| --- |
| task_categories: |
| - image-segmentation |
| tags: |
| - roboflow |
| - roboflow2huggingface |
| - Aerial |
| - Logistics |
| - Construction |
| - Damage Risk |
| - Other |
| --- |
| |
| <div align="center"> |
| <img width="640" alt="keremberke/satellite-building-segmentation" src="https://huggingface.co/datasets/keremberke/satellite-building-segmentation/resolve/main/thumbnail.jpg"> |
| </div> |
|
|
| ### Dataset Labels |
|
|
| ``` |
| ['building'] |
| ``` |
|
|
|
|
| ### Number of Images |
|
|
| ```json |
| {'train': 6764, 'valid': 1934, 'test': 967} |
| ``` |
|
|
|
|
| ### How to Use |
|
|
| - Install [datasets](https://pypi.org/project/datasets/): |
|
|
| ```bash |
| pip install datasets |
| ``` |
|
|
| - Load the dataset: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("keremberke/satellite-building-segmentation", name="full") |
| example = ds['train'][0] |
| ``` |
|
|
| ### Roboflow Dataset Page |
| [https://universe.roboflow.com/roboflow-universe-projects/buildings-instance-segmentation/dataset/1](https://universe.roboflow.com/roboflow-universe-projects/buildings-instance-segmentation/dataset/1?ref=roboflow2huggingface) |
|
|
| ### Citation |
|
|
| ``` |
| @misc{ buildings-instance-segmentation_dataset, |
| title = { Buildings Instance Segmentation Dataset }, |
| type = { Open Source Dataset }, |
| author = { Roboflow Universe Projects }, |
| howpublished = { \\url{ https://universe.roboflow.com/roboflow-universe-projects/buildings-instance-segmentation } }, |
| url = { https://universe.roboflow.com/roboflow-universe-projects/buildings-instance-segmentation }, |
| journal = { Roboflow Universe }, |
| publisher = { Roboflow }, |
| year = { 2023 }, |
| month = { jan }, |
| note = { visited on 2023-01-18 }, |
| } |
| ``` |
|
|
| ### License |
| CC BY 4.0 |
|
|
| ### Dataset Summary |
| This dataset was exported via roboflow.com on January 16, 2023 at 9:09 PM GMT |
|
|
| Roboflow is an end-to-end computer vision platform that helps you |
| * collaborate with your team on computer vision projects |
| * collect & organize images |
| * understand and search unstructured image data |
| * annotate, and create datasets |
| * export, train, and deploy computer vision models |
| * use active learning to improve your dataset over time |
|
|
| For state of the art Computer Vision training notebooks you can use with this dataset, |
| visit https://github.com/roboflow/notebooks |
|
|
| To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com |
|
|
| The dataset includes 9665 images. |
| Buildings are annotated in COCO format. |
|
|
| The following pre-processing was applied to each image: |
| * Auto-orientation of pixel data (with EXIF-orientation stripping) |
|
|
| No image augmentation techniques were applied. |
|
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|
