---
license: odc-by
language:
- en
viewer: false
---
# ComAsset

![dataset.png](dataset.png)

ComAsset is the dataset of paper ["Beyond the Contact: Discovering Comprehensive Affordance for 3D Objects from Pre-trained 2D Diffusion Models"](https://huggingface.co/papers/2401.12978).

The dataset consists of total 83 object meshes, collected from [SketchFab](https://sketchfab.com/).

All of the meshes are converted to `.obj` format with image texture files. We manually canonicalize the objects in terms of location, orientation and scale.

The format of the dataset is as follows:

```
ComAsset
├── data
│   ├── accordion # object category
│   │   └── wx75e99elm1yhyfxz1efg60luadp95sl # object id
│   │       ├── images # folder for texture files
│   │       ├── model.obj
│   │       └── model.mtl
│   ├── axe
│   ├── ...
│   └── watering can
└── categories.json
```

In `categories.json`, you can check the existing object categories, along with the original data URL and the license information.


# License

ComAsset is licensed under the [ODC-By v1.0](https://opendatacommons.org/licenses/by/1-0/) license. 
This license applies to the dataset as a whole, and users must also comply with the licenses of individual content.
The license of each content is specified in `categories.json`.


# Loading Dataset

```python
from datasets import load_dataset
from huggingface_hub import snapshot_download
import trimesh

snapshot_dir = snapshot_download(repo_id="SShowbiz/ComAsset", repo_type="dataset")
comasset = load_dataset("SShowbiz/ComAsset", data_files={"metadata": "**/metadata.json"})

with open(os.path.join(snapshot_dir, "categories.json"), "r") as json_file: objects = json.load(json_file)
categories = [object_metadata["category"] for object_metadata in objects]

category, *_ = categories # first category
object_metadata, *_ = comasset['metadata'].filter(lambda example: example['category'] == category) # first object

obj_path = os.path.join(snapshot_dir, object_metadata["obj_file"]) 
mesh = trimesh.load(obj_path)
```

# Citation

To cite ComA, please use the following BibTeX entry:

```bibtex
@inproceedings{ComA,
  title="Beyond the Contact: Discovering Comprehensive Affordance for 3D Objects from Pre-trained 2D Diffusion Models",
  author="Kim, Hyeonwoo and Han, Sookwan and Kwon, Patrick and Joo, Hanbyul",
  booktitle=ECCV,
  year={2024}
}
```