Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
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.
single-block_blue-color_pick-up_80 (TsFile)
This dataset is a TsFile conversion of
underctrl/single-block_blue-color_pick-up_80,
a LeRobot v2.0 dataset collected with a koch robot. Modalities: Time-series.
The source dataset was created using LeRobot
and is licensed as apache-2.0.
Source Dataset
Source task:
Pick single block of multi-color and drop it in the box on the right.
Source scale and split:
| Item | Value |
|---|---|
| Episodes | 80 |
| Frames / converted rows | 31,991 |
| Tasks | 1 |
| Sampling rate | 30 fps |
| Split | train 0:80 |
| Source episode parquet files | 80 |
| Source videos | 160 |
The source frame data uses these main features:
| Feature | Source dtype / shape |
|---|---|
observation.state |
float32, shape [6] |
action |
float32, shape [6] |
episode_index |
int64 |
frame_index |
int64 |
timestamp |
float32 seconds |
next.done |
bool |
index |
int64 |
task_index |
int64 |
The six motor dimensions for observation.state and action are:
shoulder_pan, shoulder_lift, elbow_flex, wrist_flex, wrist_roll,
and gripper.
Converted Layout
This repository contains one TsFile for the train split:
data/single_block_blue_color_pick_up_80.tsfile
Additional source metadata is included under meta/, including info.json,
tasks.jsonl, episodes.jsonl, and stats.json. Source video files are not
mirrored in this repository. They remain available in the original dataset under
videos/.
The original video keys are:
observation.images.phoneobservation.images.webcam
TsFile Schema
Time column:
Time: integer milliseconds, computed asround(timestamp * 1000).
TAG columns:
episode_indextask_index
FIELD columns:
frame_indexsample_index, renamed from sourceindexnext_done, renamed from sourcenext.doneand stored as an integer flagobservation_state_0...observation_state_5action_0...action_5
Flattened vector groups:
| Source column | Converted fields |
|---|---|
observation.state |
observation_state_0 ... observation_state_5 |
action |
action_0 ... action_5 |
Conversion Notes
- The conversion uses the generic LeRobot converter in script mode.
Time = round(timestamp * 1000)in milliseconds and restarts per episode.- The source
timestampcolumn is not retained as a FIELD because it is equivalent toTime / 1000seconds. - The source
indexcolumn is renamed tosample_index. - The source
next.donecolumn is renamed tonext_doneand retained as a scalar FIELD. - Vector/list columns are flattened into scalar fields by preserving the source
prefix, replacing
.with_, and appending element indexes. - Source columns
episode_indexandtask_indexare declared as TsFile TAG columns; remaining scalar columns are FIELD columns. - The converted TsFile contains 31,991 rows, matching the source frame count and staged Parquet row count.
- Source videos are intentionally excluded from this converted repository; video
alignment metadata remains in
meta/info.json.
Minimal Read Example
from huggingface_hub import hf_hub_download
from tsfile import TsFileReader
path = hf_hub_download(
repo_id="zjt24/single_block_blue_color_pick_up_80",
repo_type="dataset",
filename="data/single_block_blue_color_pick_up_80.tsfile",
)
reader = TsFileReader(path)
schemas = reader.get_all_table_schemas()
print(schemas.keys())
with reader.query_table(
"single_block_blue_color_pick_up_80",
["episode_index", "task_index", "frame_index", "observation_state_0"],
batch_size=1024,
) as result:
batch = result.read_arrow_batch()
print(batch)
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