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
category_id: string
task: struct<name: string, description: string, garment_type: string>
child 0, name: string
child 1, description: string
child 2, garment_type: string
labels: list<item: string>
child 0, item: string
schema_version: string
template_description: string
template_status: string
video_stem: string
video_file: string
source_file: string
embedding_file: string
frame_indexing: struct<base: int64, start_frame: int64, end_frame_exclusive: int64, end_frame_inclusive: int64, note (... 163 chars omitted)
child 0, base: int64
child 1, start_frame: int64
child 2, end_frame_exclusive: int64
child 3, end_frame_inclusive: int64
child 4, note: string
child 5, annotation_sampling: struct<type: string, original_frame_stride: int64, original_frame_offset: int64, annotation_frame_k_ (... 31 chars omitted)
child 0, type: string
child 1, original_frame_stride: int64
child 2, original_frame_offset: int64
child 3, annotation_frame_k_maps_to_original_frame: string
summary: struct<num_labels: int64, num_unique_labels: int64, num_annotated_segments: int64, first_frame: int6 (... 271 chars omitted)
child 0, num_labels: int64
child 1, num_unique_labels: int64
child 2, num_annotated_segments: int64
child 3, first_frame: int64
child 4, last_frame_inclusive: int64
child 5, num_labeled_frames: int64
child 6, coverage_is_contiguous: bool
child 7, coverage_is_complete: bool
child 8, num_references_total: int64
child 9, top_k: int
...
child 3, normalized_cost: double
child 4, total_cost: double
child 5, path_length: int64
child 6, weight: double
child 7, boundaries: list<item: int64>
child 0, item: int64
all_reference_votes: list<item: struct<reference_episode_index: int64, normalized_cost: double, weight: double, boundarie (... 22 chars omitted)
child 0, item: struct<reference_episode_index: int64, normalized_cost: double, weight: double, boundaries: list<ite (... 10 chars omitted)
child 0, reference_episode_index: int64
child 1, normalized_cost: double
child 2, weight: double
child 3, boundaries: list<item: int64>
child 0, item: int64
updated_at: string
created_at: string
categories: list<item: struct<id: string, label: string, start: int64, endExclusive: int64, total_episodes: int6 (... 149 chars omitted)
child 0, item: struct<id: string, label: string, start: int64, endExclusive: int64, total_episodes: int64, eligible (... 137 chars omitted)
child 0, id: string
child 1, label: string
child 2, start: int64
child 3, endExclusive: int64
child 4, total_episodes: int64
child 5, eligible_at_sampling: int64
child 6, target_sample_count: int64
child 7, sampled_episode_indices: list<item: int64>
child 0, item: int64
child 8, completed_episode_indices: list<item: null>
child 0, item: null
sample_fraction: double
status: string
dataset_root: string
session_id: string
to
{'schema_version': Value('string'), 'session_id': Value('string'), 'dataset_root': Value('string'), 'sample_fraction': Value('float64'), 'created_at': Value('string'), 'updated_at': Value('string'), 'status': Value('string'), 'categories': List({'id': Value('string'), 'label': Value('string'), 'start': Value('int64'), 'endExclusive': Value('int64'), 'total_episodes': Value('int64'), 'eligible_at_sampling': Value('int64'), 'target_sample_count': Value('int64'), 'sampled_episode_indices': List(Value('int64')), 'completed_episode_indices': List(Value('null'))})}
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 489, 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 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
category_id: string
task: struct<name: string, description: string, garment_type: string>
child 0, name: string
child 1, description: string
child 2, garment_type: string
labels: list<item: string>
child 0, item: string
schema_version: string
template_description: string
template_status: string
video_stem: string
video_file: string
source_file: string
embedding_file: string
frame_indexing: struct<base: int64, start_frame: int64, end_frame_exclusive: int64, end_frame_inclusive: int64, note (... 163 chars omitted)
child 0, base: int64
child 1, start_frame: int64
child 2, end_frame_exclusive: int64
child 3, end_frame_inclusive: int64
child 4, note: string
child 5, annotation_sampling: struct<type: string, original_frame_stride: int64, original_frame_offset: int64, annotation_frame_k_ (... 31 chars omitted)
child 0, type: string
child 1, original_frame_stride: int64
child 2, original_frame_offset: int64
child 3, annotation_frame_k_maps_to_original_frame: string
summary: struct<num_labels: int64, num_unique_labels: int64, num_annotated_segments: int64, first_frame: int6 (... 271 chars omitted)
child 0, num_labels: int64
child 1, num_unique_labels: int64
child 2, num_annotated_segments: int64
child 3, first_frame: int64
child 4, last_frame_inclusive: int64
child 5, num_labeled_frames: int64
child 6, coverage_is_contiguous: bool
child 7, coverage_is_complete: bool
child 8, num_references_total: int64
child 9, top_k: int
...
child 3, normalized_cost: double
child 4, total_cost: double
child 5, path_length: int64
child 6, weight: double
child 7, boundaries: list<item: int64>
child 0, item: int64
all_reference_votes: list<item: struct<reference_episode_index: int64, normalized_cost: double, weight: double, boundarie (... 22 chars omitted)
child 0, item: struct<reference_episode_index: int64, normalized_cost: double, weight: double, boundaries: list<ite (... 10 chars omitted)
child 0, reference_episode_index: int64
child 1, normalized_cost: double
child 2, weight: double
child 3, boundaries: list<item: int64>
child 0, item: int64
updated_at: string
created_at: string
categories: list<item: struct<id: string, label: string, start: int64, endExclusive: int64, total_episodes: int6 (... 149 chars omitted)
child 0, item: struct<id: string, label: string, start: int64, endExclusive: int64, total_episodes: int64, eligible (... 137 chars omitted)
child 0, id: string
child 1, label: string
child 2, start: int64
child 3, endExclusive: int64
child 4, total_episodes: int64
child 5, eligible_at_sampling: int64
child 6, target_sample_count: int64
child 7, sampled_episode_indices: list<item: int64>
child 0, item: int64
child 8, completed_episode_indices: list<item: null>
child 0, item: null
sample_fraction: double
status: string
dataset_root: string
session_id: string
to
{'schema_version': Value('string'), 'session_id': Value('string'), 'dataset_root': Value('string'), 'sample_fraction': Value('float64'), 'created_at': Value('string'), 'updated_at': Value('string'), 'status': Value('string'), 'categories': List({'id': Value('string'), 'label': Value('string'), 'start': Value('int64'), 'endExclusive': Value('int64'), 'total_episodes': Value('int64'), 'eligible_at_sampling': Value('int64'), 'target_sample_count': Value('int64'), 'sampled_episode_indices': List(Value('int64')), 'completed_episode_indices': List(Value('null'))})}
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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