Publish validated ViaCatalyst community LeRobot conversion

README.md

@@ -0,0 +1,128 @@
+---
+license: cc-by-4.0
+pretty_name: "MimicGen Square D0 — verified multimodal LeRobot v3 reference subset"
+task_categories:
+- robotics
+tags:
+- LeRobot
+- robotics
+- imitation-learning
+- offline-rl
+- multimodal
+- mimicgen
+- community-conversion
+- v3.0
+---
+
+# MimicGen Square D0 — verified multimodal LeRobot v3 reference subset
+
+[![Converted and validated with ViaCatalyst](https://img.shields.io/badge/Converted%20%26%20validated-ViaCatalyst-0F766E)](https://byod.viacatalyst.com)
+
+> 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`](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`](https://huggingface.co/datasets/amandlek/mimicgen_datasets)
+- Pinned source revision: [`33016f8a62c02334f929f2913af8fdd2a8a129e1`](https://huggingface.co/datasets/amandlek/mimicgen_datasets/tree/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`](provenance.json), [`bundle-manifest.json`](bundle-manifest.json), [`bundle-manifest.external.json`](bundle-manifest.external.json), and [`UPSTREAM_LICENSE.md`](UPSTREAM_LICENSE.md).
+
+## License and attribution
+
+The upstream MimicGen project states that its datasets are released under [`CC-BY 4.0`](https://huggingface.co/datasets/amandlek/mimicgen_datasets/blob/33016f8a62c02334f929f2913af8fdd2a8a129e1/README.md). 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
+
+```python
+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](https://byod.viacatalyst.com), 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:
+
+```bibtex
+@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}
+}
+```

UPSTREAM_LICENSE.md

@@ -0,0 +1,13 @@
+# Upstream license and attribution
+
+- License identifier: `cc-by-4.0`
+- Source dataset: `amandlek/mimicgen_datasets`
+- Source URL: https://huggingface.co/datasets/amandlek/mimicgen_datasets
+- Source revision: `33016f8a62c02334f929f2913af8fdd2a8a129e1`
+- License text/terms: https://huggingface.co/datasets/amandlek/mimicgen_datasets/blob/33016f8a62c02334f929f2913af8fdd2a8a129e1/README.md
+
+## Attribution
+
+Source data by amandlek/mimicgen_datasets; preserve its dataset card and citations.
+
+This file records upstream terms; the conversion does not relicense the source data.

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+          "shortestEpisodeFrames": 135
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+        "name": "episode_boundaries_and_timestamps",
+        "severity": "critical",
+        "status": "passed",
+        "title": "Episode boundaries and timestamps"
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+      "name": "mimicgen-square-d0",
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+        "id": "observation-state-outliers",
+        "message": "Some frames are more than six median absolute deviations from the feature median.",
+        "recommendation": "Inspect the affected signal for unit changes, resets, clipping, or corrupt samples.",
+        "severity": "medium",
+        "title": "observation.state contains robust outliers"
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+        "recommendation": "Inspect the affected signal for unit changes, resets, clipping, or corrupt samples.",
+        "severity": "medium",
+        "title": "action contains robust outliers"
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+    "limitations": [
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+      "Action saturation uses observed signal behavior unless hardware command limits are supplied separately.",
+      "Visual blur, exposure, and frozen-frame findings are heuristics and should be confirmed with representative episode review.",
+      "Output timestamp regularity is distinct from source synchronization; review the source alignment evidence."
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+    "summary": "The dataset is structurally valid, with quality signals that deserve review.",
+    "verdict": "review_recommended",
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+  "recommendations": [
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+}

videos/observation.images.agentview_image/chunk-000/file-000.mp4

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