metadata
task_categories:
- object-detection
tags:
- roboflow
- roboflow2huggingface
Dataset Labels
['combined damage', 'flexural', 'minorrotation', 'moderaterotation', 'severerotation', 'shear', 'undamage', 'cracks', 'water']
Number of Images
{'valid': 1266, 'test': 736, 'train': 5255}
How to Use
- Install datasets:
pip install datasets
- Load the dataset:
from datasets import load_dataset
ds = load_dataset("elliemci/building_damages", name="full")
example = ds['train'][0]
Roboflow Dataset Page
https://universe.roboflow.com/elliemci/building-damages-nnk2b/dataset/2
Citation
@misc{
building-damages-nnk2b_dataset,
title = { building damages Dataset },
type = { Open Source Dataset },
author = { EllieMci },
howpublished = { \\url{ https://universe.roboflow.com/elliemci/building-damages-nnk2b } },
url = { https://universe.roboflow.com/elliemci/building-damages-nnk2b },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2025 },
month = { feb },
note = { visited on 2025-02-03 },
}
License
CC BY 4.0
Dataset Summary
This dataset was exported via roboflow.com on February 3, 2025 at 6:53 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 7257 images. Damage-in-structures-Undamage-Flexural-Shear-Combined-water--defects-cracks-waterdamage-crack are annotated in COCO format.
The following pre-processing was applied to each image:
No image augmentation techniques were applied.