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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 ({'annotation_path', 'total_tasks', 'video_files_size_in_mb', 'chunks_size', 'total_episodes', 'total_videos', 'features', 'splits', 'robot_type', 'codebase_version', 'metainfo_path', 'video_path', 'data_files_size_in_mb', 'total_frames', 'data_path', 'fps'}) and 5 missing columns ({'primitive_annotation', 'meta_data', 'skill_annotation', 'data_folder', 'task_name'}).
This happened while the json dataset builder was generating data using
hf://datasets/lerobot/behavior1k-task0030/meta/info.json (at revision 296f0e58aa9d521023d59a8df915bd33ede2ff7a), ['hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000001.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000002.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000003.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000004.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000005.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000006.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000007.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000008.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000009.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000010.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000011.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000012.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000013.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000014.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000015.json', 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'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000252.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000253.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000254.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000255.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000256.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000267.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000278.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000280.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000291.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000294.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000296.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/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(List(Value('string'))), '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 ({'annotation_path', 'total_tasks', 'video_files_size_in_mb', 'chunks_size', 'total_episodes', 'total_videos', 'features', 'splits', 'robot_type', 'codebase_version', 'metainfo_path', 'video_path', 'data_files_size_in_mb', 'total_frames', 'data_path', 'fps'}) and 5 missing columns ({'primitive_annotation', 'meta_data', 'skill_annotation', 'data_folder', 'task_name'}).
This happened while the json dataset builder was generating data using
hf://datasets/lerobot/behavior1k-task0030/meta/info.json (at revision 296f0e58aa9d521023d59a8df915bd33ede2ff7a), ['hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000001.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000002.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000003.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000004.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000005.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000006.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000007.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000008.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000009.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000010.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000011.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000012.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000013.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000014.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/annotations/episode_00000015.json', 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'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000243.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000244.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000245.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000247.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000248.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000249.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000250.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000251.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000252.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000253.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000254.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000255.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000256.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000267.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000278.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000280.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000291.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000294.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/meta/sim/episode_00000296.json', 'hf://datasets/lerobot/behavior1k-task0030@296f0e58aa9d521023d59a8df915bd33ede2ff7a/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)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 |
|---|---|---|---|---|
setting the fire | {
"task_duration": 9561,
"valid_duration": [
97,
9658
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"newspaper_74"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
97,
173
],
"mp_ef": [],
"skill_type": ... | [
{
"primitive_idx": 0,
"primitive_id": [
2,
4
],
"primitive_description": [
"pick up from",
"place in"
],
"object_id": [
[
"newspaper_74",
"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 9626,
"valid_duration": [
23,
9649
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"newspaper_74"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
23,
432
],
"mp_ef": [],
"skill_type": ... | [
{
"primitive_idx": 0,
"primitive_id": [
2,
4
],
"primitive_description": [
"pick up from",
"place in"
],
"object_id": [
[
"newspaper_74",
"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 8732,
"valid_duration": [
21,
8753
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"newspaper_74"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
21,
447
],
"mp_ef": [],
"skill_type": ... | [
{
"primitive_idx": 0,
"primitive_id": [
2,
4
],
"primitive_description": [
"pick up from",
"place in"
],
"object_id": [
[
"newspaper_74",
"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 7807,
"valid_duration": [
39,
7846
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"newspaper_74"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
39,
222
],
"mp_ef": [],
"skill_type": ... | [
{
"primitive_idx": 0,
"primitive_id": [
2,
4
],
"primitive_description": [
"pick up from",
"place in"
],
"object_id": [
[
"newspaper_74",
"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 6971,
"valid_duration": [
0,
6971
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"newspaper_74"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
190
],
"mp_ef": [],
"skill_type": [... | [
{
"primitive_idx": 0,
"primitive_id": [
2,
4
],
"primitive_description": [
"pick up from",
"place in"
],
"object_id": [
[
"newspaper_74",
"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 9255,
"valid_duration": [
45,
9300
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"newspaper_74"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
45,
822
],
"mp_ef": [],
"skill_type": ... | [
{
"primitive_idx": 0,
"primitive_id": [
2,
4
],
"primitive_description": [
"pick up from",
"place in"
],
"object_id": [
[
"newspaper_74",
"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 11100,
"valid_duration": [
0,
11100
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"newspaper_74"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
722
],
"mp_ef": [],
"skill_type": [... | [
{
"primitive_idx": 0,
"primitive_id": [
2,
4
],
"primitive_description": [
"pick up from",
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],
"object_id": [
[
"newspaper_74",
"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 8070,
"valid_duration": [
0,
8070
]
} | [
{
"skill_idx": 0,
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1
],
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"move to"
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"object_id": [
[
"newspaper_74"
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],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
186
],
"mp_ef": [],
"skill_type": [... | [
{
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2,
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],
"primitive_description": [
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],
"object_id": [
[
"newspaper_74",
"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 7722,
"valid_duration": [
0,
7722
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"newspaper_74"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
189
],
"mp_ef": [],
"skill_type": [... | [
{
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2,
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],
"primitive_description": [
"pick up from",
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],
"object_id": [
[
"newspaper_74",
"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 9679,
"valid_duration": [
0,
9679
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"newspaper_74"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
805
],
"mp_ef": [],
"skill_type": [... | [
{
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2,
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],
"primitive_description": [
"pick up from",
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],
"object_id": [
[
"newspaper_74",
"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 9129,
"valid_duration": [
30,
9159
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"newspaper_74"
]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
30,
531
],
"mp_ef": [],
"skill_type": ... | [
{
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2,
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],
"primitive_description": [
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"object_id": [
[
"newspaper_74",
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],
[
"newspaper_74",
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]
... | |
setting the fire | {
"task_duration": 8331,
"valid_duration": [
0,
8331
]
} | [
{
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"object_id": [
[
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],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
0,
453
],
"mp_ef": [],
"skill_type": [... | [
{
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"primitive_description": [
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],
"object_id": [
[
"newspaper_74",
"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 10584,
"valid_duration": [
84,
10668
]
} | [
{
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"skill_id": [
1
],
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"move to"
],
"object_id": [
[
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]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
84,
270
],
"mp_ef": [],
"skill_type": ... | [
{
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],
"primitive_description": [
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],
"object_id": [
[
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"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 11266,
"valid_duration": [
0,
11266
]
} | [
{
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"object_id": [
[
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],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
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991
],
"mp_ef": [],
"skill_type": [... | [
{
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],
"primitive_description": [
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],
"object_id": [
[
"newspaper_74",
"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 9792,
"valid_duration": [
106,
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]
} | [
{
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"object_id": [
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"frame_duration": [
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],
"mp_ef": [],
"skill_type":... | [
{
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"object_id": [
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],
[
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]
... | |
setting the fire | {
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"valid_duration": [
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]
} | [
{
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"skill_type": [... | [
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[
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]
... | |
setting the fire | {
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} | [
{
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],
"mp_ef": [],
"skill_type":... | [
{
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"object_id": [
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"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
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117,
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} | [
{
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"object_id": [
[
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]
],
"manipulating_object_id": [],
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"frame_duration": [
117,
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],
"mp_ef": [],
"skill_type":... | [
{
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],
"primitive_description": [
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],
"object_id": [
[
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"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 10605,
"valid_duration": [
130,
10735
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} | [
{
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"object_id": [
[
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],
"manipulating_object_id": [],
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"frame_duration": [
130,
607
],
"mp_ef": [],
"skill_type":... | [
{
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],
"primitive_description": [
"pick up from",
"place in"
],
"object_id": [
[
"newspaper_74",
"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 12082,
"valid_duration": [
46,
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]
} | [
{
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"move to"
],
"object_id": [
[
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]
],
"manipulating_object_id": [],
"spatial_prefix": [],
"frame_duration": [
46,
724
],
"mp_ef": [],
"skill_type": ... | [
{
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2,
4
],
"primitive_description": [
"pick up from",
"place in"
],
"object_id": [
[
"newspaper_74",
"coffee_table_koagbh_0"
],
[
"newspaper_74",
"wood_fireplace_gpnsij_0"
]
... | |
setting the fire | {
"task_duration": 12420,
"valid_duration": [
60,
12480
]
} | [
{
"skill_idx": 0,
"skill_id": [
1
],
"skill_description": [
"move to"
],
"object_id": [
[
"newspaper_74"
]
],
"manipulating_object_id": [],
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... | |
setting the fire | {
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setting the fire | {
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setting the fire | {
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... | |
setting the fire | {
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... | |
setting the fire | {
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... | |
setting the fire | {
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... | |
setting the fire | {
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... | |
setting the fire | {
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"skill_type": ... | [
{
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... | |
setting the fire | {
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} | [
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"skill_type": ... | [
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... |
End of preview.
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