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
collection: string
profile: string
status: string
elapsed_seconds: double
failed_videos: int64
seed_report: struct<status: string, seeded_videos: int64>
child 0, status: string
child 1, seeded_videos: int64
reports: list<item: struct<pipeline_version: string, video_id: string, status: string, started_at: string, fi (... 10164 chars omitted)
child 0, item: struct<pipeline_version: string, video_id: string, status: string, started_at: string, finished_at: (... 10152 chars omitted)
child 0, pipeline_version: string
child 1, video_id: string
child 2, status: string
child 3, started_at: string
child 4, finished_at: string
child 5, elapsed_seconds: double
child 6, config_hash: string
child 7, config: struct<working_dir: string, threads_for_split: int64, video_segment_length: int64, rough_num_frames_ (... 2977 chars omitted)
child 0, working_dir: string
child 1, threads_for_split: int64
child 2, video_segment_length: int64
child 3, rough_num_frames_per_segment: int64
child 4, fine_num_frames_per_segment: int64
child 5, video_output_format: string
child 6, audio_output_format: string
child 7, video_embedding_batch_num: int64
child 8, segment_retrieval_top_k: int64
child 9, video_embedding_dim: int64
child 10, enable_entity_anchoring: bool
child 11, entity_tracking_model: string
child 12, entity_trackin
...
videos_completed: int64
metrics: struct<segments: int64, segment_boundaries: int64, boundaries_inside_words: int64, tracklets: int64, (... 212 chars omitted)
child 0, segments: int64
child 1, segment_boundaries: int64
child 2, boundaries_inside_words: int64
child 3, tracklets: int64
child 4, visual_entities: int64
child 5, text_mentions: int64
child 6, resolved_references: int64
child 7, unresolved_references: int64
child 8, alignment_edges: int64
child 9, raw_merge_candidates: int64
child 10, gated_merge_candidates: int64
child 11, accepted_merges: int64
edge_modalities: struct<visual: int64>
child 0, visual: int64
videos_expected: int64
category: string
derived_metrics: struct<mean_segment_seconds: double, min_segment_seconds: double, max_segment_seconds: double, bound (... 153 chars omitted)
child 0, mean_segment_seconds: double
child 1, min_segment_seconds: double
child 2, max_segment_seconds: double
child 3, boundary_word_cut_rate: double
child 4, tracklets_per_visual_entity: double
child 5, reference_resolution_rate: double
child 6, gate_pass_rate: double
child 7, merge_acceptance_rate: double
collection_id: string
created_at: string
workdir: string
graph: struct<nodes: int64, edges: int64>
child 0, nodes: int64
child 1, edges: int64
correspondence: struct<matched: int64, no_correspondence_evidence: int64, independent: int64>
child 0, matched: int64
child 1, no_correspondence_evidence: int64
child 2, independent: int64
to
{'created_at': Value('string'), 'collection_id': Value('string'), 'collection': Value('string'), 'category': Value('string'), 'artifact_profile': Value('string'), 'workdir': Value('string'), 'videos_expected': Value('int64'), 'graph': {'nodes': Value('int64'), 'edges': Value('int64')}, 'videos_completed': Value('int64'), 'metrics': {'segments': Value('int64'), 'segment_boundaries': Value('int64'), 'boundaries_inside_words': Value('int64'), 'tracklets': Value('int64'), 'visual_entities': Value('int64'), 'text_mentions': Value('int64'), 'resolved_references': Value('int64'), 'unresolved_references': Value('int64'), 'alignment_edges': Value('int64'), 'raw_merge_candidates': Value('int64'), 'gated_merge_candidates': Value('int64'), 'accepted_merges': Value('int64')}, 'derived_metrics': {'mean_segment_seconds': Value('float64'), 'min_segment_seconds': Value('float64'), 'max_segment_seconds': Value('float64'), 'boundary_word_cut_rate': Value('float64'), 'tracklets_per_visual_entity': Value('float64'), 'reference_resolution_rate': Value('float64'), 'gate_pass_rate': Value('float64'), 'merge_acceptance_rate': Value('float64')}, 'correspondence': {'matched': Value('int64'), 'no_correspondence_evidence': Value('int64'), 'independent': Value('int64')}, 'edge_modalities': {'visual': Value('int64')}}
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 478, 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 2815, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, 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
collection: string
profile: string
status: string
elapsed_seconds: double
failed_videos: int64
seed_report: struct<status: string, seeded_videos: int64>
child 0, status: string
child 1, seeded_videos: int64
reports: list<item: struct<pipeline_version: string, video_id: string, status: string, started_at: string, fi (... 10164 chars omitted)
child 0, item: struct<pipeline_version: string, video_id: string, status: string, started_at: string, finished_at: (... 10152 chars omitted)
child 0, pipeline_version: string
child 1, video_id: string
child 2, status: string
child 3, started_at: string
child 4, finished_at: string
child 5, elapsed_seconds: double
child 6, config_hash: string
child 7, config: struct<working_dir: string, threads_for_split: int64, video_segment_length: int64, rough_num_frames_ (... 2977 chars omitted)
child 0, working_dir: string
child 1, threads_for_split: int64
child 2, video_segment_length: int64
child 3, rough_num_frames_per_segment: int64
child 4, fine_num_frames_per_segment: int64
child 5, video_output_format: string
child 6, audio_output_format: string
child 7, video_embedding_batch_num: int64
child 8, segment_retrieval_top_k: int64
child 9, video_embedding_dim: int64
child 10, enable_entity_anchoring: bool
child 11, entity_tracking_model: string
child 12, entity_trackin
...
videos_completed: int64
metrics: struct<segments: int64, segment_boundaries: int64, boundaries_inside_words: int64, tracklets: int64, (... 212 chars omitted)
child 0, segments: int64
child 1, segment_boundaries: int64
child 2, boundaries_inside_words: int64
child 3, tracklets: int64
child 4, visual_entities: int64
child 5, text_mentions: int64
child 6, resolved_references: int64
child 7, unresolved_references: int64
child 8, alignment_edges: int64
child 9, raw_merge_candidates: int64
child 10, gated_merge_candidates: int64
child 11, accepted_merges: int64
edge_modalities: struct<visual: int64>
child 0, visual: int64
videos_expected: int64
category: string
derived_metrics: struct<mean_segment_seconds: double, min_segment_seconds: double, max_segment_seconds: double, bound (... 153 chars omitted)
child 0, mean_segment_seconds: double
child 1, min_segment_seconds: double
child 2, max_segment_seconds: double
child 3, boundary_word_cut_rate: double
child 4, tracklets_per_visual_entity: double
child 5, reference_resolution_rate: double
child 6, gate_pass_rate: double
child 7, merge_acceptance_rate: double
collection_id: string
created_at: string
workdir: string
graph: struct<nodes: int64, edges: int64>
child 0, nodes: int64
child 1, edges: int64
correspondence: struct<matched: int64, no_correspondence_evidence: int64, independent: int64>
child 0, matched: int64
child 1, no_correspondence_evidence: int64
child 2, independent: int64
to
{'created_at': Value('string'), 'collection_id': Value('string'), 'collection': Value('string'), 'category': Value('string'), 'artifact_profile': Value('string'), 'workdir': Value('string'), 'videos_expected': Value('int64'), 'graph': {'nodes': Value('int64'), 'edges': Value('int64')}, 'videos_completed': Value('int64'), 'metrics': {'segments': Value('int64'), 'segment_boundaries': Value('int64'), 'boundaries_inside_words': Value('int64'), 'tracklets': Value('int64'), 'visual_entities': Value('int64'), 'text_mentions': Value('int64'), 'resolved_references': Value('int64'), 'unresolved_references': Value('int64'), 'alignment_edges': Value('int64'), 'raw_merge_candidates': Value('int64'), 'gated_merge_candidates': Value('int64'), 'accepted_merges': Value('int64')}, 'derived_metrics': {'mean_segment_seconds': Value('float64'), 'min_segment_seconds': Value('float64'), 'max_segment_seconds': Value('float64'), 'boundary_word_cut_rate': Value('float64'), 'tracklets_per_visual_entity': Value('float64'), 'reference_resolution_rate': Value('float64'), 'gate_pass_rate': Value('float64'), 'merge_acceptance_rate': Value('float64')}, 'correspondence': {'matched': Value('int64'), 'no_correspondence_evidence': Value('int64'), 'independent': Value('int64')}, 'edge_modalities': {'visual': Value('int64')}}
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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