metadata
language:
- en
task_categories:
- object-detection
tags:
- finance
- table
- structured table
- unstructured table
- documents
pretty_name: TableBorderNet
size_categories:
- 1K<n<10K
# Dataset Card for Table Detection Dataset
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
### Dataset Summary
The Table Detection Dataset contains images of tables, categorized into 'bordered' and 'borderless' classes. The dataset is provided in YOLO format and aims to support research and development in table detection.
### Supported Tasks and Leaderboards
The dataset is intended for the task of table detection, specifically distinguishing between tables with borders ('bordered') and tables without borders ('borderless').
### Languages
The dataset primarily contains images with associated annotations in YOLO format.
## Dataset Structure
### Data Instances
The dataset includes various instances of images containing tables, each labeled with class annotations.
### Data Fields
The data fields in each annotation include class label ('bordered' or 'borderless') along with bounding box coordinates.
### Data Splits
The dataset is provided as a unified collection without predefined data splits.
## Dataset Creation
### Curation Rationale
The dataset was created to address the need for a comprehensive table detection dataset with a focus on border classification.
### Source Data
#### Initial Data Collection and Normalization
The source data was collected and normalized to create a diverse collection of table images.
#### Who are the source language producers?
The dataset was curated by FODUU AI.
### Annotations
#### Annotation process
Annotations were created using YOLO format, providing class labels and bounding box information.
#### Who are the annotators?
Annotations were carried out by experts at FODUU AI.
### Personal and Sensitive Information
The dataset does not contain personal or sensitive information.
## Considerations for Using the Data
### Social Impact of Dataset
The dataset's usage can contribute to advancements in table detection technology, benefiting fields such as document analysis, data extraction, and more.
### Discussion of Biases
No specific biases have been identified in the dataset.
### Other Known Limitations
The dataset may have limitations in terms of the diversity of table designs and backgrounds.
## Additional Information
### Dataset Curators
Curated by FODUU AI.
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
Thanks to [FODUU AI](https://www.foduu.com/) for providing this dataset.