---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
dataset_info:
  features:
  - name: id
    dtype: string
  - name: image
    dtype: image
  - name: output
    dtype: string
  splits:
  - name: train
    num_bytes: 2440808481
    num_examples: 22435
  - name: validation
    num_bytes: 329337240
    num_examples: 2804
  - name: test
    num_bytes: 328649745
    num_examples: 2805
  download_size: 3127169673
  dataset_size: 3098795466
---
# Arabic-Image2Html Dataset

A dataset of **28K image-HTML pairs** for training OCR models to transform Arabic documents into structured and semantic HTML.

## Dataset Description

This dataset was created to address the lack of available open-source Arabic OCR datasets with image-to-semantic HTML pairs. It contains diverse Arabic document images paired with clean, semantic HTML output.

### Dataset Composition

The dataset consists of two main components:

**1. Web-Scraped Wikipedia Content (~13K samples, 46%)**
- Extracted from Arabic Wikipedia articles
- Post-processed HTML with only semantic tags preserved
- Screenshots captured with real styling using Playwright
- Cleaned structure with proper semantic elements (section, header, main, etc.)

**2. Synthetically Generated Documents (~15K samples, 54%)**
- HTML documents rendered into images using CSS styling
- Mimics various real-world document types:
  - Historical manuscripts
  - Newspaper articles
  - Scientific papers
  - Invoices
  - Recipes
  - And more (~13 formats total)
- Diverse layouts, styles, noise levels, fonts, and text flows
- Filled with plain Arabic text from open datasets
- Multiple semantic tag combinations (footer, table, section, etc.)

### Features

- **Total samples:** 28,000 image-HTML pairs
- **Language:** Arabic
- **Output format:** Semantic HTML (clean tags without id, class attributes)
- **Document diversity:** Multiple formats and layouts

## Usage

### Loading the Dataset

```python
from datasets import load_dataset

dataset = load_dataset("OussamaBenSlama/arabic-image2html")
```


## Limitations

- Limited examples with diacritical marks (tashkeel), which may affect model performance on texts with extensive diacritics
- Wikipedia samples share similar design patterns
- Synthetic generation may not capture all real-world document variations

## Related Resources

- **Model:** [Alef-OCR-Image2Html](https://huggingface.co/OussamaBenSlama/Alef-OCR-Image2Html)
- **Training Notebooks:** [Github Repository](https://github.com/OussamaBenSlama/Alef-OCR-Image2Html)

## Citation

```bibtex
@misc{arabic_image2html_2025,
  title={Arabic-Image2Html: A Dataset for Arabic OCR to Semantic HTML},
  author={Oussama Ben Slama},
  year={2025},
  howpublished={Hugging Face Datasets},
  url={https://huggingface.co/datasets/OussamaBenSlama/arabic-image2html}
}
```

## License

Apache2.0
## Acknowledgments

This work builds upon the excellent research by the NAMAA community and their state-of-the-art Qari-OCR model.