file
imagewidth (px) 224
224
| age
stringclasses 9
values | gender
stringclasses 2
values | race
stringclasses 7
values | service_test
bool 2
classes |
---|---|---|---|---|
50-59 | Male | East Asian | true |
|
30-39 | Female | Indian | false |
|
3-9 | Female | Black | false |
|
20-29 | Female | Indian | true |
|
20-29 | Female | Indian | true |
|
20-29 | Male | White | true |
|
40-49 | Male | Middle Eastern | false |
|
30-39 | Female | Indian | true |
|
10-19 | Male | White | true |
|
30-39 | Male | Middle Eastern | false |
|
50-59 | Male | East Asian | true |
|
20-29 | Male | East Asian | false |
|
20-29 | Male | Latino_Hispanic | false |
|
10-19 | Male | Indian | true |
|
60-69 | Female | Indian | true |
|
30-39 | Female | White | false |
|
20-29 | Female | Southeast Asian | false |
|
40-49 | Male | Southeast Asian | false |
|
0-2 | Female | Black | false |
|
50-59 | Male | Southeast Asian | true |
|
20-29 | Female | Indian | true |
|
30-39 | Female | Middle Eastern | true |
|
20-29 | Female | Black | true |
|
30-39 | Female | White | false |
|
20-29 | Female | White | false |
|
30-39 | Female | Black | true |
|
50-59 | Female | White | false |
|
10-19 | Female | White | false |
|
20-29 | Male | Indian | true |
|
20-29 | Female | Black | false |
|
40-49 | Female | Black | true |
|
10-19 | Female | East Asian | true |
|
50-59 | Male | White | false |
|
40-49 | Male | Middle Eastern | false |
|
20-29 | Male | East Asian | true |
|
60-69 | Female | Middle Eastern | true |
|
20-29 | Female | Latino_Hispanic | false |
|
30-39 | Male | Latino_Hispanic | true |
|
50-59 | Male | Middle Eastern | false |
|
20-29 | Female | Latino_Hispanic | false |
|
20-29 | Male | White | true |
|
10-19 | Female | Black | false |
|
10-19 | Female | Southeast Asian | true |
|
40-49 | Male | Latino_Hispanic | false |
|
10-19 | Male | Indian | true |
|
10-19 | Female | Indian | true |
|
60-69 | Male | East Asian | true |
|
3-9 | Female | Middle Eastern | true |
|
10-19 | Female | Southeast Asian | false |
|
50-59 | Female | Black | false |
|
3-9 | Female | East Asian | false |
|
60-69 | Male | Latino_Hispanic | false |
|
50-59 | Male | Southeast Asian | false |
|
30-39 | Female | East Asian | false |
|
30-39 | Male | Southeast Asian | true |
|
30-39 | Male | White | false |
|
20-29 | Male | Black | false |
|
40-49 | Female | Latino_Hispanic | true |
|
10-19 | Female | Latino_Hispanic | false |
|
10-19 | Female | Latino_Hispanic | true |
|
3-9 | Male | East Asian | false |
|
10-19 | Male | Indian | true |
|
40-49 | Male | Indian | false |
|
20-29 | Male | Southeast Asian | false |
|
30-39 | Male | East Asian | true |
|
30-39 | Male | Latino_Hispanic | true |
|
10-19 | Female | Latino_Hispanic | false |
|
60-69 | Male | White | false |
|
50-59 | Male | Southeast Asian | true |
|
30-39 | Male | Indian | true |
|
60-69 | Female | Indian | false |
|
30-39 | Male | Latino_Hispanic | true |
|
30-39 | Female | Latino_Hispanic | true |
|
20-29 | Female | Southeast Asian | false |
|
30-39 | Male | Indian | true |
|
20-29 | Male | Southeast Asian | true |
|
50-59 | Female | Black | true |
|
20-29 | Female | Middle Eastern | true |
|
40-49 | Male | Latino_Hispanic | false |
|
30-39 | Male | White | false |
|
30-39 | Female | Black | false |
|
30-39 | Male | Indian | false |
|
40-49 | Male | White | false |
|
10-19 | Female | Black | true |
|
20-29 | Female | White | false |
|
20-29 | Female | Black | true |
|
20-29 | Male | Black | true |
|
20-29 | Female | Southeast Asian | true |
|
40-49 | Male | Indian | false |
|
50-59 | Male | Indian | false |
|
30-39 | Male | Latino_Hispanic | false |
|
0-2 | Female | East Asian | false |
|
30-39 | Female | White | false |
|
3-9 | Female | Latino_Hispanic | false |
|
20-29 | Male | Black | false |
|
30-39 | Female | White | true |
|
30-39 | Female | White | false |
|
20-29 | Female | East Asian | false |
|
30-39 | Male | White | false |
|
20-29 | Female | East Asian | false |
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Dataset Card for FairFace
Dataset Summary
A dataset of human faces annotated with discrete categories for the photographed person's age, sex, and race. Please consider prioritizing a previously created Hugging Face dataset repository for Fair Face as this new dataset repository was only made for downloading issues that may already be resolved.
For complete details on the dataset's construction and intended uses, please refer to the dataset's official repository or paper.
Dataset Structure
Data Instances
Each instance contains an image and discrete categories for age, gender, and race.
{
'file': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=448x448>,
'age': '50-59',
'gender': 'Male',
'race': 'East Asian',
'service_test': True
}
Data Fields
file
: an image of a human face with either padding = 0.25 or padding = 1.25 depending on the dataset configage
: a category describing the age of the person in the image limited to 0-2, 3-9, 10-19, 20-29, 30-39, 40-49, 50-59, 60-69, and more than 70gender
: a category describing the sex of the person in the image limited to Male and Femalerace
: a category describing the race of the person in the image limited to East Asian, Indian, Black, White, Middle Eastern, Latino_Hispanic, and Southeast Asianservice_test
: please refer to this issue from the dataset's official repository
Additional Information
Licensing Information
According to the official repository, FairFace is licensed under CC BY 4.0.
Citation Information
@InProceedings{Karkkainen_2021_WACV,
author = {Karkkainen, Kimmo and Joo, Jungseock},
title = {FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age for Bias Measurement and Mitigation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
pages = {1548-1558}
}
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