Enhance dataset card: Add descriptive tags and detailed sample usage (#3)

- Enhance dataset card: Add descriptive tags and detailed sample usage (e8f963ed1cdd0305e240705e4bf5333b2a61c60b)


Co-authored-by: Niels Rogge <[email protected]>

README.md

@@ -1,7 +1,13 @@
 ---
+license: mit
 task_categories:
 - image-to-3d
-license: mit
+tags:
+- 3d-physics
+- material-properties
+- gaussian-splatting
+- clip-features
+- 3d-assets
 ---
 
 # Pixie Dataset
@@ -20,13 +26,25 @@ This dataset contains data and pre-trained models for the paper [Pixie: Fast and
 
 ## Sample Usage
 
-Use the download script in the Pixie repository to automatically download this data:
+First, use the download script in the Pixie repository to automatically download this data and models:
 
 ```bash
 python scripts/download_data.py
 ```
 
-For a full pipeline usage, refer to the [Github repository's usage section](https://github.com/vlongle/pixie#usage).
+Then, you can run the main pipeline with a synthetic Objaverse object, for example:
+
+```python
+python pipeline.py obj_id=f420ea9edb914e1b9b7adebbacecc7d8 material_mode=neural
+```
+This command will:
+1. Download the specified Objaverse asset.
+2. Render it and train 3D representations (NeRF, Gaussian Splatting).
+3. Generate a voxel feature grid.
+4. Use the trained neural networks to predict the physics field.
+5. Run the MPM physics solver using the predicted physics parameters.
+
+For more detailed usage, including real-scene processing and training, refer to the [Github repository's usage section](https://github.com/vlongle/pixie#usage).
 
 ## Citation