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episode_index int64 | frame_index int64 | timestamp float64 | observation.state list | observation.images.wrist_camera list | action list | next.done bool | next.success bool |
|---|---|---|---|---|---|---|---|
0 | 0 | 1,756,985,654.367622 | [
-0.8284049891306783,
0.8285689823292257,
-0.5219825100777444,
0.374628804275318,
0.015
] | [[[99,156,145,180,112,12,14,231,194,157,104,35,52,213,215,164,216,113,230,20,163,214,37,197,252,155,(...TRUNCATED) | [
-0.8284049891306783,
0.8285689823292257,
-0.5219825100777444,
0.374628804275318,
-0.008
] | false | false |
0 | 1 | 1,756,985,707.687945 | [
0.052296572764115666,
0.4891757512320937,
-0.5223523913625822,
0.49116783586801077,
-0.008
] | [[[134,48,225,72,128,207,206,195,184,168,41,7,37,21,61,139,250,161,60,221,194,149,205,134,27,147,196(...TRUNCATED) | [
0.052296572764115666,
0.4891757512320937,
-0.5223523913625822,
0.49116783586801077,
-0.008
] | true | true |
1 | 0 | 1,756,985,707.894384 | [
1.44751233963988,
0.934394895039403,
-1.193992701506525,
-0.17430933134866822,
0.015
] | [[[122,154,136,5,79,51,227,50,167,8,134,61,145,5,143,1,64,223,59,33,23,212,17,23,110,30,166,195,89,7(...TRUNCATED) | [
1.44751233963988,
0.934394895039403,
-1.193992701506525,
-0.17430933134866822,
-0.008
] | false | false |
1 | 1 | 1,756,985,760.511876 | [
-0.01447167071245696,
0.5002410080054963,
-0.5512414162536847,
0.4631251583266947,
-0.008
] | [[[130,137,34,34,14,37,189,19,155,82,184,29,129,123,131,128,184,4,222,251,251,42,32,236,135,236,84,2(...TRUNCATED) | [
-0.01447167071245696,
0.5002410080054963,
-0.5512414162536847,
0.4631251583266947,
-0.008
] | true | true |
2 | 0 | 1,756,985,760.712713 | [
0.9837274492538963,
0.8865550165402563,
-1.3360165460402447,
0.033187491600339736,
0.015
] | [[[172,252,14,231,29,133,235,3,146,39,180,189,229,89,12,174,247,202,191,252,46,82,102,242,29,97,29,1(...TRUNCATED) | [
0.9837274492538963,
0.8865550165402563,
-1.3360165460402447,
0.033187491600339736,
-0.008
] | false | false |
2 | 1 | 1,756,985,813.270234 | [
0.028361721765865846,
0.4376105207199528,
-0.5135764001119657,
0.5121118798165794,
-0.008
] | [[[39,84,14,98,241,76,40,231,152,179,14,205,104,32,141,127,112,41,134,216,144,137,95,254,92,96,24,21(...TRUNCATED) | [
0.028361721765865846,
0.4376105207199528,
-0.5135764001119657,
0.5121118798165794,
-0.008
] | true | true |
3 | 0 | 1,756,985,813.485739 | [
-1.0310367219996235,
0.8384472305087483,
-0.5364811162994185,
0.2432995405185896,
0.015
] | [[[105,241,167,62,49,22,104,251,161,57,112,185,235,32,63,171,188,229,251,112,7,198,7,174,93,113,41,2(...TRUNCATED) | [
-1.0310367219996235,
0.8384472305087483,
-0.5364811162994185,
0.2432995405185896,
-0.008
] | false | false |
3 | 1 | 1,756,985,866.151615 | [
0.007525809858182676,
0.47291991029918706,
-0.5403821632932315,
0.47937817866763405,
-0.008
] | [[[185,149,194,88,98,200,168,219,81,53,23,174,37,168,0,76,60,68,121,177,207,131,54,75,215,49,224,160(...TRUNCATED) | [
0.007525809858182676,
0.47291991029918706,
-0.5403821632932315,
0.47937817866763405,
-0.008
] | true | true |
4 | 0 | 1,756,985,866.327761 | [
1.1424379684886268,
0.9860272309863773,
-1.0483232576375874,
0.6037781978038539,
0.015
] | [[[24,0,199,170,124,201,195,162,122,221,92,41,52,240,159,16,92,145,151,122,242,215,254,132,227,178,5(...TRUNCATED) | [
1.1424379684886268,
0.9860272309863773,
-1.0483232576375874,
0.6037781978038539,
-0.008
] | false | false |
4 | 1 | 1,756,985,919.098191 | [
-0.0024413800095626553,
0.5022794588792199,
-0.5560174040803949,
0.4584557844165408,
-0.008
] | [[[203,113,33,234,232,100,197,1,149,106,28,124,245,99,240,103,63,135,220,111,71,67,217,220,251,69,39(...TRUNCATED) | [
-0.0024413800095626553,
0.5022794588792199,
-0.5560174040803949,
0.4584557844165408,
-0.008
] | true | true |
OpenManipulator-X Dataset for SmolVLA Fine-tuning
This dataset contains demonstrations for the OpenManipulator-X 5-DOF robot arm.
Dataset Details
- Robot: OpenManipulator-X (5-DOF)
- Camera: Single RGB+Depth (4-channel)
- Task: Random object manipulation/grasping
- Format: LeRobot v2.1 (Parquet + metadata)
Usage
from lerobot.datasets.lerobot_dataset import LeRobotDataset
dataset = LeRobotDataset("Hotteok/openmanipulator_test_5ep_complete")
Training
lerobot-train \
--policy.type smolvla \
--dataset.repo_id Hotteok/openmanipulator_test_5ep_complete \
--policy.max_state_dim 5 \
--policy.max_action_dim 5
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