Update README.md

README.md

@@ -1,133 +1,61 @@
 ---
-language:
-- en
 task_categories:
 - object-detection
 tags:
-- finance
+- foduuai
 - table
-- structured table
-- unstructured table
-- documents
-pretty_name: TableBorderNet
-size_categories:
-- 1K<n<10K
+- Documents
+- bordered table
+- borderless table
+- unstructured document
 ---
+<div align="center">
+  <img width="640" alt="keremberke/table-extraction" src="https://huggingface.co/datasets/keremberke/table-extraction/resolve/main/thumbnail.jpg">
+</div>
 
-```
-# 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.
+### Dataset Labels
 
-### 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
+```
+['bordered', 'borderless']
+```
 
-### 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.
+### Number of Images
 
-### Discussion of Biases
+```json
+{'test': 34, 'train': 238, 'valid': 70}
+```
 
-No specific biases have been identified in the dataset.
 
-### Other Known Limitations
+### How to Use
 
-The dataset may have limitations in terms of the diversity of table designs and backgrounds.
+- Install [datasets](https://pypi.org/project/datasets/):
 
-## Additional Information
+```bash
+pip install datasets
+```
 
-### Dataset Curators
+- Load the dataset:
 
-Curated by FODUU AI.
+```python
+from datasets import load_dataset
+ds = load_dataset("foduucom/table-detection-yolo", name="full")
+example = ds['train'][0]
+```
 
-### Licensing Information
+### Dataset Summary
+Certainly! Here's a dataset summary for your dataset of images containing tables that are categorized as border and borderless, provided in YOLO format:
 
-[More Information Needed]
+## Dataset Summary
 
-### Citation Information
+The **Table Detection Dataset** is a curated collection of images, each depicting tables that are classified as either 'bordered' or 'borderless'. The dataset is provided in YOLO format, featuring annotations for accurate object detection and classification. It serves as a valuable resource for researchers, developers, and practitioners working on table detection tasks, with a specific focus on distinguishing between tables with distinct visual characteristics.
 
-[More Information Needed]
+**Key Features:**
+- **Image Variety:** The dataset encompasses a diverse range of images, capturing tables from various real-world scenarios and environments.
+- **Annotation Precision:** Each image is meticulously annotated with bounding box coordinates and class labels, indicating whether the table is 'bordered' or 'borderless'.
+- **YOLO Format:** Annotations follow the YOLO format, making it suitable for training and evaluating object detection models.
+- **Research and Development:** The dataset is designed to facilitate advancements in table detection algorithms and technologies, enabling the development of models capable of accurately identifying and classifying different types of tables.
 
-### Contributions
+Whether you are working on document analysis, data extraction, or image-based content recognition, the Table Detection Dataset provides an essential foundation for enhancing the capabilities of object detection models in identifying tables with varying visual attributes. By offering a comprehensive collection of border and borderless tables, this dataset empowers the AI community to tackle challenges in table detection across a wide range of applications.
 
-Thanks to [FODUU AI](https://www.foduu.com/) for providing this dataset.
-```
+For more details and access to the dataset, please refer to info@foduu.com .