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action
sequencelengths 6
6
| observation.state
sequencelengths 6
6
| timestamp
float64 0
7.77
| task_index
int64 0
3
| episode_index
int64 0
131
| frame_index
int64 0
233
| index
int64 0
15.8k
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1.399999976158142,
1.2044689655303955,
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| 2
| 87
|
[
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[
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| 3
| 88
|
[
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[
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| 4
| 89
|
[
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1.399999976158142,
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[
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1.399999976158142,
1.2044689655303955,
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| 5
| 90
|
[
0.07671777158975601,
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1.399999976158142,
1.2044689655303955,
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[
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1.399999976158142,
1.2044689655303955,
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| 0
| 1
| 6
| 91
|
[
0.07671777158975601,
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1.399999976158142,
1.2044689655303955,
-0.009206132031977177,
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[
0.07671777158975601,
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1.399999976158142,
1.2044689655303955,
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| 7
| 92
|
[
0.07671777158975601,
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1.399999976158142,
1.2044689655303955,
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[
0.07671777158975601,
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1.399999976158142,
1.2044689655303955,
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| 0
| 1
| 8
| 93
|
[
0.07825212180614471,
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1.399999976158142,
1.2044689655303955,
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[
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1.399999976158142,
1.2044689655303955,
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| 1
| 9
| 94
|
[
0.07978647947311401,
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1.399999976158142,
1.2044689655303955,
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[
0.07825212180614471,
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1.399999976158142,
1.2044689655303955,
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| 0
| 1
| 10
| 95
|
[
0.07978647947311401,
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1.399999976158142,
1.2044689655303955,
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[
0.07978647947311401,
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1.399999976158142,
1.2044689655303955,
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] | 0.366667
| 0
| 1
| 11
| 96
|
[
0.07978647947311401,
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1.399999976158142,
1.2044689655303955,
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[
0.07978647947311401,
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1.399999976158142,
1.2044689655303955,
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] | 0.4
| 0
| 1
| 12
| 97
|
[
0.07978647947311401,
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1.399999976158142,
1.2044689655303955,
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[
0.07978647947311401,
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1.399999976158142,
1.2044689655303955,
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] | 0.433333
| 0
| 1
| 13
| 98
|
[
0.07978647947311401,
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1.399999976158142,
1.2044689655303955,
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[
0.07978647947311401,
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1.399999976158142,
1.2044689655303955,
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] | 0.466667
| 0
| 1
| 14
| 99
|
End of preview. Expand
in Data Studio
so101_poker_play_train
This dataset was generated using a phospho starter pack.
This dataset contains a series of episodes recorded with a robot and multiple cameras. It can be directly used to train a policy using imitation learning. It's compatible with LeRobot and RLDS.
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