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chomeed/mimicgen_square_d0_224x224

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… See the full description on the dataset page: https://huggingface.co/datasets/chomeed/mimicgen_square_d0_224x224.

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mimicgensquared0_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).

episodes1000
frames153477
fps20
robotPanda (OSCPOSE, controlfreq 20)
camerasagentview, eye_in_hand -- 224x224, AV1 crf 30
observation.state23 = 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 (eyeinhand) 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 live Square_D0.
  • —success == done == (reward >= 1.0).
  • —source_demo_index == episode_index -- the demo's index in the source hdf5.
  • —is_first / is_last / is_terminal mark 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.