Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ArrowInvalid
Message: JSON parse error: Missing a name for object member. in row 0
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 324, in _generate_tables
df = pandas_read_json(f)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
obj = self._get_object_parser(self.data)
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
self._parse()
~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1391, in _parse
self.obj = DataFrame(
~~~~~~~~~^
ujson_loads(json, precise_float=self.precise_float), dtype=None
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/pandas/core/frame.py", line 782, in __init__
mgr = dict_to_mgr(data, index, columns, dtype=dtype, copy=copy, typ=manager)
File "/usr/local/lib/python3.14/site-packages/pandas/core/internals/construction.py", line 503, in dict_to_mgr
return arrays_to_mgr(arrays, columns, index, dtype=dtype, typ=typ, consolidate=copy)
File "/usr/local/lib/python3.14/site-packages/pandas/core/internals/construction.py", line 114, in arrays_to_mgr
index = _extract_index(arrays)
File "/usr/local/lib/python3.14/site-packages/pandas/core/internals/construction.py", line 680, in _extract_index
raise ValueError(
"Mixing dicts with non-Series may lead to ambiguous ordering."
)
ValueError: Mixing dicts with non-Series may lead to ambiguous ordering.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4408, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2679, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2861, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2395, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, 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 327, in _generate_tables
raise e
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Missing a name for object member. in row 0Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
EgoTouch clean atomic P1 cache v1
Exact memory-mapped cache used to train
MIT-Media-Lab/egotouch-tactile-encoder-p1-v1.
It is derived from
MIT-Media-Lab/egotouch-annotations-v1
using
kaichen-z/VLA-HAND@31d75d2.
The cache can be consumed directly by egotouch_formal.data.FormalWindowDataset.
It contains annotations only; no RGB images or video are redistributed.
Protocol
- Official EgoTouch source-recording split: train, validation, test seen, and test unseen.
- Pairwise source-recording overlap between all retained splits: zero.
- 5,891 episodes from 32 recordings not covered by the official split are quarantined, not reassigned.
- Target hand only, selected by the published episode
anno_type. - Pose source: target-hand
joints_camspace, 21 joints x XYZ. - History H=8; future-validity offset K=4.
- Train stride 3; evaluation stride 8.
- Fixed recording/hand-balanced 4,096-window evaluation gallery per split.
- Left tactile horizontal flip and left pose x reflection; right unchanged.
- 66 bend cells excluded, leaving 151 pressure cells per hand.
- Every window stays within one published atomic episode.
Inventory
| Split | Episodes | Recordings | Frames | Windows |
|---|---|---|---|---|
| train | 84,054 | 1,199 | 2,769,886 | 642,727 |
| validation | 7,718 | 135 | 266,102 | 26,326 |
| test seen | 9,944 | 135 | 340,566 | 33,637 |
| test unseen | 3,552 | 65 | 115,887 | 11,229 |
Layout
manifest.json
pressure_masks.npy
source_metadata/
train/
val/
test_seen/
test_unseen/
Each split contains:
touch.npy: float16[frames, 21, 21]pose.npy: float32[frames, 21, 3]pose_valid.npy: boolean[frames]windows.npy: structured window indexeval_indices.npy: fixed evaluation subset indicesmetadata.json: source recording and atomic episode offsets
manifest.json stores the complete protocol, input SHA-256 checksums, unmatched
episode IDs, split counts, and leakage audit.
Usage
Download this dataset into a directory and point the repository dataloader at that directory:
from egotouch_formal.data import FormalWindowDataset
train = FormalWindowDataset(
"/path/to/egotouch-clean-atomic-p1-cache-v1", "train", "p1"
)
sample = train[0]
print(sample["touch"].shape) # [8, 21, 21]
print(sample["pose"].shape) # [8, 21, 3]
The cache is a convenience snapshot. It can be rebuilt from the published
annotation tar with Tactile/scripts/build_egotouch_clean_atomic_cache.py.
Because files are memory mapped, downloading the complete split files is
required before training.
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