| # Data format |
|
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| ## Episode files and indexes |
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| Episodes are grouped by robot, task family, and task configuration: |
|
|
| ```text |
| <robot>/<family>/<case>/ |
| dataset/ |
| episode_XXXX.h5 |
| meta/episode.jsonl |
| meta/randomization_episodes.jsonl |
| resolved_config.yaml |
| results/ |
| ``` |
|
|
| - `meta/episodes.jsonl` lists episodes, unique `episode_id` values, H5 paths, instructions, and associated files. |
| - `meta/cases.jsonl` lists task configurations and their metadata files. |
| - `meta/info.json` contains dataset information and current statistics. |
|
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| Index paths are relative to the dataset root. Episode numbers are local to each task configuration and may be non-consecutive. Use the global index to enumerate files. |
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| For associated annotations, match `hdf5_path` or `meta.episode_index` in randomization records and `h5_episode_index` in result records. Task configurations are available as `resolved_config.yaml`. |
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| ## H5 fields |
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| Read array shapes, column names, camera names, and frame rate from each file. Below, `T` is the frame count, `D` the selected joint-state dimension, `J` the full joint-state dimension, `K` the object count, `C` the camera count, and `S` the subgoal count. |
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| | Field | Description | |
| |---|---| |
| | `agent_pose` | `(T, D)` joint states; columns are described by `agent_pose_names` and the associated index arrays. | |
| | `actions` | `(T, D)` joint-position targets. | |
| | `joint_positions` | `(T, J)` joint states, with columns described by `joint_position_names`. | |
| | `ee_pose`, `ee_pose_valid` | End-effector poses and validity flags; see `ee_pose_names` and `ee_frame`. | |
| | `camera_*_rgb` | One-dimensional `uint8` arrays containing H.264 MP4 video bytes. | |
| | `language_instruction`, `subtask_instructions` | Episode and subtask instructions. | |
| | `step_index` | `(T,)` workflow-stage indices; `-1` marks transition frames. | |
| | `object_positions`, `object_orientations`, `object_names` | Object poses and names. Quaternion order is given by the `quaternion_order` attribute. | |
| | `bboxes_2d`, `bbox_visibility`, `bbox_camera_names` | `(T, K, C, 4)` image-space boxes, visibility flags, and camera-axis names. | |
| | `subgoals/frame_idx`, `subgoals/camera_names`, `subgoals/images_png` | Zero-based frame indices, camera names, and an `(S, C)` grid of PNG byte arrays. | |
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| `actions[t]` contains the next recorded joint state; the final target is the measured state at episode end. Read the column names and gripper indices when interpreting joint values. |
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| Video bytes must be decoded before accessing images. OpenCV returns BGR images; convert them to RGB before use. Use the H5 `fps` and `frame_count` attributes for timing and length. |
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| ## Read an episode |
|
|
| ```python |
| import json |
| from pathlib import Path |
| |
| import h5py |
| |
| root = Path(".") |
| with (root / "meta/episodes.jsonl").open() as index: |
| item = json.loads(next(index)) |
| |
| with h5py.File(root / item["hdf5_path"], "r") as episode: |
| states = episode["agent_pose"][()] |
| actions = episode["actions"][()] |
| instruction = episode["language_instruction"].asstr()[()] |
| ``` |
|
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| For an optional LeRobot export with video decoding, see [convert_to_lerobot.py](../examples/convert_to_lerobot.py) and the command in the [README](../README.md). |
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