Add dataset card, paper link, and sample usage

README.md

@@ -1,3 +1,61 @@
----
-license: cc-by-nc-sa-4.0
----
+---
+license: cc-by-4.0
+task_categories:
+- object-detection
+---
+
+# TornadoNet: Real-Time Building Damage Detection with Ordinal Supervision
+
+TornadoNet is a comprehensive benchmark for automated street-level building damage assessment. It contains 3,333 high-resolution geotagged images and 8,890 annotated building instances from the 2021 Midwest tornado outbreak.
+
+- **Paper:** [TornadoNet: Real-Time Building Damage Detection with Ordinal Supervision](https://huggingface.co/papers/2603.11557)
+- **GitHub:** [https://github.com/crumeike/TornadoNet](https://github.com/crumeike/TornadoNet)
+
+## Dataset Summary
+The dataset provides building instances annotated with a five-level damage classification framework based on IN-CORE damage states:
+
+| Class | Label | Description |
+|-------|-------|-------------|
+| DS0 | Undamaged | No visible damage |
+| DS1 | Slight | Minor roof/window damage |
+| DS2 | Moderate | Significant roof damage |
+| DS3 | Extensive | Major structural damage |
+| DS4 | Complete | Total collapse |
+
+## Sample Usage
+You can download the dataset using the `huggingface_hub` library:
+
+```python
+from huggingface_hub import snapshot_download
+
+snapshot_download(
+    repo_id="crumeike/tornadonet-datasets",
+    repo_type="dataset",
+    local_dir="./data"
+)
+```
+
+## Dataset Structure
+The dataset follows the YOLO format:
+```
+data/
+├── images/
+│   ├── train/
+│   ├── val/
+│   └── test/
+├── labels/
+│   ├── train/
+│   ├── val/
+│   └── test/
+└── tornadonet.yaml
+```
+
+## Citation
+```bibtex
+@article{umeike2026tornadonet,
+  title={TornadoNet: Real-Time Building Damage Detection with Ordinal Supervision},
+  author={Umeike, Robinson and Pham, Cuong and Hausen, Ryan and Dao, Thang and Crawford, Shane and Brown-Giammanco, Tanya and Lemson, Gerard and van de Lindt, John and Johnston, Blythe and Mitschang, Arik and Do, Trung},
+  journal={arXiv preprint arXiv:2603.11557},
+  year={2026}
+}
+```