Search is not available for this dataset
action listlengths 7 7 | observation.state listlengths 23 23 | observation.sim_state listlengths 45 45 | reward float32 0 1 | done bool 2
classes | success bool 2
classes | is_first bool 2
classes | is_last bool 2
classes | is_terminal bool 2
classes | source_demo_index int64 0 999 | observation.object listlengths 14 14 | observation.robot0_eef_pos listlengths 3 3 | observation.robot0_eef_quat listlengths 4 4 | observation.robot0_eef_vel_ang listlengths 3 3 | observation.robot0_eef_vel_lin listlengths 3 3 | observation.robot0_gripper_qpos listlengths 2 2 | observation.robot0_gripper_qvel listlengths 2 2 | observation.robot0_joint_pos listlengths 7 7 | observation.robot0_joint_pos_cos listlengths 7 7 | observation.robot0_joint_pos_sin listlengths 7 7 | observation.robot0_joint_vel listlengths 7 7 | timestamp float32 0 8.55 | frame_index int64 0 171 | episode_index int64 0 999 | index int64 0 153k | task_index int64 0 0 |
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] | 2.9 | 58 | 0 | 58 | 0 |
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mimicgen_square_d0_224x224
MimicGen Square_D0 demonstrations in LeRobot v3 format, with both cameras rendered at
224x224. Same pipeline and conventions as chomeed/mimicgen_coffee_d1_224x224. Companion to chomeed/mimicgen_square_d1_224x224: same task with fixed peg placement, and a 14-dim object block versus D1's 17 (D1 adds the peg pose because its peg moves).
| episodes | 1000 |
| frames | 153477 |
| fps | 20 |
| robot | Panda (OSC_POSE, control_freq 20) |
| cameras | agentview, eye_in_hand -- 224x224, AV1 crf 30 |
observation.state |
23 = 9 proprioceptive + 14 privileged object dims |
Provenance
Built from NVIDIA's released core/square_d0.hdf5 (amandlek/mimicgen_datasets). That file
already contains every low-dim observation, but its images are only 84x84, so only the cameras
were recomputed: each frame's recorded states vector is written back into a live
Square_D0 and both views are re-rendered at 224x224. Every other column is copied verbatim
from the source hdf5, so this is a re-render, not a re-simulation, and no dynamics were replayed.
Fidelity check: re-rendering demo 0 at the source's own 84x84 and diffing against its stored images gives mean |difference| of 2.32 (agentview) and 1.57 (eye_in_hand) out of 255, versus 73.3 / 84.7 for a vertically flipped comparison. The small residual is expected -- the originals were rendered on a different OpenGL stack.
Schema
Follows the conventions of chomeed/mimicgen_coffee_d0_224x224:
observation.state(23) =concat(robot0_eef_pos, robot0_eef_quat, robot0_gripper_qpos, object), i.e. 9 proprioceptive dims followed by 14 privileged object dims. Slicing to the leading 9 gives a proprioception-only policy input.observation.sim_state(45) replays into a liveSquare_D0.success == done == (reward >= 1.0).source_demo_index == episode_index-- the demo's index in the source hdf5.is_first/is_last/is_terminalmark only the first and last frame of an episode.
Column widths are task-specific: coffee carries a 57-dim object block plus *_rel_pod keys,
square a 17-dim block with no rel_* keys.
The robot is read from the source env_args: Panda.
License
cc-by-4.0, inherited from the MimicGen datasets this is derived from.
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