Update README.md

README.md

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-# Dataset Card for Dataset Name
-
-<!-- Provide a quick summary of the dataset. -->
-
-This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
-
+# 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
 
-<!-- Provide a longer summary of what this dataset is. -->
-
+- **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:** [More Information Needed]
+- **License:** https://creativecommons.org/licenses/by/4.0/
 
 ### Dataset Sources [optional]
 
 <!-- Provide the basic links for the dataset. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Homepage** https://data.mendeley.com/datasets/5ty2wb6gvg/1
+- **Data article:** https://doi.org/10.1016/j.dib.2021.107133
+
 
 ## Uses
 
@@ -40,19 +41,29 @@ This dataset card aims to be a base template for new datasets. It has been gener
 
 <!-- This section describes suitable use cases for the dataset. -->
 
-[More Information Needed]
+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
 
-### Out-of-Scope Use
 
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
+## Dataset Structure
 
-[More Information Needed]
+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 Structure
 
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
 
-[More Information Needed]
 
 ## Dataset Creation
 
@@ -60,11 +71,8 @@ This dataset card aims to be a base template for new datasets. It has been gener
 
 <!-- Motivation for the creation of this dataset. -->
 
-[More Information Needed]
 
-### Source Data
 
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
 
 #### Data Collection and Processing
 
@@ -81,24 +89,11 @@ This dataset card aims to be a base template for new datasets. It has been gener
 ### Annotations [optional]
 
 <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-
+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. -->
 
-[More Information Needed]
-
-#### Who are the annotators?
-
-<!-- This section describes the people or systems who created the annotations. -->
-
-[More Information Needed]
-
-#### Personal and Sensitive Information
-
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-
-[More Information Needed]
 
 ## Bias, Risks, and Limitations