image
imagewidth (px)
448
448
file
stringlengths
9
13
age
stringclasses
9 values
gender
stringclasses
2 values
race
stringclasses
7 values
service_test
stringclasses
2 values
image_name
stringlengths
5
9
val/1.jpg
3-9
Male
East Asian
False
1.jpg
val/2.jpg
50-59
Female
East Asian
True
2.jpg
val/3.jpg
30-39
Male
White
True
3.jpg
val/4.jpg
20-29
Female
Latino_Hispanic
True
4.jpg
val/5.jpg
20-29
Male
Southeast Asian
False
5.jpg
val/6.jpg
30-39
Male
Latino_Hispanic
False
6.jpg
val/7.jpg
20-29
Male
Black
True
7.jpg
val/8.jpg
3-9
Male
East Asian
False
8.jpg
val/9.jpg
20-29
Male
Southeast Asian
False
9.jpg
val/10.jpg
3-9
Male
Southeast Asian
False
10.jpg
val/11.jpg
more than 70
Female
East Asian
True
11.jpg
val/12.jpg
50-59
Female
East Asian
True
12.jpg
val/13.jpg
40-49
Female
Indian
True
13.jpg
val/14.jpg
20-29
Male
Indian
True
14.jpg
val/15.jpg
30-39
Female
Latino_Hispanic
False
15.jpg
val/16.jpg
50-59
Male
Middle Eastern
True
16.jpg
val/17.jpg
30-39
Male
East Asian
False
17.jpg
val/18.jpg
20-29
Female
White
False
18.jpg
val/19.jpg
40-49
Male
White
False
19.jpg
val/20.jpg
40-49
Female
Middle Eastern
True
20.jpg
val/21.jpg
20-29
Male
East Asian
True
21.jpg
val/22.jpg
40-49
Male
White
False
22.jpg
val/23.jpg
30-39
Female
White
True
23.jpg
val/24.jpg
10-19
Female
East Asian
False
24.jpg
val/25.jpg
20-29
Female
Latino_Hispanic
False
25.jpg
val/26.jpg
30-39
Female
Latino_Hispanic
False
26.jpg
val/27.jpg
20-29
Female
Latino_Hispanic
True
27.jpg
val/28.jpg
20-29
Female
Southeast Asian
True
28.jpg
val/29.jpg
3-9
Female
East Asian
False
29.jpg
val/30.jpg
30-39
Female
Latino_Hispanic
False
30.jpg
val/31.jpg
3-9
Female
Indian
True
31.jpg
val/32.jpg
40-49
Female
Indian
False
32.jpg
val/33.jpg
20-29
Male
Southeast Asian
True
33.jpg
val/34.jpg
3-9
Male
East Asian
False
34.jpg
val/35.jpg
60-69
Male
Black
True
35.jpg
val/36.jpg
50-59
Female
Black
False
36.jpg
val/37.jpg
40-49
Male
Black
True
37.jpg
val/38.jpg
40-49
Male
Middle Eastern
False
38.jpg
val/39.jpg
60-69
Male
Middle Eastern
False
39.jpg
val/40.jpg
50-59
Female
Indian
False
40.jpg
val/41.jpg
3-9
Male
East Asian
False
41.jpg
val/42.jpg
20-29
Female
Indian
False
42.jpg
val/43.jpg
20-29
Female
Latino_Hispanic
False
43.jpg
val/44.jpg
30-39
Female
Latino_Hispanic
False
44.jpg
val/45.jpg
0-2
Male
White
False
45.jpg
val/46.jpg
20-29
Male
East Asian
False
46.jpg
val/47.jpg
40-49
Male
White
True
47.jpg
val/48.jpg
20-29
Female
White
True
48.jpg
val/49.jpg
40-49
Male
White
False
49.jpg
val/50.jpg
20-29
Female
White
True
50.jpg
val/51.jpg
30-39
Male
Middle Eastern
False
51.jpg
val/52.jpg
3-9
Male
Middle Eastern
True
52.jpg
val/53.jpg
50-59
Male
Latino_Hispanic
False
53.jpg
val/54.jpg
20-29
Male
East Asian
False
54.jpg
val/55.jpg
40-49
Male
Latino_Hispanic
False
55.jpg
val/56.jpg
40-49
Male
White
False
56.jpg
val/57.jpg
40-49
Female
East Asian
True
57.jpg
val/58.jpg
3-9
Male
Black
False
58.jpg
val/59.jpg
30-39
Female
White
False
59.jpg
val/60.jpg
10-19
Female
Southeast Asian
True
60.jpg
val/61.jpg
60-69
Male
Black
False
61.jpg
val/62.jpg
3-9
Male
Southeast Asian
True
62.jpg
val/63.jpg
3-9
Female
White
False
63.jpg
val/64.jpg
10-19
Male
East Asian
False
64.jpg
val/65.jpg
40-49
Male
Latino_Hispanic
False
65.jpg
val/66.jpg
30-39
Female
Latino_Hispanic
True
66.jpg
val/67.jpg
40-49
Female
White
True
67.jpg
val/68.jpg
3-9
Female
White
True
68.jpg
val/69.jpg
30-39
Male
Latino_Hispanic
True
69.jpg
val/70.jpg
20-29
Male
Indian
True
70.jpg
val/71.jpg
more than 70
Male
Middle Eastern
True
71.jpg
val/72.jpg
30-39
Male
White
False
72.jpg
val/73.jpg
20-29
Female
Latino_Hispanic
False
73.jpg
val/74.jpg
30-39
Female
Indian
False
74.jpg
val/75.jpg
50-59
Male
Middle Eastern
True
75.jpg
val/76.jpg
20-29
Male
Indian
True
76.jpg
val/77.jpg
40-49
Female
Latino_Hispanic
True
77.jpg
val/78.jpg
30-39
Male
Black
False
78.jpg
val/79.jpg
3-9
Female
Middle Eastern
True
79.jpg
val/80.jpg
30-39
Female
Black
False
80.jpg
val/81.jpg
30-39
Male
Black
False
81.jpg
val/82.jpg
10-19
Male
East Asian
False
82.jpg
val/83.jpg
30-39
Female
White
False
83.jpg
val/84.jpg
40-49
Male
East Asian
False
84.jpg
val/85.jpg
3-9
Female
White
False
85.jpg
val/86.jpg
10-19
Male
Black
False
86.jpg
val/87.jpg
30-39
Male
White
False
87.jpg
val/88.jpg
20-29
Male
Southeast Asian
True
88.jpg
val/89.jpg
30-39
Male
East Asian
False
89.jpg
val/90.jpg
50-59
Male
Middle Eastern
False
90.jpg
val/91.jpg
10-19
Female
Indian
True
91.jpg
val/92.jpg
10-19
Male
White
False
92.jpg
val/93.jpg
20-29
Female
Indian
True
93.jpg
val/94.jpg
50-59
Female
Latino_Hispanic
False
94.jpg
val/95.jpg
50-59
Female
East Asian
True
95.jpg
val/96.jpg
30-39
Male
White
False
96.jpg
val/97.jpg
50-59
Female
Indian
True
97.jpg
val/98.jpg
20-29
Male
East Asian
False
98.jpg
val/99.jpg
20-29
Male
East Asian
True
99.jpg
val/100.jpg
20-29
Female
East Asian
True
100.jpg
YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)

FairFace (val set)

Original paper: Fairface: Face attribute dataset for balanced race, gender, and age for bias measurement and mitigation

Homepage: https://github.com/joojs/fairface

Bibtex:

@inproceedings{karkkainenfairface,
  title={FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age for Bias Measurement and Mitigation},
  author={Karkkainen, Kimmo and Joo, Jungseock},
  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
  year={2021},
  pages={1548--1558}
}
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