manot's picture
dataset uploaded by roboflow2huggingface package
e085ecd
---
task_categories:
- object-detection
tags:
- roboflow
- roboflow2huggingface
---
<div align="center">
<img width="640" alt="manot/pothole-segmentation" src="https://huggingface.co/datasets/manot/pothole-segmentation/resolve/main/thumbnail.jpg">
</div>
### Dataset Labels
```
['potholes', 'object', 'pothole', 'potholes']
```
### Number of Images
```json
{'valid': 157, 'test': 80, 'train': 582}
```
### 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("manot/pothole-segmentation", name="full")
example = ds['train'][0]
```
### Roboflow Dataset Page
[https://universe.roboflow.com/abdulmohsen-fahad-f7pdw/road-damage-xvt2d/dataset/3](https://universe.roboflow.com/abdulmohsen-fahad-f7pdw/road-damage-xvt2d/dataset/3?ref=roboflow2huggingface)
### Citation
```
@misc{ road-damage-xvt2d_dataset,
title = { road damage Dataset },
type = { Open Source Dataset },
author = { abdulmohsen fahad },
howpublished = { \\url{ https://universe.roboflow.com/abdulmohsen-fahad-f7pdw/road-damage-xvt2d } },
url = { https://universe.roboflow.com/abdulmohsen-fahad-f7pdw/road-damage-xvt2d },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { jun },
note = { visited on 2023-06-13 },
}
```
### License
CC BY 4.0
### Dataset Summary
This dataset was exported via roboflow.com on June 13, 2023 at 8:47 AM 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 819 images.
Potholes 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.