Upload LIBERO logical state aligned dataset

.gitattributes

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README.md

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+---
+license: other
+task_categories:
+- robotics
+- imitation-learning
+tags:
+- libero
+- robotics
+- hdf5
+- logical-state
+- manipulation
+pretty_name: LIBERO Logical State and Action Trajectories
+size_categories:
+- 1K<n<10K
+---
+
+# LIBERO Logical State and Action Trajectories
+
+This repository contains LIBERO robot manipulation trajectories augmented with per-frame logical state and logical action annotations.
+
+The data is stored as HDF5 files under `datasets/`. Each suite has one directory, and each task has one HDF5 file containing multiple demonstrations.
+
+## Recommended Hugging Face Layout
+
+Keep the repository organized like this:
+
+```text
+.
+├── README.md
+├── requirements.txt
+├── visualize_dataset.py
+└── datasets/
+    ├── libero_10/
+    │   └── *_demo.hdf5
+    ├── libero_90/
+    │   └── *_demo.hdf5
+    ├── libero_goal/
+    │   └── *_demo.hdf5
+    ├── libero_object/
+    │   └── *_demo.hdf5
+    └── libero_spatial/
+        └── *_demo.hdf5
+```
+
+Use Git LFS for the HDF5 data files. The included `.gitattributes` marks `*.hdf5` files for LFS storage.
+
+Hugging Face can host this layout directly as a dataset repository. Because the trajectories are HDF5 robot data rather than CSV/JSONL/Parquet rows, the Hub's automatic dataset viewer may not render the contents directly. Use `visualize_dataset.py` for interactive inspection.
+
+## Dataset Contents
+
+After filtering trajectories without logical annotations, the dataset contains:
+
+| Suite | HDF5 files | Demonstrations |
+|---|---:|---:|
+| `libero_10` | 10 | 497 |
+| `libero_90` | 89 | 4429 |
+| `libero_goal` | 10 | 499 |
+| `libero_object` | 10 | 500 |
+| `libero_spatial` | 10 | 500 |
+| **Total** | **129** | **6425** |
+
+Each HDF5 task file follows this structure:
+
+```text
+data/
+  demo_0/
+    actions
+    dones
+    rewards
+    robot_states
+    states
+    logical_actions
+    logical_states
+    obs/
+      agentview_rgb
+      eye_in_hand_rgb
+      ee_pos
+      ee_ori
+      ee_states
+      gripper_states
+      joint_states
+    logical/
+      frame_indices
+      states
+      actions
+  demo_1/
+  ...
+```
+
+The top-level `data` group also stores task metadata in HDF5 attributes such as `problem_info`, `env_args`, `env_name`, `num_demos`, and `total`.
+
+## Per-Frame Schema
+
+For a frame index `i` in `data/demo_N`, the aligned per-frame fields are:
+
+| Field | Shape per frame | Description |
+|---|---:|---|
+| `actions[i]` | `(7,)` | Continuous robot action vector. |
+| `dones[i]` | scalar | Episode terminal flag. |
+| `rewards[i]` | scalar | Reward value. |
+| `robot_states[i]` | `(9,)` | Robot state vector. |
+| `states[i]` | variable by task | Full simulator state vector. |
+| `obs/agentview_rgb[i]` | `(128, 128, 3)` | Third-person RGB observation. |
+| `obs/eye_in_hand_rgb[i]` | `(128, 128, 3)` | Wrist camera RGB observation. |
+| `obs/ee_pos[i]` | `(3,)` | End-effector position. |
+| `obs/ee_ori[i]` | `(3,)` | End-effector orientation. |
+| `obs/ee_states[i]` | `(6,)` | Concatenated end-effector state. |
+| `obs/gripper_states[i]` | `(2,)` | Gripper state. |
+| `obs/joint_states[i]` | `(7,)` | Robot joint state. |
+| `logical_actions[i]` | string | Logical action aligned to this raw frame. |
+| `logical_states[i]` | JSON string | Logical predicates aligned to this raw frame. |
+
+The `logical/` subgroup preserves the original synced logical arrays:
+
+| Field | Description |
+|---|---|
+| `logical/frame_indices` | Raw frame indices corresponding to the synced logical state frames. |
+| `logical/states` | Exact logical state strings copied from `synced_final`. |
+| `logical/actions` | Exact logical action strings copied from `synced_final`. |
+
+`logical_states` and `logical_actions` at the demo root are convenience arrays with the same length as the raw trajectory. Terminal frames are forward-filled from the last available logical value when the source logical action array is shorter than the raw frame sequence.
+
+## Reading the Data
+
+Minimal Python example:
+
+```python
+import json
+import h5py
+
+path = "datasets/libero_10/KITCHEN_SCENE3_turn_on_the_stove_and_put_the_moka_pot_on_it_demo.hdf5"
+
+with h5py.File(path, "r") as f:
+    demo = f["data/demo_0"]
+    frame = 10
+
+    agentview = demo["obs/agentview_rgb"][frame]
+    eye_in_hand = demo["obs/eye_in_hand_rgb"][frame]
+    robot_action = demo["actions"][frame]
+    logical_action = demo["logical_actions"][frame].decode("utf-8")
+    logical_state = json.loads(demo["logical_states"][frame].decode("utf-8"))
+
+    print(logical_action)
+    print(logical_state)
+    print(robot_action)
+    print(agentview.shape, eye_in_hand.shape)
+```
+
+## Visualization App
+
+The repository includes a browser-based HDF5 reader with no web framework dependency. It uses Python's standard HTTP server plus `h5py`, `numpy`, and `Pillow`.
+
+![LIBERO dataset viewer showing RGB observations, logical state, logical action, and robot action values.](data_reader_example.png)
+
+Install dependencies:
+
+```bash
+python3 -m pip install -r requirements.txt
+```
+
+Run the viewer:
+
+```bash
+python3 visualize_dataset.py --host 127.0.0.1 --port 8000
+```
+
+By default, the viewer looks for `datasets/` next to `visualize_dataset.py`, so it still works if the repository folder is renamed. Use `--datasets-dir /path/to/datasets` only when the data is stored elsewhere.
+
+Path note: keep `visualize_dataset.py` and `datasets/` in the same repository root when possible. If you move the HDF5 files, pass the new dataset directory explicitly:
+
+```bash
+python3 visualize_dataset.py --datasets-dir /absolute/path/to/datasets --host 127.0.0.1 --port 8000
+```
+
+Open:
+
+```text
+http://127.0.0.1:8000
+```
+
+The app supports suite, task, demo, and frame selection, playback controls, both RGB camera streams, logical action, formatted logical predicates, and robot action/state values.
+
+## Data Processing Notes
+
+The logical labels were merged from files named like:
+
+```text
+synced_final/{suite}_{task_id}_{demo_id}_pairs.hdf5
+```
+
+into the corresponding HDF5 files under `datasets/{suite}/`. The merge script validates task-file correspondence using RGB frame equality before writing logical fields.
+
+The current dataset has already been merged and filtered. Demos without logical annotations were removed, remaining demos were renumbered contiguously, and `num_demos` / `total` attributes were updated.
+
+## Intended Use
+
+This dataset is intended for research on robot manipulation, imitation learning, planning-conditioned policies, language/logical-state grounding, and analysis of action/state abstractions in LIBERO demonstrations.
+
+## Limitations
+
+- The logical annotations are aligned to existing rendered/simulator frames and should be treated as derived labels.
+- HDF5 files are not automatically previewable in the Hugging Face dataset viewer like tabular formats.
+- Users should verify compatibility with their downstream LIBERO or imitation-learning pipeline, especially if the pipeline assumes exactly 50 demos per task.
+
+## Citation
+
+If you use the underlying LIBERO data, cite the original LIBERO benchmark according to its license and citation requirements. Add the citation for this augmented logical-state version here before publishing if applicable.

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