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README.md

@@ -8,7 +8,7 @@ viewer: false
 
 ComAsset is the dataset for paper "Beyond the Contact: Discovering Comprehensive Affordance for 3D Objects from Pre-trained 2D Diffusion Models".
 
-The dataset consists of total 93 object meshes, collected from [SketchFab](https://sketchfab.com/).
+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.
 
@@ -24,12 +24,32 @@ ComAsset
 │   │       └── model.mtl
 │   ├── axe
 │   ├── ...
-│   └── wine glass
+│   └── watering can
 └── categories.json
 ```
 
 In `categories.json`, you can check the existing object categories, along with the original data URL and the license information.
 
+# Loading Dataset
+
+```python
+from datasets import load_dataset, config
+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: