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README.md

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+---
+license: mit
+task_categories:
+  - image-segmentation
+  - object-detection
+tags:
+  - panoptic-segmentation
+  - aerial-imagery
+  - remote-sensing
+  - COCO
+  - detectron2
+  - urban
+  - Brasilia
+pretty_name: BSB Aerial Dataset
+size_categories:
+  - 1K<n<10K
+language:
+  - en
+---
+
+# BSB Aerial Dataset
+
+A panoptic segmentation dataset of aerial imagery from Brasilia, Brazil, annotated in COCO format.
+
+## Dataset Description
+
+The BSB Aerial Dataset contains **3,400 aerial image tiles** (512x512 pixels) of urban areas in Brasilia, annotated for panoptic segmentation with **14 categories** covering both "stuff" and "things" classes.
+
+### Splits
+
+| Split | Images |
+|-------|--------|
+| Train | 3,000  |
+| Val   | 200    |
+| Test  | 200    |
+
+### Categories
+
+| ID | Name                  | Type  |
+|----|-----------------------|-------|
+| 1  | Street                | Stuff |
+| 2  | Permeable Area        | Stuff |
+| 3  | Lake                  | Stuff |
+| 4  | Swimming Pool         | Thing |
+| 5  | Harbor                | Thing |
+| 6  | Vehicle               | Thing |
+| 7  | Boat                  | Thing |
+| 8  | Sports Court          | Thing |
+| 9  | Soccer Field          | Thing |
+| 10 | Comm. Building        | Thing |
+| 11 | Comm. Building Block  | Thing |
+| 12 | Res. Building         | Thing |
+| 13 | House                 | Thing |
+| 14 | Small Construction    | Thing |
+
+## Dataset Structure
+
+```
+bsb_dataset/
+├── annotations/
+│   ├── panoptic_train.json
+│   ├── panoptic_val.json
+│   ├── panoptic_test.json
+│   ├── instance_train.json
+│   ├── instance_val.json
+│   └── instance_test.json
+├── image_train/          # RGB aerial tiles (TIFF)
+├── image_val/
+├── image_test/
+├── panoptic_train/       # Panoptic segmentation masks
+├── panoptic_val/
+├── panoptic_test/
+├── panoptic_stuff_train/ # Stuff-only masks
+├── panoptic_stuff_val/
+├── panoptic_stuff_test/
+├── class_train/          # Semantic class masks
+├── class_val/
+└── class_test/
+```
+
+## Annotation Format
+
+Annotations follow the [COCO Panoptic format](https://cocodataset.org/#format-data). Each annotation JSON contains image metadata and segment information compatible with tools like Detectron2.
+
+## Usage with Detectron2
+
+See the example notebook in the [GitHub repository](https://github.com/osmarluiz/BSB-Aerial-Dataset) for a full implementation using Detectron2's Panoptic-FPN.
+
+> **Note:** The repository includes a modified `detection_utils.py` that properly handles RGB image tiles. Replace the original Detectron2 file with the provided version.
+
+## Related Tools
+
+- [Panoptic-Generator](https://github.com/abilius-app/Panoptic-Generator) — Tool for building remote sensing panoptic segmentation datasets in COCO format using GIS software.
+
+## Citation
+
+If you use this dataset in your research, please cite:
+
+```bibtex
+@misc{bsb_aerial_dataset,
+  author = {Osmar Luiz Carvalho},
+  title = {BSB Aerial Dataset: Panoptic Segmentation of Aerial Imagery from Brasilia},
+  year = {2024},
+  url = {https://github.com/osmarluiz/BSB-Aerial-Dataset}
+}
+```
+
+## License
+
+This dataset is released under the [MIT License](https://opensource.org/licenses/MIT).