Dataset Viewer
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
clip_id: string
status: string
issue_count: int64
issues: list<item: struct<severity: string, code: string, message: string, path: string, details: struct<exp (... 32 chars omitted)
child 0, item: struct<severity: string, code: string, message: string, path: string, details: struct<expected: doub (... 20 chars omitted)
child 0, severity: string
child 1, code: string
child 2, message: string
child 3, path: string
child 4, details: struct<expected: double, actual: double>
child 0, expected: double
child 1, actual: double
metrics: struct<clip_root: string, dataset_name: string, cameras: list<item: string>, clip_episode_count: int (... 347 chars omitted)
child 0, clip_root: string
child 1, dataset_name: string
child 2, cameras: list<item: string>
child 0, item: string
child 3, clip_episode_count: int64
child 4, clip_total_duration_seconds: double
child 5, meta_episode_count: int64
child 6, meta_row_count: int64
child 7, data_row_count: int64
child 8, episode_row_count: int64
child 9, total_episode_duration_seconds: double
child 10, chunk_video_duration_seconds: struct<cam0: double, cam1: double>
child 0, cam0: double
child 1, cam1: double
child 11, frame_gap_summary: struct<episode_count: int64, frame_gap_count: int64, max_frame_gap_frames: int64>
child 0, episode_count: int64
child 1, frame_gap_count: int64
child 2, max_frame_gap_frames: int64
version: string
camera_in
...
oeffs: list<item: double>
child 0, item: double
child 9, timeshift_cam_imu: double
child 10, timeshift_cam_imu1: double
child 1, cam1: struct<rostopic: string, T_cam_imu: list<item: list<item: double>>, T_cn_cnm1: list<item: list<item: (... 292 chars omitted)
child 0, rostopic: string
child 1, T_cam_imu: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 2, T_cn_cnm1: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 3, T_cam_imu1: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 4, intrinsics: list<item: double>
child 0, item: double
child 5, resolution: list<item: int64>
child 0, item: int64
child 6, cam_overlaps: list<item: int64>
child 0, item: int64
child 7, camera_model: string
child 8, distortion_model: string
child 9, distortion_coeffs: list<item: double>
child 0, item: double
child 10, timeshift_cam_imu: double
child 11, timeshift_cam_imu1: double
dataset_name: string
clip_ids: list<item: string>
child 0, item: string
cameras: list<item: string>
child 0, item: string
path_templates: struct<data: string, videos: string, episodes: string>
child 0, data: string
child 1, videos: string
child 2, episodes: string
source_type: string
to
{'version': Value('string'), 'dataset_name': Value('string'), 'source_type': Value('string'), 'cameras': List(Value('string')), 'clip_ids': List(Value('string')), 'path_templates': {'data': Value('string'), 'videos': Value('string'), 'episodes': Value('string')}, 'camera_info': {'cam0': {'rostopic': Value('string'), 'T_cam_imu': List(List(Value('float64'))), 'T_cam_imu1': List(List(Value('float64'))), 'intrinsics': List(Value('float64')), 'resolution': List(Value('int64')), 'cam_overlaps': List(Value('int64')), 'camera_model': Value('string'), 'distortion_model': Value('string'), 'distortion_coeffs': List(Value('float64')), 'timeshift_cam_imu': Value('float64'), 'timeshift_cam_imu1': Value('float64')}, 'cam1': {'rostopic': Value('string'), 'T_cam_imu': List(List(Value('float64'))), 'T_cn_cnm1': List(List(Value('float64'))), 'T_cam_imu1': List(List(Value('float64'))), 'intrinsics': List(Value('float64')), 'resolution': List(Value('int64')), 'cam_overlaps': List(Value('int64')), 'camera_model': Value('string'), 'distortion_model': Value('string'), 'distortion_coeffs': List(Value('float64')), 'timeshift_cam_imu': Value('float64'), 'timeshift_cam_imu1': Value('float64')}}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 544, 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 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
clip_id: string
status: string
issue_count: int64
issues: list<item: struct<severity: string, code: string, message: string, path: string, details: struct<exp (... 32 chars omitted)
child 0, item: struct<severity: string, code: string, message: string, path: string, details: struct<expected: doub (... 20 chars omitted)
child 0, severity: string
child 1, code: string
child 2, message: string
child 3, path: string
child 4, details: struct<expected: double, actual: double>
child 0, expected: double
child 1, actual: double
metrics: struct<clip_root: string, dataset_name: string, cameras: list<item: string>, clip_episode_count: int (... 347 chars omitted)
child 0, clip_root: string
child 1, dataset_name: string
child 2, cameras: list<item: string>
child 0, item: string
child 3, clip_episode_count: int64
child 4, clip_total_duration_seconds: double
child 5, meta_episode_count: int64
child 6, meta_row_count: int64
child 7, data_row_count: int64
child 8, episode_row_count: int64
child 9, total_episode_duration_seconds: double
child 10, chunk_video_duration_seconds: struct<cam0: double, cam1: double>
child 0, cam0: double
child 1, cam1: double
child 11, frame_gap_summary: struct<episode_count: int64, frame_gap_count: int64, max_frame_gap_frames: int64>
child 0, episode_count: int64
child 1, frame_gap_count: int64
child 2, max_frame_gap_frames: int64
version: string
camera_in
...
oeffs: list<item: double>
child 0, item: double
child 9, timeshift_cam_imu: double
child 10, timeshift_cam_imu1: double
child 1, cam1: struct<rostopic: string, T_cam_imu: list<item: list<item: double>>, T_cn_cnm1: list<item: list<item: (... 292 chars omitted)
child 0, rostopic: string
child 1, T_cam_imu: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 2, T_cn_cnm1: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 3, T_cam_imu1: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 4, intrinsics: list<item: double>
child 0, item: double
child 5, resolution: list<item: int64>
child 0, item: int64
child 6, cam_overlaps: list<item: int64>
child 0, item: int64
child 7, camera_model: string
child 8, distortion_model: string
child 9, distortion_coeffs: list<item: double>
child 0, item: double
child 10, timeshift_cam_imu: double
child 11, timeshift_cam_imu1: double
dataset_name: string
clip_ids: list<item: string>
child 0, item: string
cameras: list<item: string>
child 0, item: string
path_templates: struct<data: string, videos: string, episodes: string>
child 0, data: string
child 1, videos: string
child 2, episodes: string
source_type: string
to
{'version': Value('string'), 'dataset_name': Value('string'), 'source_type': Value('string'), 'cameras': List(Value('string')), 'clip_ids': List(Value('string')), 'path_templates': {'data': Value('string'), 'videos': Value('string'), 'episodes': Value('string')}, 'camera_info': {'cam0': {'rostopic': Value('string'), 'T_cam_imu': List(List(Value('float64'))), 'T_cam_imu1': List(List(Value('float64'))), 'intrinsics': List(Value('float64')), 'resolution': List(Value('int64')), 'cam_overlaps': List(Value('int64')), 'camera_model': Value('string'), 'distortion_model': Value('string'), 'distortion_coeffs': List(Value('float64')), 'timeshift_cam_imu': Value('float64'), 'timeshift_cam_imu1': Value('float64')}, 'cam1': {'rostopic': Value('string'), 'T_cam_imu': List(List(Value('float64'))), 'T_cn_cnm1': List(List(Value('float64'))), 'T_cam_imu1': List(List(Value('float64'))), 'intrinsics': List(Value('float64')), 'resolution': List(Value('int64')), 'cam_overlaps': List(Value('int64')), 'camera_model': Value('string'), 'distortion_model': Value('string'), 'distortion_coeffs': List(Value('float64')), 'timeshift_cam_imu': Value('float64'), 'timeshift_cam_imu1': Value('float64')}}}
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.
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