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# Dataset Card for RDD_2020
The RDD2020 dataset is a comprehensive collection of 26,336 road images from India, Japan, and the Czech Republic, annotated with over 31,000 instances of road damages. This dataset is designed to support the development and evaluation of machine learning models for automatic road damage detection, offering a valuable resource for municipalities and road agencies for efficient road condition monitoring.
## Dataset Details

### Dataset Description

- **Source:** [Mendeley Data](https://data.mendeley.com/datasets/5ty2wb6gvg/1) - DOI: 10.17632/5ty2wb6gvg.1  
- **Size:** 1.13 GB  
- **Format:** Images (JPEG) and Annotations (XML in PASCAL VOC format)  
- **Resolution:**   
  - India: 720 × 720 pixels  
  - Japan and Czech: 600 × 600 pixels  
- **Categories:** Longitudinal Cracks (D00), Transverse Cracks (D10), Alligator Cracks (D20), Potholes (D40)  


- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** https://creativecommons.org/licenses/by/4.0/

### Dataset Sources [optional]

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- **Homepage** https://data.mendeley.com/datasets/5ty2wb6gvg/1
- **Data article:** https://doi.org/10.1016/j.dib.2021.107133


## Uses

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### Direct Use

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RDD2020 dataset can be directly used for developing and benchmarking machine learning models aimed at automatic detection and classification of road damages. This includes developing new deep learning architectures or modifying existing ones to improve detection accuracy across different types of road damages


## Dataset Structure

The data will follow the structure below:
{
  "image_id": "Czech_000248",
  "country": "Czech",
  "type": "train",
  "image": "<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=600x600>",
  "image_path": "train/Czech/images/Czech_000248.jpg",
  "crack_type": ["D20", "D20"],
  "crack_coordinates": {
    "x_min": [188, 3],
    "x_max": [309, 171],
    "y_min": [463, 438],
    "y_max": [509, 519]
  }
}




## Dataset Creation

### Curation Rationale

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#### Data Collection and Processing

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[More Information Needed]

#### Who are the source data producers?

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### Annotations [optional]

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Each image in the dataset comes with corresponding XML files containing annotations in PASCAL VOC format. These annotations describe the location and type of road damages present in the images, categorized into four main types: Longitudinal Cracks (D00), Transverse Cracks (D10), Alligator Cracks (D20), and Potholes (D40).
#### Annotation process

<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->


## Bias, Risks, and Limitations

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[More Information Needed]

### Recommendations

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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [optional]

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**BibTeX:**

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**APA:**

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## Glossary [optional]

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## More Information [optional]

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## Dataset Card Authors [optional]

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## Dataset Card Contact

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