Datasets:

zjt24
/

catheter_force_depth_eef

Tasks:

Robotics

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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.

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catheter_force_depth_eef

This dataset is a TsFile conversion of the Hugging Face dataset giakhuyendihoc/catheter_force_depth_eef. The source dataset was created using LeRobot and is stored in the episode-split LeRobot v2.1 layout used by OpenPI.

Modalities: Time-series. The original dataset also contains robot camera videos; those videos are not included in this converted repository and remain available from the original Hugging Face dataset.

Source Dataset

Original dataset: giakhuyendihoc/catheter_force_depth_eef
License: apache-2.0
Source format: LeRobot v2.1 episode Parquet files plus metadata and videos
Robot type: ur5
Source scale: 100 episodes, 45,255 frames, 1 task, 1 data chunk, 600 videos
Sampling rate: 30 fps
Split: train (0:100)

Task: Insert the gray cable into the rubber tube and push it down until the cable tip reaches the end.

Converted Files

TsFile data: data/catheter_force_depth_eef.tsfile
Mirrored metadata: meta/
Table name: catheter_force_depth_eef
Time precision: milliseconds
Converted row count: 45,255
Source episode shard count: 100 Parquet files

The original source data path is data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet. The converted TsFile path is data/catheter_force_depth_eef.tsfile.

Schema

Time is synthesized as round(timestamp * 1000) and restarts within each episode, matching the source LeRobot timestamp semantics.

TAG columns:

episode_index
task_index

FIELD columns:

frame_index
sample_index (renamed from source index)
observation_state_0 to observation_state_6
action_0 to action_6
observation_ee_pose_0 to observation_ee_pose_6
teleop_target_pose_0 to teleop_target_pose_6
observation_force_torque_0 to observation_force_torque_5

The source motor names for both observation.state and action are:

shoulder_pan.pos
shoulder_lift.pos
elbow.pos
wrist_1.pos
wrist_2.pos
wrist_3.pos
gripper.pos

The source pose names for observation.ee_pose and teleop.target_pose are:

translation_x
translation_y
translation_z
rotation_x
rotation_y
rotation_z
rotation_w

The source force/torque names are:

fx
fy
fz
tx
ty
tz

Conversion Notes

The source vector columns are flattened into scalar FLOAT fields:

observation.state[7] -> observation_state_0..6
action[7] -> action_0..6
observation.ee_pose[7] -> observation_ee_pose_0..6
teleop.target_pose[7] -> teleop_target_pose_0..6
observation.force_torque[6] -> observation_force_torque_0..5

Dots in source column names are replaced with underscores before appending the vector element index.

The source timestamp column is not retained as a separate field because it is redundant with Time / 1000 seconds. The source index column is renamed to sample_index.

The source video features are omitted from this repository:

observation.images.wrist
observation.images.front
observation.images.base
observation.images.wrist_depth
observation.images.front_depth
observation.images.base_depth

Videos remain in the original dataset at: https://huggingface.co/datasets/giakhuyendihoc/catheter_force_depth_eef/tree/main/videos

The meta/info.json file is mirrored and updated with a tsfile_conversion object that records the source dataset, converted data path, table name, time mapping, TAG columns, flattened features, omitted video features, and row count.

Minimal Read Example

from tsfile import TsFileReader

path = "data/catheter_force_depth_eef.tsfile"

with TsFileReader(path) as reader:
    schemas = reader.get_all_table_schemas()
    print(schemas.keys())

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