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@@ -18,11 +18,8 @@ The RDD2020 dataset is a comprehensive collection of 26,336 road images from Ind
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  - Japan and Czech: 600 × 600 pixels
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  - **Categories:** Longitudinal Cracks (D00), Transverse Cracks (D10), Alligator Cracks (D20), Potholes (D40)
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- - **Curated by:** [More Information Needed]
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  - **Funded by [optional]:** [More Information Needed]
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  - **Shared by [optional]:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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  - **License:** https://creativecommons.org/licenses/by/4.0/
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  ### Dataset Sources [optional]
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  #### Data Collection and Processing
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  <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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  #### Who are the source data producers?
 
 
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  <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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- [More Information Needed]
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  ### Annotations [optional]
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  <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
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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).
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  #### Annotation process
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  <!-- 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. -->
 
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  ## Bias, Risks, and Limitations
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  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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- ## Citation [optional]
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- <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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- **BibTeX:**
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- [More Information Needed]
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- **APA:**
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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- [More Information Needed]
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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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- [More Information Needed]
 
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  - Japan and Czech: 600 × 600 pixels
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  - **Categories:** Longitudinal Cracks (D00), Transverse Cracks (D10), Alligator Cracks (D20), Potholes (D40)
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  - **Funded by [optional]:** [More Information Needed]
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  - **Shared by [optional]:** [More Information Needed]
 
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  - **License:** https://creativecommons.org/licenses/by/4.0/
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  ### Dataset Sources [optional]
 
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  #### Data Collection and Processing
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  <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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+ Road images (.jpg) were collected using a vehicle-mounted smartphone, moving at an average speed of about 40Km/h. XML files were created using the LabelImg tool to annotate the road damages present in the images.
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  #### Who are the source data producers?
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+ Deeksha Arya, Hiroya Maeda, Sanjay Kumar Ghosh, Durga Toshniwal, Hiroshi Omata, Takehiro Kashiyama, Toshikazu Seto, Alexander Mraz,
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+ Yoshihide Sekimot
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  <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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  ### Annotations [optional]
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  <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
 
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  #### Annotation process
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  <!-- 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. -->
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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).
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  ## Bias, Risks, and Limitations
 
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  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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