ViaCatalyst/mimicgen-square-d0-lerobot-v3

MimicGen Square D0 — verified multimodal LeRobot v3 reference subset

Community conversion produced by ViaCatalyst BYOD. This repository is not an official upstream release and is not affiliated with the MimicGen authors.

This is a compact, provenance-complete conversion of the first 10 episodes from the pinned MimicGen Square D0 core HDF5 file. It provides a reproducible multimodal LeRobot v3 reference dataset and conversion-quality example.

At a glance

Property	Value
LeRobot format	v3.0
Robot	Panda
Task	Assemble the square nut on its matching peg
Episodes	10
Frames	1,444
Duration	72.20 seconds
FPS	20
Observation modalities	State + 2 RGB camera streams
RGB streams	agentview_image, robot0_eye_in_hand_image
Image resolution	84 × 84 × 3, H.264
Action / state dimension	7 / 59
Official LeRobot reader	Passed with LeRobot 0.6.0

Features and source mapping

LeRobot feature	dtype	shape	Source mapping
action	float32	[7]	Direct per-frame copy from each demonstration's actions dataset, with a float32 cast only
observation.state	float32	[59]	Deterministic concatenation of numeric obs/* vectors; names are documented in meta/info.json
observation.images.agentview_image	video	[84, 84, 3]	Aligned RGB frames from obs/agentview_image, encoded H.264 at 20 FPS
observation.images.robot0_eye_in_hand_image	video	[84, 84, 3]	Aligned RGB frames from obs/robot0_eye_in_hand_image, encoded H.264 at 20 FPS
episode_index / frame_index	int64	[1]	Preserved HDF5 episode boundaries and zero-based frame positions
timestamp	float32	[1]	frame_index / 20 seconds
task_index	int64	[1]	Maps to the Square task in meta/tasks.parquet

Original-action preservation

The conversion reads the original actions array for every selected episode and writes each row directly to action. It does not replay a learned policy, regenerate actions, interpolate action values, or relabel demonstrations. The two camera streams are retained only when aligned to their episode frames; output timestamps are normalized to the declared 20 FPS.

Validation evidence

The complete machine-readable evidence is in validation-report.json. All eight critical automated checks passed:

• Dataset metadata counts
• Parquet schema and frame count
• Episode boundaries and timestamp regularity
• Feature dimensions and finite values
• LeRobot v3 relational metadata
• Video-frame alignment
• License and provenance completeness
• Official LeRobot reader smoke test

The readiness score is 84/100 — Review recommended. Two medium-confidence statistical signals are disclosed: observation.state has an 84.76% robust-outlier frame rate and action has a 4.85% rate. These are robust distribution signals, not proof of corruption; review the feature-level evidence before training.

Source, revision, and integrity

• Source dataset: amandlek/mimicgen_datasets
• Pinned source revision: 33016f8a62c02334f929f2913af8fdd2a8a129e1
• Source file: core/square_d0.hdf5
• Source file size: 1,621,351,476 bytes
• Source SHA-256: 41fc24bce0f88343099c0b1b5bf6eee08cbc35851e71276d4509a01c9b75481c
• Converter adapter: mimicgen adapter 1.0.0
• Converter code revision: 4230bc4b56abe85116b202398b1a625a81c1c55c

Additional audit files: provenance.json, bundle-manifest.json, bundle-manifest.external.json, and UPSTREAM_LICENSE.md.

License and attribution

The upstream MimicGen project states that its datasets are released under CC-BY 4.0. This conversion retains that identifier, attribution, and citation. Conversion does not transfer ownership, create affiliation, or replace upstream terms.

Intended use

• Testing multimodal LeRobot v3 readers, video handling, and data pipelines
• Small offline imitation-learning or educational experiments
• Reproducible HDF5-to-LeRobot conversion evaluation
• Comparing schema, provenance, and validation tooling across state and camera streams

Limitations

• This is a community conversion, not an official upstream release.
• It contains only the first 10 episodes from the pinned Square D0 core file, not the complete MimicGen corpus or full Square D0 split.
• It retains only adapter-recognized state, action, and RGB streams; inspect meta/info.json before training.
• Statistical quality signals require domain-aware review before training.
• Automated validation does not measure policy performance, simulation transfer, or task success.

Load with LeRobot

from lerobot.datasets.lerobot_dataset import LeRobotDataset

dataset = LeRobotDataset("ViaCatalyst/mimicgen-square-d0-lerobot-v3")
print(dataset.meta.total_episodes, dataset.meta.total_frames)

Conversion tooling

Converted and validated with the ViaCatalyst BYOD Processing Platform, a free workflow for converting robotics datasets to LeRobot format. For high-volume datasets, contact ViaCatalyst support through the platform.

Citation

Please cite the original MimicGen work:

@inproceedings{mandlekar2023mimicgen,
  title={MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations},
  author={Mandlekar, Ajay and Nasiriany, Soroush and Wen, Bowen and Akinola, Iretiayo and Narang, Yashraj and Fan, Linxi and Zhu, Yuke and Fox, Dieter},
  booktitle={7th Annual Conference on Robot Learning},
  year={2023}
}