Metadata-Version: 2.4
Name: robotdataset
Version: 0.1.0
Summary: A Python package for RL data handling.
Author-email: Robotics Action Group <vaishnavahari.seenivasan@rwth-aachen.de>
License: MIT
Project-URL: Homepage, https://github.com/robotics-action-group/robotdataset
Project-URL: Repository, https://github.com/robotics-action-group/robotdataset.git
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: ipykernel>=6.16.2
Requires-Dist: numpy>=1.21.6
Requires-Dist: tensordict>=0.2.1
Requires-Dist: torch>=1.13.1
Requires-Dist: torchrl>=0.2.0
Requires-Dist: tqdm>=4.64.0
Requires-Dist: imageio[ffmpeg]
Provides-Extra: oxe
Requires-Dist: tensorflow>=2.11.1; extra == "oxe"
Requires-Dist: tensorflow-datasets>=4.8.2; extra == "oxe"
Provides-Extra: hf
Requires-Dist: datasets>=2.14.0; extra == "hf"
Requires-Dist: huggingface_hub>=0.19.0; extra == "hf"
Requires-Dist: Pillow>=9.0; extra == "hf"
Dynamic: license-file

# robotdataset

A Python package for loading robot learning datasets, with support for the [Open X-Embodiment (OXE)](./doc/OXE.md) collection.

## Installation

```bash
pip install "robotdataset[oxe]"
```

Or from source:

```bash
git clone https://github.com/robotics-action-group/robotdataset.git
cd robotdataset
pip install -e ".[oxe]"
```

**Requirements:** Python >= 3.7, PyTorch >= 1.13.1, TensorFlow >= 2.11.1, TensorFlow Datasets >= 4.8.2

## Quick Start

```python
from robotdataset import OXEDataset

dataset = OXEDataset(dataset_name='droid', split='train')

print(len(dataset))
print(dataset.get_dataset_info())

for sample in dataset:
    print(sample.keys())
    break
```

## License

MIT — see [LICENSE](LICENSE).
