---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: age
    dtype:
      class_label:
        names:
          '0': 0-2
          '1': 3-9
          '2': 10-19
          '3': 20-29
          '4': 30-39
          '5': 40-49
          '6': 50-59
          '7': 60-69
          '8': more than 70
  - name: gender
    dtype:
      class_label:
        names:
          '0': Male
          '1': Female
  - name: race
    dtype:
      class_label:
        names:
          '0': East Asian
          '1': Indian
          '2': Black
          '3': White
          '4': Middle Eastern
          '5': Latino_Hispanic
          '6': Southeast Asian
  - name: service_test
    dtype: bool
  splits:
  - name: train
    num_bytes: 65869100.551
    num_examples: 3031
  download_size: 65046038
  dataset_size: 65869100.551
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: apache-2.0
language:
- en
pretty_name: Fairness
size_categories:
- 1K<n<10K
---

<h1 align="center" style="font-family:Arial, sans-serif; font-size:36px; color:#333;">FairFace_Balanced_3K</h1>

## Overview

`FairFace_Balanced_3K` is a balanced subset of the original [HuggingFaceM4/FairFace](https://huggingface.co/datasets/HuggingFaceM4/FairFace) dataset created to support bias-sensitive experiments in facial attribute recognition. This subset includes **3,031 samples**, with **433 images per race class**, across **7 race categories**:

- White  
- Black  
- East Asian  
- Southeast Asian  
- Indian  
- Middle Eastern  
- Latino_Hispanic  

Each entry contains:
- RGB facial image
- Age group label (9 categories)
- Gender label (Male, Female)
- Race label (7 classes)

The subset is balanced to mitigate data bias and allow fair evaluation across racial groups.

Some random samples of the dataset are as: <img src="testimgs/random_samples.png" alt="Sample" width="300"/>


## Data Format

The dataset is stored in the Hugging Face Hub using the `datasets` library and Parquet format. Each row includes:
- `image`: PIL image in byte format
- `age`: Integer (mapped to age group)
- `gender`: Integer (0: Male, 1: Female)
- `race`: Integer (0–6, mapped to race category)

## Visuals
- Race Distribution
   <img src="testimgs/race_distribution.png" alt="Sample" width="300"/>

- Age vs Group Distriution
   <img src="testimgs/age_roup_distribution.png" alt="Sample" width="300"/>

- Gender Distribution
   <img src="testimgs/gender_distribution.png" alt="Sample" width="300"/>
  
## Citation

If you use this dataset or the original FairFace dataset, please cite the following work:

```bibtex
@inproceedings{karkkainenfairface,
  title={FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age for Bias Measurement and Mitigation},
  author={Karkkainen, Kimmo and Joo, Jungseock},
  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
  year={2021},
  pages={1548--1558}
}
```

## Original Sources

Original Repo: [joojs/fairface](https://github.com/joojs/fairface)

Original Dataset: [HuggingFaceM4/FairFace](https://huggingface.co/datasets/HuggingFaceM4/FairFace)

Original Paper: [FairFace](https://openaccess.thecvf.com/content/WACV2021/papers/Karkkainen_FairFace_Face_Attribute_Dataset_for_Balanced_Race_Gender_and_Age_WACV_2021_paper.pdf)