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observation.images.image
image
observation.images.wrist_image
image
observation.state
list
action
list
timestamp
float32
frame_index
int64
episode_index
int64
index
int64
task_index
int64
[ -0.204423725605011, 0.0021315901540219784, 1.18168044090271, 3.139340877532959, 0.0005462145782075822, -0.08861229568719864, 0.038784466683864594, -0.03879138082265854 ]
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0
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0.1
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0
1
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0.2
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0.3
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0
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0.4
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0
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0.5
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0
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0.6
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0.7
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0.8
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0.9
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1
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0
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1.1
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1.2
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12
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1.3
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1.4
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0
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1.5
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1.6
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1.7
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17
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1.8
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1.9
19
0
19
0
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2
20
0
20
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2.1
21
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21
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2.2
22
0
22
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2.3
23
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2.4
24
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24
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2.5
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0
25
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2.6
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2.7
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27
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2.8
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2.9
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3
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0
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3.1
31
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3.2
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3.3
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3.4
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3.5
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3.6
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3.7
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3.8
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3.9
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4
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4.1
41
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4.2
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4.3
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4.4
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4.5
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4.6
46
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4.7
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4.8
48
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4.9
49
0
49
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5
50
0
50
0
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[ 0.3991071283817291, 0, 0.8464285731315613, 0, 0.1339285671710968, -0.07928571105003357, 1 ]
5.1
51
0
51
0
[ -0.04401601105928421, 0.15662053227424622, 0.9672099351882935, 3.1223835945129395, -0.14133523404598236, -0.014363263733685017, 0.002755102701485157, -0.0028089014813303947 ]
[ 0.5357142686843872, 0, 0.8705357313156128, 0, 0.11999999731779099, -0.08571428805589676, 1 ]
5.2
52
0
52
0
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[ 0.65625, 0, 0.8758928775787354, 0, 0.09214285761117935, -0.09214285761117935, 1 ]
5.3
53
0
53
0
[ -0.035462599247694016, 0.15578621625900269, 0.9871118664741516, 3.124990224838257, -0.17545701563358307, -0.03337826579809189, 0.0027265159878879786, -0.002779309405013919 ]
[ 0.675000011920929, 0, 0.862500011920929, 0, 0.09107142686843872, -0.08892857283353806, 1 ]
5.4
54
0
54
0
[ -0.029215989634394646, 0.15511037409305573, 0.9972696900367737, 3.126401424407959, -0.19307488203048706, -0.03993773087859154, 0.0027181399054825306, -0.002769679995253682 ]
[ 0.7098214030265808, 0.02678571455180645, 0.862500011920929, -0.006428571417927742, 0.06750000268220901, -0.08464285731315613, 1 ]
5.5
55
0
55
0
[ -0.0221725981682539, 0.15446938574314117, 1.0075569152832031, 3.1274821758270264, -0.20975424349308014, -0.04517538473010063, 0.0027117717545479536, -0.002761343726888299 ]
[ 0.7473214268684387, 0.0803571417927742, 0.7178571224212646, -0.023571427911520004, 0.029999999329447746, -0.07928571105003357, 1 ]
5.6
56
0
56
0
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[ 0.7982142567634583, 0.04821428656578064, 0.47410714626312256, 0, 0.02250000089406967, -0.06964285671710968, 1 ]
5.7
57
0
57
0
[ -0.005339990835636854, 0.1538519561290741, 1.0249046087265015, 3.1282923221588135, -0.23874010145664215, -0.04350002110004425, 0.0027030007913708687, -0.0027462018188089132 ]
[ 0.8678571581840515, 0.02678571455180645, 0.2571428716182709, 0.008571428246796131, 0.020357143133878708, -0.056785713881254196, 1 ]
5.8
58
0
58
0
[ 0.004031391814351082, 0.15399187803268433, 1.029475450515747, 3.129981279373169, -0.2513032853603363, -0.03914801776409149, 0.0026993025094270706, -0.0027401389088481665 ]
[ 0.9214285612106323, 0.03750000149011612, 0.09107142686843872, 0.008571428246796131, 0.012857142835855484, -0.04714285582304001, 1 ]
5.9
59
0
59
0
[ 0.01406165398657322, 0.15409600734710693, 1.031288504600525, 3.1323978900909424, -0.26207467913627625, -0.032887715846300125, 0.002696153474971652, -0.002734730252996087 ]
[ 0.9348214268684387, 0.02142857201397419, 0, 0.018214285373687744, 0.002142857061699033, -0.04500000178813934, 1 ]
6
60
0
60
0
[ 0.024562189355492592, 0.15418946743011475, 1.031179666519165, 3.135387420654297, -0.27187037467956543, -0.025187695398926735, 0.002693519229069352, -0.0027296009939163923 ]
[ 0.9267857074737549, 0.008035714738070965, -0.11517857015132904, 0.02250000089406967, 0, -0.04821428656578064, 1 ]
6.1
61
0
61
0
[ 0.03520019352436066, 0.15419790148735046, 1.0295789241790771, 3.138782024383545, -0.28198450803756714, -0.01719728484749794, 0.002690860303118825, -0.0027248093392699957 ]
[ 0.9053571224212646, 0, -0.30267858505249023, 0.03214285895228386, 0, -0.055714286863803864, 1 ]
6.2
62
0
62
0
[ 0.045724935829639435, 0.15414997935295105, 1.0260452032089233, 3.1427218914031982, -0.29311153292655945, -0.009625851176679134, 0.0026885210536420345, -0.002719840267673135 ]
[ 0.7982142567634583, 0, -0.6026785969734192, 0.06428571790456772, -0.02678571455180645, -0.07071428745985031, 1 ]
6.3
63
0
63
0
[ 0.05589243397116661, 0.15435652434825897, 1.0198076963424683, 3.148392915725708, -0.30639123916625977, -0.0024773990735411644, 0.002687061671167612, -0.0027140628080815077 ]
[ 0.3589285612106323, 0, -0.8892857432365417, 0.09857142716646194, -0.09321428835391998, -0.07178571075201035, 1 ]
6.4
64
0
64
0
[ 0.06438535451889038, 0.15501540899276733, 1.0110797882080078, 3.155733108520508, -0.3209089934825897, 0.00024225121887866408, 0.0026853049639612436, -0.002708184765651822 ]
[ -0.07232142984867096, 0.09107142686843872, -0.9375, 0.055714286863803864, -0.061071429401636124, -0.04714285582304001, 1 ]
6.5
65
0
65
0
[ 0.06934916973114014, 0.15587177872657776, 1.0011824369430542, 3.161029815673828, -0.33238592743873596, -0.008737549185752869, 0.002681987825781107, -0.00270308880135417 ]
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6.6
66
0
66
0
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6.7
67
0
67
0
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6.8
68
0
68
0
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[ -0.46071428060531616, 0.0803571417927742, -0.9375, 0, -0.10285714268684387, -0.02142857201397419, 1 ]
6.9
69
0
69
0
[ 0.06775528937578201, 0.16113968193531036, 0.9658618569374084, 3.152104377746582, -0.33965280652046204, -0.07039837539196014, 0.0026752206031233072, -0.0026830618735402822 ]
[ -0.47678571939468384, 0.03482142835855484, -0.9375, 0, -0.08892857283353806, -0.02678571455180645, 1 ]
7
70
0
70
0
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[ -0.5544642806053162, 0, -0.9375, 0.010714286006987095, -0.07285714149475098, -0.019285714253783226, 1 ]
7.1
71
0
71
0
[ 0.0627114325761795, 0.16348572075366974, 0.9468700885772705, 3.144453287124634, -0.34531307220458984, -0.08171396702528, 0.002672238741070032, -0.0026785379741340876 ]
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7.2
72
0
72
0
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7.3
73
0
73
0
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[ -0.5544642806053162, -0.0535714291036129, -0.7955357432365417, 0.023571427911520004, -0.05999999865889549, 0, 1 ]
7.4
74
0
74
0
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7.5
75
0
75
0
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7.6
76
0
76
0
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7.7
77
0
77
0
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7.8
78
0
78
0
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[ 0, -0.14196428656578064, 0.3348214328289032, 0.010714286006987095, 0.027857143431901932, -0.0835714265704155, -1 ]
7.9
79
0
79
0
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[ 0, -0.14196428656578064, 0.5571428537368774, 0.025714285671710968, 0.05999999865889549, -0.09428571164608002, -1 ]
8
80
0
80
0
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[ 0, -0.11249999701976776, 0.6910714507102966, 0.039642855525016785, 0.07178571075201035, -0.09428571164608002, -1 ]
8.1
81
0
81
0
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8.2
82
0
82
0
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8.3
83
0
83
0
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0
0
1
84
0
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[ 0.8089285492897034, 0.4151785671710968, 0.22232143580913544, -0.035357143729925156, 0.06964285671710968, 0, -1 ]
0.1
1
1
85
0
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[ 0.8892857432365417, 0.4446428716182709, 0.15803571045398712, -0.031071428209543228, 0.035357143729925156, 0, -1 ]
0.2
2
1
86
0
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0.3
3
1
87
0
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0.4
4
1
88
0
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[ 0.9375, 0.49017858505249023, 0.0053571430034935474, -0.004285714123398066, 0.04392857104539871, 0, -1 ]
0.5
5
1
89
0
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[ 0.9375, 0.46875, 0, 0, 0.03857142850756645, 0, -1 ]
0.6
6
1
90
0
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[ 0.9375, 0.43392857909202576, -0.02678571455180645, 0, 0.03750000149011612, 0, -1 ]
0.7
7
1
91
0
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0.8
8
1
92
0
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[ 0.9375, 0.4124999940395355, -0.10446428507566452, 0, 0.04928571358323097, 0, -1 ]
0.9
9
1
93
0
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1
10
1
94
0
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[ 0.9375, 0.3910714387893677, -0.19285714626312256, 0, 0.04821428656578064, 0, -1 ]
1.1
11
1
95
0
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[ 0.9375, 0.3857142925262451, -0.21696428954601288, 0, 0.04928571358323097, 0, -1 ]
1.2
12
1
96
0
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[ 0.9375, 0.3776785731315613, -0.3187499940395355, 0, 0.046071428805589676, 0, -1 ]
1.3
13
1
97
0
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[ 0.9375, 0.3616071343421936, -0.4848214387893677, 0.014999999664723873, 0.039642855525016785, 0, -1 ]
1.4
14
1
98
0
[ -0.04244600236415863, 0.08537334203720093, 1.157489538192749, 3.1374764442443848, 0.005368659272789955, -0.07855274528265, 0.03945351392030716, -0.03935915231704712 ]
[ 0.9375, 0.30267858505249023, -0.6776785850524902, 0.04500000178813934, 0.028928572311997414, 0, -1 ]
1.5
15
1
99
0
End of preview. Expand in Data Studio

LIBERO Spatial Image — LIBERO Task 0

This is a single-task subset derived from lerobot/libero_spatial_image. Its name follows the canonical task order of the LIBERO benchmark used at runtime by verl-vla.

The selected task is LIBERO Spatial task_id=0:

Pick up the black bowl between the plate and the ramekin and place it on the plate.

In the upstream LeRobot dataset's local task table, the same task is stored as task_index=4. The numeric IDs differ because the upstream dataset and LIBERO benchmark use different task-table orderings.

Dataset summary

  • Format: LeRobot v3.0
  • Robot: Panda
  • Frequency: 10 FPS
  • Episodes: 45
  • Frames: 4,487
  • Tasks: 1
  • Canonical LIBERO task ID: 0
  • Upstream dataset-local task index: 4
  • Observations: agent-view image, wrist image, and 8-dimensional robot state
  • Actions: 7-dimensional continuous action

Derivation and validation

All upstream episodes whose task description exactly matches the LIBERO task-0 description were selected. Observation and action values were copied without modification, while episode, frame, sample, and dataset-local task indices were rebuilt into a contiguous single-task LeRobot dataset.

Images are losslessly encoded as PNG data. The first extracted episode was checked for exact tensor equality against its source episode for both images, state, and action. Global image mean and standard deviation were recomputed directly from all 4,487 decoded frames because the installed LeRobot version's per-episode image-statistics aggregation produced invalid near-zero standard deviations during subset creation.

This is a derived subset, not an independently collected dataset. Refer to the upstream dataset and the LIBERO project for the original collection and benchmark details.

Loading with LeRobot

from lerobot.datasets.lerobot_dataset import LeRobotDataset

dataset = LeRobotDataset("Miical/libero_spatial_image_task0")

License and attribution

The upstream dataset is published under the Apache-2.0 license. This derived subset retains that license. Please credit the upstream LeRobot dataset and LIBERO when using it.

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