chomeed/mimicgen_hammer_cleanup_d0_224x224

mimicgenhammercleanupd0224x224

MimicGen HammerCleanup_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_hammer_cleanup_d1_224x224: same task, fixed (non-randomised) cabinet placement.

Provenance

Built from NVIDIA's released core/hammer_cleanup_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 HammerCleanup_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 1.95 (agentview) and 1.76 (eyeinhand) out of 255, versus 95.3 / 85.1 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 (37) = concat(robot0_eef_pos, robot0_eef_quat, robot0_gripper_qpos, object), i.e. 9 proprioceptive dims followed by 28 privileged object dims. Slicing to the leading 9 gives a proprioception-only policy input.
• —observation.sim_state (34) replays into a live HammerCleanup_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.