timestamps=arange(T)/30, per episode from 0, constant 1/30 step — a resampled/aligned 30Hz axis, not recorded source times. - Tactile is per-episode baseline-subtracted. uSkin raw values have a large
per-taxel DC offset (~37000). The released
left_tactile_data_uskin1/2is minus the mean of each episode's first ~5 (no-contact) frames -> signed integers, not raw. Add back the per-episode baseline to recover raw values. - Tactile functional area. Each 4x6 uSkin pad is one MTTS functional area:
left_tactile_area_uskin1= 0 (left fingertip),..._uskin2= 1 (right fingertip). The per-taxel 4x6 layout is given by the channel order and the supplementary note, not by the area field. Hand joint index: gripper 1-DoF ->hand_joints_idx = 28.
Contents
The .zarr dataset is under InsertTac-uSkin/ as a single zip split into 4
volumes (~40 GB each):
InsertTac-uSkin/InsertTac-uSkin.z01 / .z02 / .z03 / .zip (.zip = last/main volume)
All four parts are required to extract.
Download and extract
zip -s 0 InsertTac-uSkin.zip --out combined.zip # merge split volumes
unzip combined.zip # -> InsertTac-uSkin.zarr/
import zarr
root = zarr.open_group("InsertTac-uSkin.zarr", mode="r")
print(root["meta"]["episode_ends"][:]) # 200 episode boundaries
print(sorted(root["data"].array_keys()))
Visualizations (viz/)
viz/episode_<i>.mp4 (200 videos): external + left-wrist RGB on top; the two uSkin
pads as bubble plots (radius = normal z, displacement = shear x/y), baseline-
subtracted per episode. For quick visual QC of each trajectory.
Quality-check outputs (oxt_check_output/)
OXT-QC toolkit outputs on THIS released data (QC object == release object):
metadata.json, dict.json, precheck_report*.json (PASS, 0 error/0 warning),
vlm_review*.json (VLM semantic review; scores ~0.70-0.75, 0 fail; initial
screening, human-verified — see the submission note), and the montage PNGs.
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