README.md

metadata

dataset_info:
  features:
    - name: image
      dtype: image
    - name: 5_o_Clock_Shadow
      dtype: int64
    - name: Arched_Eyebrows
      dtype: int64
    - name: Bags_Under_Eyes
      dtype: int64
    - name: Bald
      dtype: int64
    - name: Bangs
      dtype: int64
    - name: Big_Lips
      dtype: int64
    - name: Big_Nose
      dtype: int64
    - name: Black_Hair
      dtype: int64
    - name: Blond_Hair
      dtype: int64
    - name: Blurry
      dtype: int64
    - name: Brown_Hair
      dtype: int64
    - name: Bushy_Eyebrows
      dtype: int64
    - name: Chubby
      dtype: int64
    - name: Double_Chin
      dtype: int64
    - name: Eyeglasses
      dtype: int64
    - name: Goatee
      dtype: int64
    - name: Gray_Hair
      dtype: int64
    - name: Heavy_Makeup
      dtype: int64
    - name: High_Cheekbones
      dtype: int64
    - name: Male
      dtype: int64
    - name: Mouth_Slightly_Open
      dtype: int64
    - name: Mustache
      dtype: int64
    - name: Narrow_Eyes
      dtype: int64
    - name: No_Beard
      dtype: int64
    - name: Oval_Face
      dtype: int64
    - name: Pale_Skin
      dtype: int64
    - name: Pointy_Nose
      dtype: int64
    - name: Receding_Hairline
      dtype: int64
    - name: Rosy_Cheeks
      dtype: int64
    - name: Sideburns
      dtype: int64
    - name: Smiling
      dtype: int64
    - name: Straight_Hair
      dtype: int64
    - name: Wavy_Hair
      dtype: int64
    - name: Wearing_Earrings
      dtype: int64
    - name: Wearing_Hat
      dtype: int64
    - name: Wearing_Lipstick
      dtype: int64
    - name: Wearing_Necklace
      dtype: int64
    - name: Wearing_Necktie
      dtype: int64
    - name: Young
      dtype: int64
    - name: image_hash
      dtype: string
    - name: Attractive
      dtype: int64
    - name: reviewed
      dtype: bool
  splits:
    - name: train
      num_bytes: 879662473.28
      num_examples: 117544
  download_size: 839788664
  dataset_size: 879662473.28
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

CelebA Female Dataset

Dataset Description

This dataset is a filtered subset of the CelebA dataset (Celebrities Faces Attributes), containing only female faces. The original CelebA dataset is a large-scale face attributes dataset with more than 200,000 celebrity images, each with 40 attribute annotations.

Dataset Creation

This dataset was created by:

1. Loading the original CelebA dataset
2. Filtering to keep only images labeled as female (based on the "Male" attribute)
3. Deduplicating the dataset to remove any potential duplicate images

Intended Uses & Limitations

This dataset is intended for:

• Facial analysis research focusing on female subjects
• Training or fine-tuning image models that need to work specifically with female faces
• Studying facial attributes in a gender-specific context

Limitations:

• The dataset is limited to faces labeled as female in the original CelebA dataset
• Any biases present in the original CelebA dataset may persist in this filtered version
• The gender labels come from the original dataset and may not reflect self-identification

Dataset Structure

The dataset preserves the original structure of CelebA, including:

• Image data
• All 40 original attribute annotations
• File paths and identifiers

Citation

If you use this dataset, please cite both the original CelebA dataset and this filtered version:

@inproceedings{liu2015faceattributes, title = {Deep Learning Face Attributes in the Wild}, author = {Liu, Ziwei and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou}, booktitle = {Proceedings of International Conference on Computer Vision (ICCV)}, month = {December}, year = {2015} }

Ethical Considerations

This gender-filtered dataset should be used with awareness of potential ethical implications:

• Be mindful of reinforcing gender stereotypes or biases
• Consider the impacts of technology built using gender-specific datasets
• Respect privacy and consent considerations relevant to facial images