Behavior 1K
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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 16 new columns ({'total_frames', 'data_path', 'video_files_size_in_mb', 'data_files_size_in_mb', 'robot_type', 'total_videos', 'metainfo_path', 'fps', 'video_path', 'annotation_path', 'codebase_version', 'chunks_size', 'features', 'total_episodes', 'splits', 'total_tasks'}) and 5 missing columns ({'skill_annotation', 'data_folder', 'meta_data', 'task_name', 'primitive_annotation'}).
This happened while the json dataset builder was generating data using
hf://datasets/lerobot/behavior1k-task0040/meta/info.json (at revision 608b067eb1b122ab5db90779ff58271d10c56535), ['hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/annotations/episode_00000001.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/annotations/episode_00000002.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/annotations/episode_00000003.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/annotations/episode_00000004.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/annotations/episode_00000005.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/annotations/episode_00000006.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/annotations/episode_00000007.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/annotations/episode_00000008.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/annotations/episode_00000009.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/annotations/episode_00000010.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/annotations/episode_00000011.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/annotations/episode_00000012.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/annotations/episode_00000013.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/annotations/episode_00000014.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/annotations/episode_00000015.json', 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'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000109.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000110.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000111.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000112.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000113.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000114.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000115.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000116.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000120.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000122.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000123.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000124.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000125.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000126.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000127.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000128.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000129.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000130.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000131.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000132.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000134.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000135.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000136.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000137.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000138.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000139.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000140.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000141.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000142.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000143.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000145.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000146.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000147.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000148.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000149.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000150.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000151.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000152.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000153.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000154.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000156.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000158.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000165.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000171.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000186.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000188.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000191.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000195.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000201.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000219.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000223.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000234.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000247.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000250.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000251.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000252.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000253.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000255.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000256.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000257.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000258.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000259.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000260.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000261.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000262.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000263.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000264.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000265.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000266.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000267.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000268.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000271.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000272.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000274.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000275.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000276.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000277.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000278.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000279.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000280.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000281.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000282.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000283.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000284.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000285.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000286.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000287.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000288.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000290.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000291.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000292.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000293.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000294.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000295.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000296.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000297.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000298.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000299.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/sim/episode_00000300.json', 'hf://datasets/lerobot/behavior1k-task0040@608b067eb1b122ab5db90779ff58271d10c56535/meta/stats.json']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 675, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
codebase_version: string
robot_type: string
total_episodes: int64
total_frames: int64
total_tasks: int64
chunks_size: int64
fps: int64
splits: struct<train: string>
child 0, train: string
data_path: string
video_path: string
metainfo_path: string
annotation_path: string
features: struct<observation.images.rgb.left_wrist: struct<dtype: string, shape: list<item: int64>, names: lis (... 3302 chars omitted)
child 0, observation.images.rgb.left_wrist: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.fps: d (... 158 chars omitted)
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: list<item: string>
child 0, item: string
child 3, info: struct<video.fps: double, video.height: int64, video.width: int64, video.channels: int64, video.code (... 76 chars omitted)
child 0, video.fps: double
child 1, video.height: int64
child 2, video.width: int64
child 3, video.channels: int64
child 4, video.codec: string
child 5, video.pix_fmt: string
child 6, video.is_depth_map: bool
child 7, has_audio: bool
child 1, observation.images.rgb.right_wrist: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.fps: d (... 158 chars omitted)
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, n
...
ld 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 3, fps: int64
child 12, index: struct<dtype: string, shape: list<item: int64>, names: null, fps: int64>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 3, fps: int64
child 13, observation.cam_rel_poses: struct<dtype: string, shape: list<item: int64>, names: null, fps: int64>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 3, fps: int64
child 14, observation.state: struct<dtype: string, shape: list<item: int64>, names: null, fps: int64>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 3, fps: int64
child 15, observation.task_info: struct<dtype: string, shape: list<item: int64>, names: null, fps: int64>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 3, fps: int64
child 16, task_index: struct<dtype: string, shape: list<item: int64>, names: null, fps: int64>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 3, fps: int64
data_files_size_in_mb: int64
video_files_size_in_mb: int64
total_videos: int64
to
{'task_name': Value('string'), 'data_folder': Value('string'), 'meta_data': {'task_duration': Value('int64'), 'valid_duration': List(Value('int64'))}, 'skill_annotation': List({'skill_idx': Value('int64'), 'skill_id': List(Value('int64')), 'skill_description': List(Value('string')), 'object_id': List(List(Value('string'))), 'manipulating_object_id': List(Value('string')), 'spatial_prefix': List(Value('null')), 'frame_duration': List(Value('int64')), 'mp_ef': List(Value('null')), 'skill_type': List(Value('string'))}), 'primitive_annotation': List({'primitive_idx': Value('int64'), 'primitive_id': List(Value('int64')), 'primitive_description': List(Value('string')), 'object_id': List(List(Value('string'))), 'manipulating_object_id': List(Value('string')), 'spatial_prefix': List(Value('null')), 'frame_duration': List(Value('int64')), 'skill_idxes': List(Value('int64'))})}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1342, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 907, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1736, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1889, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 16 new columns ({'total_frames', 'data_path', 'video_files_size_in_mb', 'data_files_size_in_mb', 'robot_type', 'total_videos', 'metainfo_path', 'fps', 'video_path', 'annotation_path', 'codebase_version', 'chunks_size', 'features', 'total_episodes', 'splits', 'total_tasks'}) and 5 missing columns ({'skill_annotation', 'data_folder', 'meta_data', 'task_name', 'primitive_annotation'}).
This happened while the json dataset builder was generating data using
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Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
task_name string | data_folder string | meta_data dict | skill_annotation list | primitive_annotation list |
|---|---|---|---|---|
make microwave popcorn | {
"task_duration": 3806,
"valid_duration": [
0,
3806
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
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"move to"
],
"object_id": [
[
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],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
780
],
"mp_ef": [],
"skill_ty... | [
{
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],
"primitive_description": [
"open door"
],
"object_id": [
[
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]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
1434
],
"skill_idx... | |
make microwave popcorn | {
"task_duration": 4380,
"valid_duration": [
0,
4380
]
} | [
{
"skill_idx": 0,
"skill_id": [
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"object_id": [
[
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],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
1293
],
"mp_ef": [],
"skill_t... | [
{
"primitive_idx": 0,
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"primitive_description": [
"open door"
],
"object_id": [
[
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]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
1779
],
"skill_idx... | |
make microwave popcorn | {
"task_duration": 3464,
"valid_duration": [
0,
3464
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
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]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
1004
],
"mp_ef": [],
"skill_t... | [
{
"primitive_idx": 0,
"primitive_id": [
10
],
"primitive_description": [
"open door"
],
"object_id": [
[
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]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
1530
],
"skill_idx... | |
make microwave popcorn | {
"task_duration": 3445,
"valid_duration": [
0,
3445
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
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]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
684
],
"mp_ef": [],
"skill_ty... | [
{
"primitive_idx": 0,
"primitive_id": [
10
],
"primitive_description": [
"open door"
],
"object_id": [
[
"microwave_hjjxmi_0"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
1204
],
"skill_idx... | |
make microwave popcorn | {
"task_duration": 3814,
"valid_duration": [
0,
3814
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"microwave_hjjxmi_0"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
1145
],
"mp_ef": [],
"skill_t... | [
{
"primitive_idx": 0,
"primitive_id": [
10
],
"primitive_description": [
"open door"
],
"object_id": [
[
"microwave_hjjxmi_0"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
1635
],
"skill_idx... | |
make microwave popcorn | {
"task_duration": 3330,
"valid_duration": [
0,
3330
]
} | [
{
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"skill_id": [
1
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"skill_description": [
"move to"
],
"object_id": [
[
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],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
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],
"mp_ef": [],
"skill_ty... | [
{
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10
],
"primitive_description": [
"open door"
],
"object_id": [
[
"microwave_hjjxmi_0"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
1419
],
"skill_idx... | |
make microwave popcorn | {
"task_duration": 2937,
"valid_duration": [
0,
2937
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"microwave_hjjxmi_0"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
368
],
"mp_ef": [],
"skill_ty... | [
{
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"primitive_id": [
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],
"primitive_description": [
"open door"
],
"object_id": [
[
"microwave_hjjxmi_0"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
1202
],
"skill_idx... | |
make microwave popcorn | {
"task_duration": 3775,
"valid_duration": [
0,
3775
]
} | [
{
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"skill_id": [
1
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"object_id": [
[
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"object_id": [
[
"microwave_hjjxmi_0"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
1324
],
"skill_idx... | |
make microwave popcorn | {
"task_duration": 3023,
"valid_duration": [
0,
3023
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"microwave_hjjxmi_0"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
375
],
"mp_ef": [],
"skill_ty... | [
{
"primitive_idx": 0,
"primitive_id": [
10
],
"primitive_description": [
"open door"
],
"object_id": [
[
"microwave_hjjxmi_0"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
1073
],
"skill_idx... | |
make microwave popcorn | {
"task_duration": 2931,
"valid_duration": [
0,
2931
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"microwave_hjjxmi_0"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
370
],
"mp_ef": [],
"skill_ty... | [
{
"primitive_idx": 0,
"primitive_id": [
10
],
"primitive_description": [
"open door"
],
"object_id": [
[
"microwave_hjjxmi_0"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
925
],
"skill_idxe... | |
make microwave popcorn | {
"task_duration": 3089,
"valid_duration": [
0,
3089
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"microwave_hjjxmi_0"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
417
],
"mp_ef": [],
"skill_ty... | [
{
"primitive_idx": 0,
"primitive_id": [
10
],
"primitive_description": [
"open door"
],
"object_id": [
[
"microwave_hjjxmi_0"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
1011
],
"skill_idx... |
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