---
license: apache-2.0
task_categories:
- robotics
tags:
- motion-retargeting
- humanoid-robot
- agibot
- unitree-g1
size_categories:
- 10G<n<100G
---

# Agibot2UnitreeG1Retarget Dataset

## Description
This dataset contains action retargeting data from Agibot to UnitreeG1 humanoid robot.

## Dataset Size
- Total size: ~30GB
- Split into 7 parts (A2UG1_dataset.tar.gz.aa to A2UG1_dataset.tar.gz.ag)
- Each part is approximately 4GB

## Usage

### Method 1: Using Hugging Face Hub (Recommended)
```bash
pip install huggingface-hub
```

```python
from huggingface_hub import snapshot_download

# Download the entire dataset
snapshot_download(
    repo_id="l2aggle/Agibot2UnitreeG1Retarget",
    repo_type="dataset",
    local_dir="./Agibot2UnitreeG1Retarget"
)
```

### Method 2: Using Git with LFS
```bash
# Make sure git-lfs is installed
git lfs install

# Clone the repository (this will download LFS pointer files)
git clone https://huggingface.co/datasets/l2aggle/Agibot2UnitreeG1Retarget
cd Agibot2UnitreeG1Retarget

# Download the actual large files
git lfs pull
```

### Method 3: Manual Download
Download individual parts through the Hugging Face web interface:
https://huggingface.co/datasets/l2aggle/Agibot2UnitreeG1Retarget/tree/main

## Extract Dataset
After downloading, extract the complete dataset:

```bash
# Combine and extract all parts
cat A2UG1_dataset.tar.gz.* | tar -xzf -
```

This will create the complete `A2UG1_dataset` folder with all original files.

## File Structure
```
A2UG1_dataset/
├── [your dataset structure will be shown here after extraction]
```

## Requirements
- At least 60GB free disk space (30GB for download + 30GB for extraction)
- For Method 1: Python 3.6+ with `huggingface-hub` package
- For Method 2: Git with Git LFS support
- tar utility (standard on Linux/Mac, available on Windows via WSL or Git Bash)

## Installation Requirements
```bash
# For Method 1
pip install huggingface-hub

# For Method 2 (if git-lfs not installed)
# Ubuntu/Debian:
sudo apt install git-lfs
# macOS:
brew install git-lfs
# Windows: download from https://git-lfs.github.io/
```

## License
Apache 2.0