---
license: apache-2.0
language:
  - en
tags:
  - robotics
  - reinforcement learning
  - embodied ai
  - computer vision
  - simulation
size_categories:
  - 1M<n<10M
task_categories:
  - reinforcement-learning
  - robotics
viewer: false
---

# ManiSkill Demonstrations

This dataset repo contains all of the latest [ManiSkill](https://github.com/haosulab/ManiSkill) demonstration datasets as well as some pretained model weights used to generate some demonstrations. To download by environment ID run

```
python -m mani_skill.utils.download_demo env_id
```

You can also replace env_id with "all" to download all demos.

For the previous ManiSkill2 paper's demonstration data (v0.5.3 of the `mani_skill` package) see https://huggingface.co/datasets/haosulab/ManiSkill2


The demonstrations are organized first by environment ID / task ID, then organized into subfolders indicating where the demonstration data is sourced from (motionplanning, rl, teleop). In the subfolders there may sometimes be several demonstration .h5 dataset files which are typically labelled by the control mode the actions in the dataset are using.

Motionplanning Demonstration Examples
<div style="display: flex; justify-content: center;">
<video playsinline autoplay muted loop>
<source src="https://huggingface.co/datasets/haosulab/ManiSkill_Demonstrations/resolve/main/sample_videos/PegInsertionSide-v1-motionplanning.mp4?download=true">
</video>
<video playsinline autoplay muted loop>
<source src="https://huggingface.co/datasets/haosulab/ManiSkill_Demonstrations/resolve/main/sample_videos/PickCube-v1-motionplanning.mp4?download=true">
</video>
</div>

RL Demonstration Examples
<div style="display: flex; justify-content: center;">
<video playsinline autoplay muted loop>
<source src="https://huggingface.co/datasets/haosulab/ManiSkill_Demonstrations/resolve/main/sample_videos/PushT-v1-rl.mp4?download=true">
</video>

<video playsinline autoplay muted loop>
<source src="https://huggingface.co/datasets/haosulab/ManiSkill_Demonstrations/resolve/main/sample_videos/AnymalC-Reach-v1-rl.mp4?download=true">
</video>
</div>

## Contributing Demonstrations

To contribute demos follow the structure of other tasks by adding them to

```
demos/<env_id>/<demo_type>/
```

and provide a `sample.mp4` file as a sample video of the demonstration and the demo `trajectory.h5` file.

Then run `git add .` and `bash hooks/zip_modified_demos.sh` to add your new demos to the dataset to be tracked by git LFS and update the zip file (for easy download from HF).