task_categories:image-classification size_categories:10K<n<100K language:ar region:us
---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype: int64
  splits:
  - name: train
    num_bytes: 16186819.125
    num_examples: 59999
  - name: test
    num_bytes: 2695549.125
    num_examples: 9999
  download_size: 15361996
  dataset_size: 18882368.25
task_categories:
- image-classification
language:
- ar
pretty_name: Arabic Handwritten Digits Images Dataset
size_categories:
- 10K<n<100K
---
# Dataset Card for MADBase

## Dataset Description

- **Homepage:**
  https://datacenter.aucegypt.edu/shazeem/
- **Repository:** 
- **Paper:**
A Two-Stage System for Arabic Handwritten Digit Recognition Tested on a New Large Database.
EA El-Sherif, S Abdelazeem
Artificial intelligence and pattern recognition, 237-242
- **Leaderboard:** 
- **Point of Contact:**
Ezzat ezzat.elsherif@gmail.com

### Dataset Summary

This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

Arabic

## Dataset Structure

### Data Instances

{
  'image': <PIL.PngImagePlugin.PngImageFile image mode=L size=28x28 at 0x7F5EE5B427A0>,
   'label': 1,
}

### Data Fields

image: A PIL.Image.Image object containing the 28x28 image. Note that when accessing the image column: dataset[0]["image"] the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. dataset[0]["image"] should always be preferred over dataset["image"][0]
label: an integer between 0 and 9 representing the digit.

### Data Splits

The data is split into training and test set. The training set contains, as in mnist dataset, 60,000 images and the test set 10,000 images.

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

The dataset is publickly available for research. Any work that uses this dataset should cite the work below in Citation Information.

### Citation Information
```
@inproceedings{el2007two,
  title={A Two-Stage System for Arabic Handwritten Digit Recognition Tested on a New Large Database.},
  author={El-Sherif, Ezzat Ali and Abdelazeem, Sherif},
  booktitle={Artificial intelligence and pattern recognition},
  pages={237--242},
  year={2007}
}
```

### Contributions

[More Information Needed]