mssqpi/Arabic-OCR-Dataset

Arabic OCR Dataset

Overview

The Arabic OCR Dataset is a comprehensive resource aimed at enhancing Optical Character Recognition (OCR) capabilities for the Arabic language. The dataset consists of over 2 million labeled images of Arabic text extracted from diverse sources, ideal for training and benchmarking Arabic OCR models.

Dataset Details

• Dataset Size: ~2.16 million labeled samples
• Total File Size: 1.87 GB
• Format: Parquet
• Modalities: Images and Text
• Languages: Arabic

Structure

Each entry in the dataset includes:

• image: An image file containing Arabic text.
• text: Corresponding Arabic text as ground truth.

The images vary in width from 29px to 222px, containing text samples ranging from 7 to 10 characters in length.

Intended Uses

This dataset is designed for:

• Training state-of-the-art Arabic OCR models.
• Evaluating performance of OCR systems.
• Research in Arabic Natural Language Processing (NLP).

Limitations

• Text length is limited to short to medium-length Arabic text snippets.
• Variability in image quality may affect OCR performance.

How to Use

Loading the Dataset

from datasets import load_dataset

# Load Arabic OCR Dataset
dataset = load_dataset("mssqapi/Arabic-OCR-Dataset")

Accessing Data Samples

# Example of accessing data sample
sample = dataset['train'][0]
print(sample['text'])
display(sample['image'])