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README.md

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+---
+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.

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