README.md

metadata

dataset_info:
  features:
    - name: image
      dtype: image
    - name: age
      dtype: int64
    - name: gender
      dtype: int64
    - name: race
      dtype: int64
  splits:
    - name: train
      num_bytes: 870768436.19
      num_examples: 10135
  download_size: 884280789
  dataset_size: 870768436.19
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: apache-2.0
task_categories:
  - image-classification
language:
  - en
pretty_name: 'RealFaces '
size_categories:
  - 1K<n<10K

UTKFace Demographics V1 Dataset

---

About

The UTKFace Demographics V1 dataset contains over 10,000+ facial images labeled with:

• Age (0 to 116 years)
• Gender (0 = Male, 1 = Female)
• Race (0 = White, 1 = Black, 2 = Asian, 3 = Indian, 4 = Others)

All faces are aligned and cropped to 200x200 resolution, collected in uncontrolled conditions from the wild.

📦 This version restructures the original UTKFace dataset for seamless streaming, preview, and filtering on the Hugging Face Hub.

---

License

This dataset is distributed for research and educational use only. Please cite the original paper if you use this data.

More details and conditions: https://susanqq.github.io/UTKFace/

Citation

@inproceedings{zhifei2017cvpr,
  title={Age Progression/Regression by Conditional Adversarial Autoencoder},
  author={Zhang, Zhifei, Song, Yang, and Qi, Hairong},
  booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2017},
  organization={IEEE}
}

Acknowledgements

Original authors: Zhifei Zhang, Yang Song, and Hairong Qi Project page: https://susanqq.github.io/UTKFace/

I've curated and restructured this version.