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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
000000: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000001: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000002: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000003: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000004: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000005: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000006: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000007: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000008: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000009: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000010: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000011: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000012: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000013: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000014: struct<p
...
loat>>
child 0, points: list<item: float>
child 0, item: float
000118: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000119: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000120: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000121: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000122: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000123: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000124: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000125: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000126: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000127: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000128: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000129: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
point_inst: int16
sample_body: int64
sample_geom: int64
sample_geom_name: binary
sample_local: list<item: float>
child 0, item: float
sample_region: binary
to
{'000000': {'points': List(Value('float32'), length=3)}, '000001': {'points': List(Value('float32'), length=3)}, '000002': {'points': List(Value('float32'), length=3)}, '000003': {'points': List(Value('float32'), length=3)}, '000004': {'points': List(Value('float32'), length=3)}, '000005': {'points': List(Value('float32'), length=3)}, '000006': {'points': List(Value('float32'), length=3)}, '000007': {'points': List(Value('float32'), length=3)}, '000008': {'points': List(Value('float32'), length=3)}, '000009': {'points': List(Value('float32'), length=3)}, '000010': {'points': List(Value('float32'), length=3)}, '000011': {'points': List(Value('float32'), length=3)}, '000012': {'points': List(Value('float32'), length=3)}, '000013': {'points': List(Value('float32'), length=3)}, '000014': {'points': List(Value('float32'), length=3)}, '000015': {'points': List(Value('float32'), length=3)}, '000016': {'points': List(Value('float32'), length=3)}, '000017': {'points': List(Value('float32'), length=3)}, '000018': {'points': List(Value('float32'), length=3)}, '000019': {'points': List(Value('float32'), length=3)}, '000020': {'points': List(Value('float32'), length=3)}, '000021': {'points': List(Value('float32'), length=3)}, '000022': {'points': List(Value('float32'), length=3)}, '000023': {'points': List(Value('float32'), length=3)}, '000024': {'points': List(Value('float32'), length=3)}, '000025': {'points': List(Value('float32'), length=3)}, '000026': {'points': List(Value('float32'),
...
'000115': {'points': List(Value('float32'), length=3)}, '000116': {'points': List(Value('float32'), length=3)}, '000117': {'points': List(Value('float32'), length=3)}, '000118': {'points': List(Value('float32'), length=3)}, '000119': {'points': List(Value('float32'), length=3)}, '000120': {'points': List(Value('float32'), length=3)}, '000121': {'points': List(Value('float32'), length=3)}, '000122': {'points': List(Value('float32'), length=3)}, '000123': {'points': List(Value('float32'), length=3)}, '000124': {'points': List(Value('float32'), length=3)}, '000125': {'points': List(Value('float32'), length=3)}, '000126': {'points': List(Value('float32'), length=3)}, '000127': {'points': List(Value('float32'), length=3)}, '000128': {'points': List(Value('float32'), length=3)}, '000129': {'points': List(Value('float32'), length=3)}, '000130': {'points': List(Value('float32'), length=3)}, '000131': {'points': List(Value('float32'), length=3)}, '000132': {'points': List(Value('float32'), length=3)}, '000133': {'points': List(Value('float32'), length=3)}, '000134': {'points': List(Value('float32'), length=3)}, '000135': {'points': List(Value('float32'), length=3)}, '000136': {'points': List(Value('float32'), length=3)}, '000137': {'points': List(Value('float32'), length=3)}, 'point_inst': Value('int16'), 'sample_body': Value('int64'), 'sample_geom': Value('int64'), 'sample_geom_name': Value('string'), 'sample_local': List(Value('float32'), length=3), 'sample_region': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 87, in _generate_tables
yield Key(file_idx, batch_idx), cast_table_to_features(pa_table, self.info.features)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2280, in cast_table_to_features
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
000000: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000001: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000002: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000003: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000004: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000005: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000006: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000007: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000008: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000009: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000010: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000011: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000012: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000013: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000014: struct<p
...
loat>>
child 0, points: list<item: float>
child 0, item: float
000118: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000119: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000120: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000121: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000122: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000123: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000124: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000125: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000126: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000127: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000128: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
000129: struct<points: list<item: float>>
child 0, points: list<item: float>
child 0, item: float
point_inst: int16
sample_body: int64
sample_geom: int64
sample_geom_name: binary
sample_local: list<item: float>
child 0, item: float
sample_region: binary
to
{'000000': {'points': List(Value('float32'), length=3)}, '000001': {'points': List(Value('float32'), length=3)}, '000002': {'points': List(Value('float32'), length=3)}, '000003': {'points': List(Value('float32'), length=3)}, '000004': {'points': List(Value('float32'), length=3)}, '000005': {'points': List(Value('float32'), length=3)}, '000006': {'points': List(Value('float32'), length=3)}, '000007': {'points': List(Value('float32'), length=3)}, '000008': {'points': List(Value('float32'), length=3)}, '000009': {'points': List(Value('float32'), length=3)}, '000010': {'points': List(Value('float32'), length=3)}, '000011': {'points': List(Value('float32'), length=3)}, '000012': {'points': List(Value('float32'), length=3)}, '000013': {'points': List(Value('float32'), length=3)}, '000014': {'points': List(Value('float32'), length=3)}, '000015': {'points': List(Value('float32'), length=3)}, '000016': {'points': List(Value('float32'), length=3)}, '000017': {'points': List(Value('float32'), length=3)}, '000018': {'points': List(Value('float32'), length=3)}, '000019': {'points': List(Value('float32'), length=3)}, '000020': {'points': List(Value('float32'), length=3)}, '000021': {'points': List(Value('float32'), length=3)}, '000022': {'points': List(Value('float32'), length=3)}, '000023': {'points': List(Value('float32'), length=3)}, '000024': {'points': List(Value('float32'), length=3)}, '000025': {'points': List(Value('float32'), length=3)}, '000026': {'points': List(Value('float32'),
...
'000115': {'points': List(Value('float32'), length=3)}, '000116': {'points': List(Value('float32'), length=3)}, '000117': {'points': List(Value('float32'), length=3)}, '000118': {'points': List(Value('float32'), length=3)}, '000119': {'points': List(Value('float32'), length=3)}, '000120': {'points': List(Value('float32'), length=3)}, '000121': {'points': List(Value('float32'), length=3)}, '000122': {'points': List(Value('float32'), length=3)}, '000123': {'points': List(Value('float32'), length=3)}, '000124': {'points': List(Value('float32'), length=3)}, '000125': {'points': List(Value('float32'), length=3)}, '000126': {'points': List(Value('float32'), length=3)}, '000127': {'points': List(Value('float32'), length=3)}, '000128': {'points': List(Value('float32'), length=3)}, '000129': {'points': List(Value('float32'), length=3)}, '000130': {'points': List(Value('float32'), length=3)}, '000131': {'points': List(Value('float32'), length=3)}, '000132': {'points': List(Value('float32'), length=3)}, '000133': {'points': List(Value('float32'), length=3)}, '000134': {'points': List(Value('float32'), length=3)}, '000135': {'points': List(Value('float32'), length=3)}, '000136': {'points': List(Value('float32'), length=3)}, '000137': {'points': List(Value('float32'), length=3)}, 'point_inst': Value('int16'), 'sample_body': Value('int64'), 'sample_geom': Value('int64'), 'sample_geom_name': Value('string'), 'sample_local': List(Value('float32'), length=3), 'sample_region': Value('string')}
because column names don't match
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
000000 dict | 000001 dict | 000002 dict | 000003 dict | 000004 dict | 000005 dict | 000006 dict | 000007 dict | 000008 dict | 000009 dict | 000010 dict | 000011 dict | 000012 dict | 000013 dict | 000014 dict | 000015 dict | 000016 dict | 000017 dict | 000018 dict | 000019 dict | 000020 dict | 000021 dict | 000022 dict | 000023 dict | 000024 dict | 000025 dict | 000026 dict | 000027 dict | 000028 dict | 000029 dict | 000030 dict | 000031 dict | 000032 dict | 000033 dict | 000034 dict | 000035 dict | 000036 dict | 000037 dict | 000038 dict | 000039 dict | 000040 dict | 000041 dict | 000042 dict | 000043 dict | 000044 dict | 000045 dict | 000046 dict | 000047 dict | 000048 dict | 000049 dict | 000050 dict | 000051 dict | 000052 dict | 000053 dict | 000054 dict | 000055 dict | 000056 dict | 000057 dict | 000058 dict | 000059 dict | 000060 dict | 000061 dict | 000062 dict | 000063 dict | 000064 dict | 000065 dict | 000066 dict | 000067 dict | 000068 dict | 000069 dict | 000070 dict | 000071 dict | 000072 dict | 000073 dict | 000074 dict | 000075 dict | 000076 dict | 000077 dict | 000078 dict | 000079 dict | 000080 dict | 000081 dict | 000082 dict | 000083 dict | 000084 dict | 000085 dict | 000086 dict | 000087 dict | 000088 dict | 000089 dict | 000090 dict | 000091 dict | 000092 dict | 000093 dict | 000094 dict | 000095 dict | 000096 dict | 000097 dict | 000098 dict | 000099 dict | 000100 dict | 000101 dict | 000102 dict | 000103 dict | 000104 dict | 000105 dict | 000106 dict | 000107 dict | 000108 dict | 000109 dict | 000110 dict | 000111 dict | 000112 dict | 000113 dict | 000114 dict | 000115 dict | 000116 dict | 000117 dict | 000118 dict | 000119 dict | 000120 dict | 000121 dict | 000122 dict | 000123 dict | 000124 dict | 000125 dict | 000126 dict | 000127 dict | 000128 dict | 000129 dict | 000130 dict | 000131 dict | 000132 dict | 000133 dict | 000134 dict | 000135 dict | 000136 dict | 000137 dict | point_inst int16 | sample_body int64 | sample_geom int64 | sample_geom_name string | sample_local list | sample_region string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
{
"points": [
-0.21302898228168488,
0.04925759881734848,
1.2861095666885376
]
} | {
"points": [
-0.2124105542898178,
0.04969707131385803,
1.2847239971160889
]
} | {
"points": [
-0.21051551401615143,
0.05054350569844246,
1.282711386680603
]
} | {
"points": [
-0.20719964802265167,
0.05150166153907776,
1.2804075479507446
]
} | {
"points": [
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]
} | {
"points": [
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]
} | {
"points": [
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} | {
"points": [
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]
} | {
"points": [
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]
} | {
"points": [
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]
} | {
"points": [
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]
} | {
"points": [
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]
} | {
"points": [
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]
} | {
"points": [
-0.1426951140165329,
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1.269084095954895
]
} | {
"points": [
-0.13743531703948975,
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1.2674506902694702
]
} | {
"points": [
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1.2656478881835938
]
} | {
"points": [
-0.12862645089626312,
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1.263665795326233
]
} | {
"points": [
-0.12484434247016907,
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1.261478304862976
]
} | {
"points": [
-0.12172186374664307,
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1.2592507600784302
]
} | {
"points": [
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]
} | {
"points": [
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]
} | {
"points": [
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1.2530018091201782
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} | {
"points": [
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} | {
"points": [
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]
} | {
"points": [
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} | {
"points": [
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} | {
"points": [
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} | {
"points": [
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} | {
"points": [
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]
} | {
"points": [
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} | {
"points": [
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} | {
"points": [
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} | {
"points": [
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]
} | {
"points": [
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} | {
"points": [
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} | {
"points": [
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]
} | {
"points": [
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]
} | {
"points": [
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]
} | {
"points": [
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]
} | {
"points": [
-0.11010514944791794,
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1.2067581415176392
]
} | {
"points": [
-0.10934479534626007,
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]
} | {
"points": [
-0.10838478803634644,
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]
} | {
"points": [
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]
} | {
"points": [
-0.10583741217851639,
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1.1965453624725342
]
} | {
"points": [
-0.10419774800539017,
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]
} | {
"points": [
-0.10218282043933868,
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]
} | {
"points": [
-0.09966573119163513,
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1.1899564266204834
]
} | {
"points": [
-0.09660786390304565,
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1.1879627704620361
]
} | {
"points": [
-0.09298180788755417,
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1.1861413717269897
]
} | {
"points": [
-0.08878545463085175,
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1.1845605373382568
]
} | {
"points": [
-0.08405239135026932,
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1.183440089225769
]
} | {
"points": [
-0.07886938750743866,
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1.182865023612976
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} | 0 | 12 | 71 | gripper0_hand_visual | [
-0.02278798073530197,
-0.024760954082012177,
-0.09129245579242706
] |
End of preview.
LIBERO-Goal mesh point clouds
Ground-truth 3D point clouds for all 500 demonstrations of the libero_goal suite, sampled from the simulator's object meshes and replayed against each demonstration's own recorded scene.
| files | 500 (10 tasks × 50 demos) |
| frames | 63,728 |
| points per frame | 4,096 = 8 objects × 512 |
| coordinates | world frame, metres, not normalised |
| size | 3.1 GB |
What makes this different
1. The same points, everywhere. Each object is sampled once and those same surface points are carried through every frame, every demo and every task by the object's current pose. Row i is permanently the same physical spot on the same object, so per-point motion and scene flow are computable. Verified: internal distances on a rigid object vary by <0.001 mm between frames, and a static fixture's points move 0.000 mm.
2. Fixture positions match the demonstration. Fixtures (cabinet, stove, wine rack) are
welded — their pose lives in model.body_pos, not qpos — so replaying a demo's states
does not restore them, and a plain env.reset() re-runs the placement sampler and puts
them somewhere else (measured: 15–29 mm off). Each demo here is rebuilt from its own
recorded model_file XML, so every object sits where it actually was.
This is easy to get wrong and silent when you do: the fixture point clouds end up decorrelated from the actions in the same file.
3. Articulation is handled. Points are stored against their own geom, so a cabinet drawer's points slide out with the drawer while the shell's stay put.
Verification
Points were compared against a dense, area-weighted sample of the true mesh surface taken live from the simulator, per object and per frame. The floor column is what the method reports on a known-correct input — the resolution limit — and every object sits on it:
| object | floor | measured |
|---|---|---|
cream_cheese_1 |
0.12 mm | 0.12 mm |
plate_1 |
0.20 mm | 0.20 mm |
akita_black_bowl_1 |
0.21 mm | 0.21 mm |
wine_bottle_1 |
0.22 mm | 0.22 mm |
flat_stove_1 |
0.29 mm | 0.29 mm |
wine_rack_1 |
0.63 mm | 0.62 mm |
wooden_cabinet_1 |
1.14 mm | 1.13 mm |
No detectable error. Floors differ per object because the same number of reference samples spread over a larger surface sit further apart.
File format
<task>/demo_<i>.h5
│
├── point_inst (4096,) int16 object index into instance_names
├── sample_local (4096, 3) float32 the chosen spot on the object, in its own frame
├── sample_geom (4096,) int64 which geom each point sits on
├── sample_geom_name (4096,) str e.g. "wooden_cabinet_1_g21"
├── sample_body (4096,) int64 which MuJoCo body
├── sample_region (4096,) str region covering that point, "" if none
│
├── 000000/points (4096, 3) float32 world coordinates, metres
├── 000001/points ...
└── ... one group per frame
Attributes: instance_names, ooi_names, n_frames, coord, correspondence,
geom_ids, geom_names, region_names, region_bodies, region_parents.
sample_* are stored once, not per frame — they are identical in all 500 files.
import h5py
with h5py.File("put_the_bowl_on_the_plate/demo_0.h5") as h:
names = [str(x) for x in h.attrs["instance_names"]]
pts = h["000042"]["points"][()] # (4096, 3) metres
lab = h["point_inst"][()]
bowl = pts[lab == names.index("akita_black_bowl_1")]
# the points a task is actually about
region = h["sample_region"][()]
target = pts[region == b"wooden_cabinet_1_middle_region"]
Objects
PandaGripper0, akita_black_bowl_1, cream_cheese_1, flat_stove_1, plate_1,
wine_bottle_1, wine_rack_1, wooden_cabinet_1 — 512 points each.
The robot arm and mount are excluded (--include-robot puts them back).
Known limitations
- The gripper samples its collision meshes as well as its visual ones. 231 of
PandaGripper0's 512 points sit on a simplified duplicate surface overlaid on the real one. Other objects are unaffected — their collision geometry is primitives, which are skipped. Fix would be to filter ongeom_group. flat_stove_1's base is missing. Its visual geometry is a primitive, and only mesh geoms are sampled, so the stove's points cover the burner but not the body.ooi_namesis inconsistent. Some entries are object names, some are raw region names (wooden_cabinet_1_middle_region). Use theregion_names/region_parentsattributes to resolve either form.- Complete geometry, not sensor-like. Points cover surfaces no camera could see. Good for supervision and shape priors; not a substitute for realistic partial depth if you intend to transfer to real hardware.
Reproducing
Requires the original LIBERO demonstrations (they carry the per-step states and the recorded scene XML):
hf download yifengzhu-hf/LIBERO-datasets --repo-type dataset \
--include "libero_goal/*" --local-dir ./libero_raw
MUJOCO_GL=egl python code/extract_mesh_points.py --all \
--demo-dir ./libero_raw/libero_goal --out-dir ./out
sampling_cache.npz is included and is loaded automatically — it defines which 512
spots are used per object. Delete it and you get a different (still self-consistent)
sampling; keep it to reproduce these files exactly.
Source
Derived from LIBERO
(Liu et al., 2023) and its libero_goal demonstrations.
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