license: other
dataset_info:
features:
- name: image
dtype: image
- name: 5_o_Clock_Shadow
dtype: int64
- name: Arched_Eyebrows
dtype: int64
- name: Attractive
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
splits:
- name: train
num_bytes: 365293550
num_examples: 50000
download_size: 349853371
dataset_size: 365293550
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
pretty_name: CelebA-Smiles
size_categories:
- 10M<n<100M
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.