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
task_index: int64
task: string
-- schema metadata --
pandas: '{"index_columns": ["task"], "column_indexes": [{"name": null, "f' + 443
to
{'episode_index': Value('int64'), 'tasks': List(Value('string')), 'length': Value('int64'), 'data/chunk_index': Value('int64'), 'data/file_index': Value('int64'), 'dataset_from_index': Value('int64'), 'dataset_to_index': Value('int64'), 'videos/observation.images.top/chunk_index': Value('int64'), 'videos/observation.images.top/file_index': Value('int64'), 'videos/observation.images.top/from_timestamp': Value('float64'), 'videos/observation.images.top/to_timestamp': Value('float64'), 'videos/observation.images.side/chunk_index': Value('int64'), 'videos/observation.images.side/file_index': Value('int64'), 'videos/observation.images.side/from_timestamp': Value('float64'), 'videos/observation.images.side/to_timestamp': Value('float64'), 'stats/action/min': List(Value('float64')), 'stats/action/max': List(Value('float64')), 'stats/action/mean': List(Value('float64')), 'stats/action/std': List(Value('float64')), 'stats/action/count': List(Value('int64')), 'stats/action/q01': List(Value('float64')), 'stats/action/q10': List(Value('float64')), 'stats/action/q50': List(Value('float64')), 'stats/action/q90': List(Value('float64')), 'stats/action/q99': List(Value('float64')), 'stats/observation.state/min': List(Value('float64')), 'stats/observation.state/max': List(Value('float64')), 'stats/observation.state/mean': List(Value('float64')), 'stats/observation.state/std': List(Value('float64')), 'stats/observation.state/count': List(Value('int64')), 'stats/observation.state/q01': List(Valu
...
ode_index/min': List(Value('float64')), 'stats/episode_index/max': List(Value('float64')), 'stats/episode_index/mean': List(Value('float64')), 'stats/episode_index/std': List(Value('float64')), 'stats/episode_index/count': List(Value('int64')), 'stats/episode_index/q01': List(Value('float64')), 'stats/episode_index/q10': List(Value('float64')), 'stats/episode_index/q50': List(Value('float64')), 'stats/episode_index/q90': List(Value('float64')), 'stats/episode_index/q99': List(Value('float64')), 'stats/index/min': List(Value('float64')), 'stats/index/max': List(Value('float64')), 'stats/index/mean': List(Value('float64')), 'stats/index/std': List(Value('float64')), 'stats/index/count': List(Value('int64')), 'stats/index/q01': List(Value('float64')), 'stats/index/q10': List(Value('float64')), 'stats/index/q50': List(Value('float64')), 'stats/index/q90': List(Value('float64')), 'stats/index/q99': List(Value('float64')), 'stats/task_index/min': List(Value('float64')), 'stats/task_index/max': List(Value('float64')), 'stats/task_index/mean': List(Value('float64')), 'stats/task_index/std': List(Value('float64')), 'stats/task_index/count': List(Value('int64')), 'stats/task_index/q01': List(Value('float64')), 'stats/task_index/q10': List(Value('float64')), 'stats/task_index/q50': List(Value('float64')), 'stats/task_index/q90': List(Value('float64')), 'stats/task_index/q99': List(Value('float64')), 'meta/episodes/chunk_index': Value('int64'), 'meta/episodes/file_index': Value('int64')}
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 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 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/parquet/parquet.py", line 220, in _generate_tables
yield Key(file_idx, batch_idx), self._cast_table(pa_table)
~~~~~~~~~~~~~~~~^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/parquet/parquet.py", line 156, 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
task_index: int64
task: string
-- schema metadata --
pandas: '{"index_columns": ["task"], "column_indexes": [{"name": null, "f' + 443
to
{'episode_index': Value('int64'), 'tasks': List(Value('string')), 'length': Value('int64'), 'data/chunk_index': Value('int64'), 'data/file_index': Value('int64'), 'dataset_from_index': Value('int64'), 'dataset_to_index': Value('int64'), 'videos/observation.images.top/chunk_index': Value('int64'), 'videos/observation.images.top/file_index': Value('int64'), 'videos/observation.images.top/from_timestamp': Value('float64'), 'videos/observation.images.top/to_timestamp': Value('float64'), 'videos/observation.images.side/chunk_index': Value('int64'), 'videos/observation.images.side/file_index': Value('int64'), 'videos/observation.images.side/from_timestamp': Value('float64'), 'videos/observation.images.side/to_timestamp': Value('float64'), 'stats/action/min': List(Value('float64')), 'stats/action/max': List(Value('float64')), 'stats/action/mean': List(Value('float64')), 'stats/action/std': List(Value('float64')), 'stats/action/count': List(Value('int64')), 'stats/action/q01': List(Value('float64')), 'stats/action/q10': List(Value('float64')), 'stats/action/q50': List(Value('float64')), 'stats/action/q90': List(Value('float64')), 'stats/action/q99': List(Value('float64')), 'stats/observation.state/min': List(Value('float64')), 'stats/observation.state/max': List(Value('float64')), 'stats/observation.state/mean': List(Value('float64')), 'stats/observation.state/std': List(Value('float64')), 'stats/observation.state/count': List(Value('int64')), 'stats/observation.state/q01': List(Valu
...
ode_index/min': List(Value('float64')), 'stats/episode_index/max': List(Value('float64')), 'stats/episode_index/mean': List(Value('float64')), 'stats/episode_index/std': List(Value('float64')), 'stats/episode_index/count': List(Value('int64')), 'stats/episode_index/q01': List(Value('float64')), 'stats/episode_index/q10': List(Value('float64')), 'stats/episode_index/q50': List(Value('float64')), 'stats/episode_index/q90': List(Value('float64')), 'stats/episode_index/q99': List(Value('float64')), 'stats/index/min': List(Value('float64')), 'stats/index/max': List(Value('float64')), 'stats/index/mean': List(Value('float64')), 'stats/index/std': List(Value('float64')), 'stats/index/count': List(Value('int64')), 'stats/index/q01': List(Value('float64')), 'stats/index/q10': List(Value('float64')), 'stats/index/q50': List(Value('float64')), 'stats/index/q90': List(Value('float64')), 'stats/index/q99': List(Value('float64')), 'stats/task_index/min': List(Value('float64')), 'stats/task_index/max': List(Value('float64')), 'stats/task_index/mean': List(Value('float64')), 'stats/task_index/std': List(Value('float64')), 'stats/task_index/count': List(Value('int64')), 'stats/task_index/q01': List(Value('float64')), 'stats/task_index/q10': List(Value('float64')), 'stats/task_index/q50': List(Value('float64')), 'stats/task_index/q90': List(Value('float64')), 'stats/task_index/q99': List(Value('float64')), 'meta/episodes/chunk_index': Value('int64'), 'meta/episodes/file_index': Value('int64')}
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.
svla_cap_pick_place (TsFile)
Apache TsFile version of cher2018/svla_cap_pick_place.
Overview
A LeRobot robot manipulation dataset. Each frame holds the commanded action and observed observation.state joint positions; camera views are stored as videos in the original dataset.
- Episodes: 35
- Frames: 26204
- Sampling rate: 30 fps
- Tasks: 1
- Split: a single train split
- Robot: so_follower
- Cameras (not uploaded): top, side
Schema (TsFile structure)
All episodes share one TsFile with episode_index and task_index as TAG columns; query a single episode with WHERE episode_index = N.
- Time (INT64, milliseconds) —
round(timestamp * 1000); the sourcetimestampcolumn is dropped (it equals Time / 1000). - episode_index (TAG) — device dimension.
- task_index (TAG) — device dimension.
- frame_index (INT64) — measurement.
- sample_index (INT64) — measurement.
- action_0..N (FLOAT) — commanded joints.
- state_0..N (FLOAT) — measurement.
Vector columns are flattened element-wise with an index suffix.
Usage
Install the Apache TsFile Python SDK (pip install tsfile) and read a converted file:
from pathlib import Path
from tsfile import TsFileReader
path = Path("data/svla_cap_pick_place.tsfile")
with TsFileReader(str(path)) as reader:
schemas = reader.get_all_table_schemas()
print("tables:", list(schemas))
table_name = next(iter(schemas))
table = schemas[table_name]
columns = [column.get_column_name() for column in table.get_columns()]
print("columns:", columns)
field_names = [
column.get_column_name()
for column in table.get_columns()
if column.get_column_name() not in {"Time", "time"}
]
if field_names:
with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
batch = result.read_arrow_batch()
if batch is not None:
print(batch.to_pandas().head())
Source & license
- Original dataset: https://huggingface.co/datasets/cher2018/svla_cap_pick_place
- Author / publisher: cher2018
- License: apache-2.0
- Note: camera videos are NOT included; see the original dataset for them.
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