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---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 1759539306
num_examples: 2160000
download_size: 1866820804
dataset_size: 1759539306
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
language:
- ar
---
# 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
```python
from datasets import load_dataset
# Load Arabic OCR Dataset
dataset = load_dataset("mssqapi/Arabic-OCR-Dataset")
```
### Accessing Data Samples
```python
# Example of accessing data sample
sample = dataset['train'][0]
print(sample['text'])
display(sample['image'])
```
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