Datasets:

Ayana666888
/

LIBERO-3D

license: apache-2.0
pretty_name: LIBERO-3D
task_categories:
  - robotics
tags:
  - robotics
  - imitation-learning
  - reinforcement-learning
  - embodied-ai
  - computer-vision
  - depth
  - point-cloud
  - npz
size_categories:
  - 100K<n<1M

LIBERO-3D

LIBERO-3D is a processed LIBERO demonstration dataset packaged for 3D-aware robot learning. It keeps the original LIBERO task suites while converting each trajectory into per-episode .npz files with RGB, depth, camera parameters, segmentation, states, and actions.

This repository is intended as a storage and distribution repo for dataset files. The Hugging Face dataset viewer is not expected to render these files directly because the payload is stored as binary .npz episodes rather than tabular data.

The repository is organized into four suites:

libero_goal/
libero_object/
libero_spatial/
libero_10/
README.md

Each suite contains 10 tasks. Each task contains 50 episodes. In total this repo contains 40 tasks and 2000 episodes.

Each task directory follows this structure:

<suite>/<task_name>/
  metadata.json
  _SUCCESS
  episode_000/data.npz
  episode_001/data.npz
  ...
  episode_049/data.npz

Data Format

Each data.npz episode stores trajectory-aligned arrays. The exact keys can be checked from the accompanying metadata.json. The processed files include at least the following modalities:

state: robot state, shape (T, 8)
actions: control actions, shape (T, 7)
agentview_rgb: static camera RGB frames, shape (T, 256, 256, 3)
agentview_depth: static camera depth frames, shape (T, 256, 256)
wrist_rgb: wrist camera RGB frames, shape (T, 256, 256, 3)
wrist_depth: wrist camera depth frames, shape (T, 256, 256)
wrist_intrinsic: wrist camera intrinsics, shape (T, 3, 3)
wrist_extrinsic: wrist camera extrinsics, shape (T, 4, 4)
wrist_segmentation: wrist segmentation maps, shape (T, 256, 256, 2)

The task-level metadata.json also records:

suite name and task name
original source demo path
image resolution
state semantics
static and dynamic camera calibration fields
per-episode step counts and tensor shapes

Suite Summary

libero_goal: 10 goal-conditioned manipulation tasks
libero_object: 10 object-centric pick-and-place tasks
libero_spatial: 10 spatial-relation manipulation tasks
libero_10: 10 long-horizon tasks from the LIBERO-10 suite

Source

This dataset is derived from the LIBERO benchmark datasets and reorganized into processed per-episode .npz files for downstream 3D learning pipelines.

Official LIBERO repository: https://github.com/Lifelong-Robot-Learning/LIBERO
Official Hugging Face dataset release for the original demo files: https://huggingface.co/datasets/yifengzhu-hf/LIBERO-datasets

Usage Notes

This repo is for file hosting and dataset download, not for in-browser preview.
Keep the directory names stable if downstream code expects suite names such as libero_goal or libero_10.
Do not upload macOS metadata files such as ._* or .DS_Store.
Large-file upload tooling such as huggingface_hub or hf upload-large-folder is recommended.

License

This processed release follows the upstream LIBERO dataset license labeling used in the official Hugging Face dataset repository: apache-2.0.