Datasets:

HuggingFaceM4
/

FairFace

age class label 9 classes	gender class label 2 classes	race class label 7 classes	service_test bool 2 classes
650-59	0Male	0East Asian	true
430-39	1Female	1Indian	false
13-9	1Female	2Black	false
320-29	1Female	1Indian	true
320-29	1Female	1Indian	true
320-29	0Male	3White	true
540-49	0Male	4Middle Eastern	false
430-39	1Female	1Indian	true
210-19	0Male	3White	true
430-39	0Male	4Middle Eastern	false
650-59	0Male	0East Asian	true
320-29	0Male	0East Asian	false
320-29	0Male	5Latino_Hispanic	false
210-19	0Male	1Indian	true
760-69	1Female	1Indian	true
430-39	1Female	3White	false
320-29	1Female	6Southeast Asian	false
540-49	0Male	6Southeast Asian	false
00-2	1Female	2Black	false
650-59	0Male	6Southeast Asian	true
320-29	1Female	1Indian	true
430-39	1Female	4Middle Eastern	true
320-29	1Female	2Black	true
430-39	1Female	3White	false
320-29	1Female	3White	false
430-39	1Female	2Black	true
650-59	1Female	3White	false
210-19	1Female	3White	false
320-29	0Male	1Indian	true
320-29	1Female	2Black	false
540-49	1Female	2Black	true
210-19	1Female	0East Asian	true
650-59	0Male	3White	false
540-49	0Male	4Middle Eastern	false
320-29	0Male	0East Asian	true
760-69	1Female	4Middle Eastern	true
320-29	1Female	5Latino_Hispanic	false
430-39	0Male	5Latino_Hispanic	true
650-59	0Male	4Middle Eastern	false
320-29	1Female	5Latino_Hispanic	false
320-29	0Male	3White	true
210-19	1Female	2Black	false
210-19	1Female	6Southeast Asian	true
540-49	0Male	5Latino_Hispanic	false
210-19	0Male	1Indian	true
210-19	1Female	1Indian	true
760-69	0Male	0East Asian	true
13-9	1Female	4Middle Eastern	true
210-19	1Female	6Southeast Asian	false
650-59	1Female	2Black	false
13-9	1Female	0East Asian	false
760-69	0Male	5Latino_Hispanic	false
650-59	0Male	6Southeast Asian	false
430-39	1Female	0East Asian	false
430-39	0Male	6Southeast Asian	true
430-39	0Male	3White	false
320-29	0Male	2Black	false
540-49	1Female	5Latino_Hispanic	true
210-19	1Female	5Latino_Hispanic	false
210-19	1Female	5Latino_Hispanic	true
13-9	0Male	0East Asian	false
210-19	0Male	1Indian	true
540-49	0Male	1Indian	false
320-29	0Male	6Southeast Asian	false
430-39	0Male	0East Asian	true
430-39	0Male	5Latino_Hispanic	true
210-19	1Female	5Latino_Hispanic	false
760-69	0Male	3White	false
650-59	0Male	6Southeast Asian	true
430-39	0Male	1Indian	true
760-69	1Female	1Indian	false
430-39	0Male	5Latino_Hispanic	true
430-39	1Female	5Latino_Hispanic	true
320-29	1Female	6Southeast Asian	false
430-39	0Male	1Indian	true
320-29	0Male	6Southeast Asian	true
650-59	1Female	2Black	true
320-29	1Female	4Middle Eastern	true
540-49	0Male	5Latino_Hispanic	false
430-39	0Male	3White	false
430-39	1Female	2Black	false
430-39	0Male	1Indian	false
540-49	0Male	3White	false
210-19	1Female	2Black	true
320-29	1Female	3White	false
320-29	1Female	2Black	true
320-29	0Male	2Black	true
320-29	1Female	6Southeast Asian	true
540-49	0Male	1Indian	false
650-59	0Male	1Indian	false
430-39	0Male	5Latino_Hispanic	false
00-2	1Female	0East Asian	false
430-39	1Female	3White	false
13-9	1Female	5Latino_Hispanic	false
320-29	0Male	2Black	false
430-39	1Female	3White	true
430-39	1Female	3White	false
320-29	1Female	0East Asian	false
430-39	0Male	3White	false
320-29	1Female	0East Asian	false

End of preview. Expand in Data Studio

Dataset Card for FairFace

Dataset Summary

FairFace is a face image dataset which is race balanced. It contains 108,501 images from 7 different race groups: White, Black, Indian, East Asian, Southeast Asian, Middle Eastern, and Latino. Images were collected from the YFCC-100M Flickr dataset and labeled with race, gender, and age groups.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

[More Information Needed]

Dataset Structure

Data Instances

Each instance has the following structure:

{
    'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=448x448 at 0x7FCABA221FA0>,
    'age': 6,
    'gender': 0,
    'race': 0,
    'service_test': True
}

Data Fields

image: The image
age: Age class among ["0-2", "3-9", "10-19", "20-29", "30-39", "40-49", "50-59", "60-69", "more than 70"]
gender: Gender class among ["Male", "Female"]
race: Race class among ["East Asian", "Indian", "Black", "White", "Middle Eastern", "Latino_Hispanic", "Southeast Asian"]
service_test: Not sure what this is. See issue.