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Dataset Card for Arabic Digits
Dataset Details
Dataset Description
This dataset contains 70,000 Arabic handwritten digits, written by 700 participants. It is intended for Arabic digit recognition tasks using machine learning. The dataset is split into a training set of 60,000 images and a test set of 10,000 images, covering 10 Arabic digits (labeled 0–9). Each digit was written ten times by each writer. The images are in grayscale, 28×28 pixels, and were collected from different institutions to ensure diversity in handwriting styles. The dataset is derived from the MADBase database.
- License: Open Database License (ODbL)
Dataset Sources
- Homepage: https://github.com/mloey/Arabic-Handwritten-Digits-Dataset
- Paper: El-Sawy, A., El-Bakry, H., & Loey, M. (2017). CNN for handwritten arabic digits recognition based on LeNet-5. In Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2016 2 (pp. 566-575). Springer International Publishing.
Dataset Structure
Total images: 70,000
Splits:
Train: 60,000 images (85.7%)
Test: 10,000 images (14.3%)
Classes (labels): 10 (Arabic digits), labeled 0–9
Image specs: PNG format, 28×28 pixels, grayscale
Example Usage
Below is a quick example of how to load this dataset via the Hugging Face Datasets library.
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("randall-lab/arabic-digits", split="train", trust_remote_code=True)
# dataset = load_dataset("randall-lab/arabic-digits", split="test", trust_remote_code=True)
# Access a sample from the training set
example = dataset["train"][0]
image = example["image"]
label = example["label"]
image.show() # Display the image
print(f"Label: {label}")
Citation
BibTeX:
@inproceedings{el2017cnn, title={CNN for handwritten arabic digits recognition based on LeNet-5}, author={El-Sawy, Ahmed and El-Bakry, Hazem and Loey, Mohamed}, booktitle={Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2016 2}, pages={566--575}, year={2017}, organization={Springer} }