DALES-2 / README.md
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---
license: mit
language:
- en
pretty_name: DALES 2
size_categories:
- 1G<n<10G
tags:
- lidar
- point-cloud
- aerial
- 3d-scene-understanding
- instance-segmentation
- semantic-segmentation
- scene-graph
- remote-sensing
task_categories:
- other
---
# DALES 2
## Dataset summary
**DALES 2** is a renovated large-scale **aerial LiDAR** benchmark for **3D scene understanding**, built on the geographic coverage of the original [DALES](https://udayton.edu/blogs/artssciences/2020-stories/dales-large-scale-aerial-lidar.php) release with **re-annotated** semantic and **instance** labels, refined taxonomy, and companion **scene-graph** structure (objects and relations) described in the USM3D workshop paper at CVPR 2026.
This Hub repository distributes the **annotated point clouds** (typically LAZ/LAS per tile). **Graph JSON** and the interactive **[graph editing tool](https://github.com/mbendjilali/dales-2)** live in the companion code repository (see [Scene graph tool](#scene-graph-tool)).
### What is new vs. DALES Objects
- Human-in-the-loop revision of instances and semantics (e.g. powerline granularity per span, tree instances promoted from vegetation, fence as non-instantiable stuff).
- **15-class** semantic taxonomy with per-point **classification** and cross-class **unique instance IDs** within each tile (see [Class IDs](#class-ids)).
- Optional use with **relational graphs** (edges such as adjacent, near, support, extension) when generated with the official pipeline.
## Supported tasks
- Semantic and instance segmentation on aerial LiDAR
- 3D detection / panoptic-style parsing in urban / infrastructure scenes
- Scene graph generation and reasoning (with external graph assets and tools)
## Data modality
- **3D point clouds** (LAZ or LAS), aerial / large-footprint tiles
## Class IDs
| ID | Class | Notes (high level) |
|---:|--------------|---------------------------|
| 0 | Ground | Stuff |
| 1 | Vegetation | Stuff |
| 2 | Car | Vehicle instance |
| 3 | Powerline | Conductor instance |
| 4 | Fence | Stuff |
| 5 | Tree | Tree instance |
| 6 | Pick-up | Vehicle instance |
| 7 | Van & Truck | Vehicle instance |
| 8 | Heavy-duty | Vehicle instance |
| 9 | Utility pole | Pole instance |
| 10 | Light pole | Pole instance |
| 11 | Traffic pole | Pole instance |
| 12 | Habitat | Building instance |
| 13 | Complex | Building instance |
| 14 | Annex | Building instance |
**Instance field:** Each point carries an **instance** attribute. **Non-stuff** objects use distinct positive instance IDs; **stuff** classes use instance **0** in the released convention. Instance IDs are **unique across semantic classes within a tile** (one ID does not appear on two different classes in the same file).
## Dataset structure (repository layout)
Layout may evolve between releases; a typical layout is:
- One file per spatial **tile**, e.g. `*.laz` / `*.las` at the repository root or under a `tiles/` (or similar) prefix.
- Optional sidecar assets (metadata, splits, checksums) as you add them on the Hub.
After uploading, configure **Dataset > Files and versions** so the Hub (and `datasets`) can see supported patterns if you add a `load_dataset` script later. Until then, use **`huggingface_hub`** to download files (below).
## Download
### huggingface_hub (recommended for raw files)
```bash
pip install huggingface_hub
```
```python
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="mbendjilali/DALES-2",
repo_type="dataset",
local_dir="dales2",
)
```
### Git LFS
```bash
git lfs install
git clone https://huggingface.co/datasets/mbendjilali/DALES-2
```
## Scene graph tool
Scene graphs (`graph_*.json`, `graph_*_edges.json`, `geom_*.json`) and the **web editor** are maintained in the **[Github](https://github.com/mbendjilali/dales-2)** codebase. Documentation, schema, and build instructions are in the project README shipped with that repository.
## Citation
If you use this dataset, please cite:
```bibtex
@inproceedings{bendjilali2026dales2,
title = {{DALES} 2: A Renovated Aerial {LiDAR} Benchmark for 3D Scene Understanding},
author = {Bendjilali, Moussa and Peyran, Claire and Velumani, Kaaviya and Mauri, Antoine and Luminari, Nicola and Alliez, Pierre},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2026},
note = {USM3D workshop},
}
```
(Update `pages` or volume fields when official workshop proceedings are available.)
## License
This dataset is released under the **MIT License**, consistent with the Hub dataset metadata.
## Acknowledgments
DALES 2 builds on the original **DALES** aerial LiDAR data and the **DALES Objects** instance benchmark. Please cite the original DALES and DALES Objects papers when comparing to prior work on that geography.
## Contact
For questions about the release or benchmark, open a discussion on this dataset page or contact the authors via the affiliations listed in the paper.