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@@ -40,14 +40,14 @@ task_categories:
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  - image-to-text
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  ---
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- # SAND: A Large-Scale Synthetic Arabic OCR Dataset
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  [![Hugging Face Datasets](https://img.shields.io/badge/🤗%20Hugging%20Face-Datasets-yellow)](https://huggingface.co/datasets/riotu-lab/SAND-Extended)
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  [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/riotu-lab/text2image)
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  ## Overview
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- **SAND** (Synthetic Arabic OCR Dataset) is a large-scale, synthetically generated dataset designed for training and evaluating Optical Character Recognition (OCR) models for Arabic text. This dataset addresses the critical need for comprehensive Arabic text recognition resources by providing controlled, diverse, and scalable training data that simulates real-world book layouts.
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  ## Key Features
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@@ -149,7 +149,7 @@ from PIL import Image
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  import matplotlib.pyplot as plt
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  # Load dataset with streaming enabled
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- ds = load_dataset("riotu-lab/SAND-Extended", streaming=True)
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  print(ds)
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  # Iterate over a specific font dataset (e.g., Amiri)
@@ -187,7 +187,7 @@ from datasets import load_dataset
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  import random
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  # Load the dataset
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- ds = load_dataset("riotu-lab/SAND")
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  # Select a balanced sample from multiple fonts
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  fonts_to_use = ["Amiri", "Arial", "Scheherazade_New", "Thabit", "Noto_Naskh_Arabic_UI"]
@@ -223,14 +223,6 @@ SAND is designed to support various Arabic text recognition tasks:
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  If you use SAND in your research, please cite:
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- ```bibtex
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- @misc{sand2025,
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- title={SAND: A Large-Scale Synthetic Arabic OCR Dataset for Vision-Language Models},
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- author={RIOTU Lab},
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- year={2025},
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- howpublished={\url{https://huggingface.co/datasets/riotu-lab/SAND}}
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- }
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- ```
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  ## Acknowledgments
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  - image-to-text
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  ---
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+ # SARD: Synthetic Arabic Recognition Dataset
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  [![Hugging Face Datasets](https://img.shields.io/badge/🤗%20Hugging%20Face-Datasets-yellow)](https://huggingface.co/datasets/riotu-lab/SAND-Extended)
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  [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/riotu-lab/text2image)
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  ## Overview
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+ **SARD** (Synthetic Arabic Recognition Dataset) is a large-scale, synthetically generated dataset designed for training and evaluating Optical Character Recognition (OCR) models for Arabic text. This dataset addresses the critical need for comprehensive Arabic text recognition resources by providing controlled, diverse, and scalable training data that simulates real-world book layouts.
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  ## Key Features
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  import matplotlib.pyplot as plt
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  # Load dataset with streaming enabled
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+ ds = load_dataset("riotu-lab/SARD-Extended", streaming=True)
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  print(ds)
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  # Iterate over a specific font dataset (e.g., Amiri)
 
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  import random
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  # Load the dataset
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+ ds = load_dataset("riotu-lab/SARD")
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  # Select a balanced sample from multiple fonts
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  fonts_to_use = ["Amiri", "Arial", "Scheherazade_New", "Thabit", "Noto_Naskh_Arabic_UI"]
 
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  If you use SAND in your research, please cite:
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  ## Acknowledgments
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