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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
frame_idx: int64
pose: list<item: struct<kp2d: list<item: list<item: double>>, kp3d: list<item: list<item: double>>, is_rig (... 169 chars omitted)
child 0, item: struct<kp2d: list<item: list<item: double>>, kp3d: list<item: list<item: double>>, is_right: bool, b (... 157 chars omitted)
child 0, kp2d: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 1, kp3d: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 2, is_right: bool
child 3, box: list<item: double>
child 0, item: double
child 4, mano: struct<global_orient: list<item: double>, hand_pose: list<item: double>, betas: list<item: double>, (... 26 chars omitted)
child 0, global_orient: list<item: double>
child 0, item: double
child 1, hand_pose: list<item: double>
child 0, item: double
child 2, betas: list<item: double>
child 0, item: double
child 3, cam_t: list<item: double>
child 0, item: double
fps_container: double
ts_first_us: int64
run: string
ts_last_us: int64
height: int64
nonmonotonic_timestamps_repaired: int64
face_score_histogram: struct<0.80: int64>
child 0, 0.80: int64
gpu: string
imu_samples: int64
status: string
frames_left: int64
faces_rejected_tiny: int64
anon: struct<detector: string, size: int64, upright_thr: double, rot4: bool, rot_thr: double, detect_strid (... 80 chars omitted)
child 0, detector: string
child 1, size: int64
child 2, upright_thr: double
child 3, rot4: bool
child 4, rot_thr: double
child 5, detect_stride: int64
child 6, hold_frames: int64
child 7, bench: string
child 8, bench_as_written_by_worker: string
seg: string
white_balanced: bool
card_id: string
span_s: double
source_chunks: list<item: string>
child 0, item: string
color_range: string
faces_rejected_aspect: int64
faces_blurred: int64
color_space: string
fps_processing: double
rectified: bool
faces_rejected_big: int64
wall_s: double
qa_jpegs: list<item: string>
child 0, item: string
hand_zones_requested: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
ms_per_frame: struct<rect: double, decode: double, strip: double, wb: double, face: double, blur: double, enc: dou (... 18 chars omitted)
child 0, rect: double
child 1, decode: double
child 2, strip: double
child 3, wb: double
child 4, face: double
child 5, blur: double
child 6, enc: double
child 7, skip: double
frames_right: int64
face_upper_area_bound: null
frames_missing_s: double
section_s: list<item: double>
child 0, item: double
unreadable_imu_strips: int64
fps_measured_from_imu_clock: double
frames: int64
faces_held_by_persistence: int64
imu_per_frame: double
flip: bool
face_detection: bool
duration_s: double
width: int64
to
{'run': Value('string'), 'card_id': Value('string'), 'seg': Value('string'), 'section_s': List(Value('float64')), 'status': Value('string'), 'frames': Value('int64'), 'frames_left': Value('int64'), 'frames_right': Value('int64'), 'width': Value('int64'), 'height': Value('int64'), 'imu_samples': Value('int64'), 'imu_per_frame': Value('float64'), 'fps_container': Value('float64'), 'fps_measured_from_imu_clock': Value('float64'), 'duration_s': Value('float64'), 'span_s': Value('float64'), 'faces_blurred': Value('int64'), 'faces_held_by_persistence': Value('int64'), 'faces_rejected_tiny': Value('int64'), 'faces_rejected_big': Value('int64'), 'faces_rejected_aspect': Value('int64'), 'face_upper_area_bound': Value('null'), 'unreadable_imu_strips': Value('int64'), 'nonmonotonic_timestamps_repaired': Value('int64'), 'flip': Value('bool'), 'face_detection': Value('bool'), 'color_space': Value('string'), 'color_range': Value('string'), 'source_chunks': List(Value('string')), 'qa_jpegs': List(Value('string')), 'face_score_histogram': {'0.80': Value('int64')}, 'wall_s': Value('float64'), 'fps_processing': Value('float64'), 'ms_per_frame': {'rect': Value('float64'), 'decode': Value('float64'), 'strip': Value('float64'), 'wb': Value('float64'), 'face': Value('float64'), 'blur': Value('float64'), 'enc': Value('float64'), 'skip': Value('float64')}, 'gpu': Value('string'), 'ts_first_us': Value('int64'), 'ts_last_us': Value('int64'), 'frames_missing_s': Value('float64'), 'hand_zones_requested': List(List(Value('float64'))), 'anon': {'detector': Value('string'), 'size': Value('int64'), 'upright_thr': Value('float64'), 'rot4': Value('bool'), 'rot_thr': Value('float64'), 'detect_stride': Value('int64'), 'hold_frames': Value('int64'), 'bench': Value('string'), 'bench_as_written_by_worker': Value('string')}, 'rectified': Value('bool'), 'white_balanced': Value('bool')}
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/json/json.py", line 343, 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 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
frame_idx: int64
pose: list<item: struct<kp2d: list<item: list<item: double>>, kp3d: list<item: list<item: double>>, is_rig (... 169 chars omitted)
child 0, item: struct<kp2d: list<item: list<item: double>>, kp3d: list<item: list<item: double>>, is_right: bool, b (... 157 chars omitted)
child 0, kp2d: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 1, kp3d: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 2, is_right: bool
child 3, box: list<item: double>
child 0, item: double
child 4, mano: struct<global_orient: list<item: double>, hand_pose: list<item: double>, betas: list<item: double>, (... 26 chars omitted)
child 0, global_orient: list<item: double>
child 0, item: double
child 1, hand_pose: list<item: double>
child 0, item: double
child 2, betas: list<item: double>
child 0, item: double
child 3, cam_t: list<item: double>
child 0, item: double
fps_container: double
ts_first_us: int64
run: string
ts_last_us: int64
height: int64
nonmonotonic_timestamps_repaired: int64
face_score_histogram: struct<0.80: int64>
child 0, 0.80: int64
gpu: string
imu_samples: int64
status: string
frames_left: int64
faces_rejected_tiny: int64
anon: struct<detector: string, size: int64, upright_thr: double, rot4: bool, rot_thr: double, detect_strid (... 80 chars omitted)
child 0, detector: string
child 1, size: int64
child 2, upright_thr: double
child 3, rot4: bool
child 4, rot_thr: double
child 5, detect_stride: int64
child 6, hold_frames: int64
child 7, bench: string
child 8, bench_as_written_by_worker: string
seg: string
white_balanced: bool
card_id: string
span_s: double
source_chunks: list<item: string>
child 0, item: string
color_range: string
faces_rejected_aspect: int64
faces_blurred: int64
color_space: string
fps_processing: double
rectified: bool
faces_rejected_big: int64
wall_s: double
qa_jpegs: list<item: string>
child 0, item: string
hand_zones_requested: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
ms_per_frame: struct<rect: double, decode: double, strip: double, wb: double, face: double, blur: double, enc: dou (... 18 chars omitted)
child 0, rect: double
child 1, decode: double
child 2, strip: double
child 3, wb: double
child 4, face: double
child 5, blur: double
child 6, enc: double
child 7, skip: double
frames_right: int64
face_upper_area_bound: null
frames_missing_s: double
section_s: list<item: double>
child 0, item: double
unreadable_imu_strips: int64
fps_measured_from_imu_clock: double
frames: int64
faces_held_by_persistence: int64
imu_per_frame: double
flip: bool
face_detection: bool
duration_s: double
width: int64
to
{'run': Value('string'), 'card_id': Value('string'), 'seg': Value('string'), 'section_s': List(Value('float64')), 'status': Value('string'), 'frames': Value('int64'), 'frames_left': Value('int64'), 'frames_right': Value('int64'), 'width': Value('int64'), 'height': Value('int64'), 'imu_samples': Value('int64'), 'imu_per_frame': Value('float64'), 'fps_container': Value('float64'), 'fps_measured_from_imu_clock': Value('float64'), 'duration_s': Value('float64'), 'span_s': Value('float64'), 'faces_blurred': Value('int64'), 'faces_held_by_persistence': Value('int64'), 'faces_rejected_tiny': Value('int64'), 'faces_rejected_big': Value('int64'), 'faces_rejected_aspect': Value('int64'), 'face_upper_area_bound': Value('null'), 'unreadable_imu_strips': Value('int64'), 'nonmonotonic_timestamps_repaired': Value('int64'), 'flip': Value('bool'), 'face_detection': Value('bool'), 'color_space': Value('string'), 'color_range': Value('string'), 'source_chunks': List(Value('string')), 'qa_jpegs': List(Value('string')), 'face_score_histogram': {'0.80': Value('int64')}, 'wall_s': Value('float64'), 'fps_processing': Value('float64'), 'ms_per_frame': {'rect': Value('float64'), 'decode': Value('float64'), 'strip': Value('float64'), 'wb': Value('float64'), 'face': Value('float64'), 'blur': Value('float64'), 'enc': Value('float64'), 'skip': Value('float64')}, 'gpu': Value('string'), 'ts_first_us': Value('int64'), 'ts_last_us': Value('int64'), 'frames_missing_s': Value('float64'), 'hand_zones_requested': List(List(Value('float64'))), 'anon': {'detector': Value('string'), 'size': Value('int64'), 'upright_thr': Value('float64'), 'rot4': Value('bool'), 'rot_thr': Value('float64'), 'detect_stride': Value('int64'), 'hold_frames': Value('int64'), 'bench': Value('string'), 'bench_as_written_by_worker': Value('string')}, 'rectified': Value('bool'), 'white_balanced': Value('bool')}
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handTrackingSample
Scene and task spread
120 episodes drawn from 44 recordings on 27 different cameras, across 13 top-level categories:
| category | recordings |
|---|---|
| Creative Workshops | 8 |
| Repair Services | 6 |
| Printing and Design | 5 |
| Food and Beverage | 4 |
| Retail and Consumer Goods | 4 |
| Cleaning and Sanitation | 4 |
| Laboratory / Scientific | 3 |
| Automotive and Transport | 3 |
| Clothing and Fashion | 2 |
| Animal Care | 2 |
| Energy and Utilities | 1 |
| Industrial Manufacturing | 1 |
| Agriculture and Farming | 1 |
No category exceeds 8 of 44 recordings. Episodes were selected round-robin across cameras, so the set spans the full camera fleet rather than over-sampling whichever recordings happened to be longest.
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