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

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 config
  • age: 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 70
  • gender: a category describing the sex of the person in the image limited to Male and Female
  • race: a category describing the race of the person in the image limited to East Asian, Indian, Black, White, Middle Eastern, Latino_Hispanic, and Southeast Asian
  • service_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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