Datasets:
Tasks:
Image Segmentation
Size:
1K - 10K
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. | |