CelebA-Smiles

Overview

This dataset is a subset of the CelebFaces Attributes Dataset. The dataset can be employed as the training and test sets for computer vision tasks like smile detection.

Dataset Details

The CelebA-Smiles dataset is a smaller version of the original dataset. This data originally came from CelebFaces Attributes Dataset (CelebA)

The original dataset contains : CelebFaces Attributes Dataset (CelebA) is a large-scale face attributes dataset with more than 200K celebrity images, each with 40 attribute annotations. The images in this dataset cover large pose variations and background clutter. CelebA has large diversities, large quantities, and rich annotations, including

• 10,177 number of identities
• 202,599 face images
• 5 landmark locations
• 40 binary attribute annotations per image.

The dataset can be employed as the training and test sets for the following computer vision tasks: face attribute recognition, face recognition, face detection, landmark (or facial part) localization, and face editing & synthesis.

@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} 
}

• Dataset Name: CelebA-Smiles
• Language: English
• Total Size: 50,000 demonstrations

Contents

The subset dataset consists of images of celebrity people with 40 attributes. The CelebA-Smile dataset is balanced with 50% people smiling and 50% people not smiling, it also contains the other 39 attributes like "5_o_Clock_Shadow", "Arched_Eyebrows", "Attractive", "Bags_Under_Eyes", "bald", etc.

How to use

from datasets import load_dataset

dataset = load_dataset("AiresPucrs/CelebA-Smiles", split='train')

License

The dataset is licensed under the Other.