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---
license: apache-2.0
task_categories:
- robotics
- image-to-3d
tags:
- objaverse
- procthor
- ai2-thor
- 3d-objects
- embodied-ai
- procedural-generation
---
# Objaverse VIDA Dataset
Processed 3D assets from [Objaverse](https://objaverse.allenai.org/) for use with [AI2-THOR](https://ai2thor.allenai.org/) and [ProcTHOR](https://procthor.allenai.org/).
## Contents
| Component | Description | Size |
|-----------|-------------|------|
| `processed_2023_07_28/` | ~40K processed 3D objects with textures | 27 GB |
| `houses_2023_07_28/` | 160K+ procedurally generated house layouts | 3.7 GB |
| `procthor_databases_2023_07_28/` | Asset databases, materials, placement rules | 70 MB |
## Quick Start
```bash
# Install dependencies
pip install huggingface_hub[hf_transfer]
# Download the unpack script
wget https://huggingface.co/datasets/spatial-training/objaverse_vida/raw/main/unpack.py
# Run it (downloads ~30GB and extracts to ./objaverse_vida)
python unpack.py ./objaverse_vida
```
Or specify a custom path:
```bash
python unpack.py /path/to/destination
```
## Data Format
### Processed Objects
Each object directory contains:
```
{object_id}/
├── {object_id}.pkl.gz # 3D mesh data (gzip pickle)
├── albedo.jpg # Diffuse texture
├── normal.jpg # Normal map
├── emission.jpg # Emission map
└── thor_metadata.json # AI2-THOR metadata
```
### House Layouts
- `train.jsonl.gz` / `test.jsonl.gz` / `val.jsonl.gz` - Full house definitions
- `train/` / `test/` / `val/` - Individual house JSON files
### Asset Databases
- `asset-database.json` - Asset catalog
- `material-database.json` - Materials
- `placement-annotations.json` - Placement rules
- `receptacles.json` - Receptacle definitions
## Manual Download
If you prefer not to use the script:
```bash
# Clone the dataset
huggingface-cli download spatial-training/objaverse_vida --repo-type dataset --local-dir ./objaverse_vida
# Extract processed shards
cd objaverse_vida/processed_2023_07_28
for f in shard_*.tar; do tar -xf "$f" && rm "$f"; done
rm manifest.json
# Extract house files
cd ../houses_2023_07_28
for split in train test val; do
tar -xf "${split}_individual.tar" -C "$split/" && rm "${split}_individual.tar"
done
```
## Citation
```bibtex
@inproceedings{deitke2023objaverse,
title={Objaverse: A Universe of Annotated 3D Objects},
author={Deitke, Matt and others},
booktitle={CVPR},
year={2023}
}
@inproceedings{deitke2022procthor,
title={ProcTHOR: Large-Scale Embodied AI Using Procedural Generation},
author={Deitke, Matt and others},
booktitle={NeurIPS},
year={2022}
}
```
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