Datasets:
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 "tsfile/tsfile_py_cpp.pyx", line 567, in tsfile.tsfile_py_cpp.tsfile_reader_new_c
tsfile.exceptions.FileOpenError: 28:
The above exception was the direct cause of the following exception:
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/tsfile/tsfile.py", line 271, in _split_generators
scan = self._scan_metadata(all_files)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 318, in _scan_metadata
with self._open_reader(file) as reader:
~~~~~~~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 742, in _open_reader
return TsFileReader(file)
File "tsfile/tsfile_reader.pyx", line 323, in tsfile.tsfile_reader.TsFileReaderPy.__init__
SystemError: <class '_weakrefset.WeakSet'> returned a result with an exception set
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 66, 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.
Pouring (TsFile)
This is a time-series conversion of garySue/pouring, a LeRobot v2.0 robotics dataset containing demonstrations of the pouring task with a dual-arm bi_ur5 robot.
- Modalities: Time-series
- Robot:
bi_ur5 - Task:
pouring - License: Apache License 2.0
Dataset scale
| Split | Episodes | Frames / TsFile rows | Sampling rate | Tasks | Source Parquets | Final TsFiles |
|---|---|---|---|---|---|---|
train |
80 | 16,818 | 30 fps | 1 | 80 | 1 |
All numeric frame data is merged into exactly one file, data/pouring.tsfile, containing the table pouring. The file is approximately 2.59 MB.
TsFile schema
| Column | TsFile role | Type | Description |
|---|---|---|---|
Time |
TIME | INT64 |
Milliseconds, computed as Time = round(timestamp * 1000); time restarts within each episode. |
episode_index |
TAG | INT64 |
Original episode identifier (0 through 79). |
task_index |
TAG | INT64 |
Original task identifier (0 for the single pouring task). |
frame_index |
FIELD | INT64 |
Original frame position within the episode. |
sample_index |
FIELD | INT64 |
Original global index, renamed to avoid ambiguity. |
action_0 ... action_13 |
FIELD | FLOAT (float32) |
Complete 14-element source action vector. |
observation_state_0 ... observation_state_13 |
FIELD | FLOAT (float32) |
Complete 14-element source observation.state vector. |
observation_velocity_0 ... observation_velocity_13 |
FIELD | FLOAT (float32) |
Complete 14-element source observation.velocity vector. |
observation_gripper_position_0 ... observation_gripper_position_1 |
FIELD | FLOAT (float32) |
Complete two-element source observation.gripper_position vector. |
The source timestamp column is dropped after generating Time because it is the redundant seconds representation of the same time coordinate (Time / 1000). No rows or other numeric source columns are dropped. All four vectors are flattened without truncation, index is renamed, and the episode, task, and frame identifiers remain available.
Videos and metadata
The source contains three 480 x 640 RGB H.264 camera streams: observation.images.top_rgb, observation.images.left_rgb, and observation.images.right_rgb. Their 240 MP4 files are intentionally omitted from this time-series repository and remain in the original dataset's videos/ tree.
Numeric rows retain episode_index, frame_index, and the 30 fps time coordinate, so they remain aligned with the corresponding source video frames. The source meta/ files are mirrored, except that meta/info.json is rewritten to describe the single TsFile path, TIME/TAG/FIELD schema, flattened and renamed features, omitted video features, and source-video alignment. No videos/ directory is included here.
Reading the data
Install the Apache TsFile Python package, then query the actual table. query_table returns the time column automatically in addition to the requested TAG and FIELD columns.
from tsfile import TsFileReader
reader = TsFileReader("data/pouring.tsfile")
columns = [
"episode_index",
"task_index",
"frame_index",
"sample_index",
"observation_state_0",
"observation_velocity_0",
"action_0",
]
with reader.query_table("pouring", columns, batch_size=65536) as result:
batch = result.read_arrow_batch()
if batch is not None:
print(batch.to_pandas().head())
Source and citation
The source dataset was created with LeRobot and is published at garySue/pouring. Its dataset card does not provide a paper or BibTeX citation; consult the source repository for any future citation updates.
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