Facial Recognition - Emotional Poses
If you are out to build a model to classify expressions of human emotion, this is the dataset you are looking for. This dataset has more than 500K images of people of a variety of ages, genders and ethnicities, each expressing a range of emotions.
If you are out to build a model to classify expressions of human emotion, this is the dataset you are looking for. This dataset has more than 500K images of people of a variety of ages, genders and ethnicities, each expressing a range of emotions.
If you are out to build a model to classify expressions of human emotion, this is the dataset you are looking for. This dataset has more than 500K images of people of a variety of ages, genders and ethnicities, each expressing a range of emotions.
If you are out to build a model to classify expressions of human emotion, this is the dataset you are looking for. This dataset has more than 500K images of people of a variety of ages, genders and ethnicities, each expressing a range of emotions.
Dataset specs
Type
Image
Region/Locale
NO,
EL,
NE,
la,
si-lk,
brx-in,
nl-NL,
tl-PH,
or-in,
et-ee,
haz-af,
ca-es,
gjr-in,
ro-ro,
tcy-in,
bto-ph,
qaz-ir,
eu-es,
haw-us,
he-IL,
nb-NO,
ml-in,
ZH,
zh-CN,
en-AU,
dhd-in,
wuu-cn,
mni-in,
gl-es,
ahr-in,
pt-PT,
af-za,
hu-hu,
fi-fi,
gon-in,
bn-IN,
LV,
ar-LAV,
ar-SD,
KO,
MS,
AR,
pa-IN,
ta-IN,
te-IN,
es-ES,
it-IT,
en-GB,
fr-MX,
de-DE,
en-US,
en-IN,
fr-FR,
TH,
HE,
SO,
ZU,
TL,
SR,
EN,
DA,
VI,
mr-IN,
hi-IN,
ID,
pl-PL,
kn-IN,
FA,
UR,
fr-CA,
TR,
YUE,
es-MX,
CZ,
es-AR,
JA,
sv-SE,
DE,
RU,
FR,
pt-BR,
es-VE,
ar-MA,
ar-LB,
hi-US,
fr-MA,
ar-TN,
es-US,
ar-JO,
ar-JS,
ar-IQ,
ar-YE,
ar-DZ,
ar-AR,
de-US,
ar-EG,
ja-JP,
ar-SA,
ar-AE,
es-BO,
ar-TR,
ja-US,
es-PE,
ar-Kw,
es-EC,
es-LA,
es-CO,
es-CL,
fr-US,
en-CA,
ko-KR,
da-DK,
ru-RU,
nl-BE,
cs-CZ,
vi-VN,
gu-IN,
ar-MSA,
fa-IR,
en-IE,
is-is,
sk-sk,
lt-lt,
uk-ua,
rmn-ro,
cy-gb,
kxu-in,
sgs-lt,
la-latn
Amount
550.4K images
Leverage
Train AI models to accurately recognize individual's expressions across diverse ethnicities, genders, and age groups
Use cases
Train AI models to recognize emotions and analyze sentiment from facial expressions in real-world selfie images, supporting emotion-aware and sentiment-driven applications.
Assess and reduce demographic bias by evaluating recognition performance across age groups and genders.
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Dataset specs
Type
Image
Region/Locale
NO,
EL,
NE,
la,
si-lk,
brx-in,
nl-NL,
tl-PH,
or-in,
et-ee,
haz-af,
ca-es,
gjr-in,
ro-ro,
tcy-in,
bto-ph,
qaz-ir,
eu-es,
haw-us,
he-IL,
nb-NO,
ml-in,
ZH,
zh-CN,
en-AU,
dhd-in,
wuu-cn,
mni-in,
gl-es,
ahr-in,
pt-PT,
af-za,
hu-hu,
fi-fi,
gon-in,
bn-IN,
LV,
ar-LAV,
ar-SD,
KO,
MS,
AR,
pa-IN,
ta-IN,
te-IN,
es-ES,
it-IT,
en-GB,
fr-MX,
de-DE,
en-US,
en-IN,
fr-FR,
TH,
HE,
SO,
ZU,
TL,
SR,
EN,
DA,
VI,
mr-IN,
hi-IN,
ID,
pl-PL,
kn-IN,
FA,
UR,
fr-CA,
TR,
YUE,
es-MX,
CZ,
es-AR,
JA,
sv-SE,
DE,
RU,
FR,
pt-BR,
es-VE,
ar-MA,
ar-LB,
hi-US,
fr-MA,
ar-TN,
es-US,
ar-JO,
ar-JS,
ar-IQ,
ar-YE,
ar-DZ,
ar-AR,
de-US,
ar-EG,
ja-JP,
ar-SA,
ar-AE,
es-BO,
ar-TR,
ja-US,
es-PE,
ar-Kw,
es-EC,
es-LA,
es-CO,
es-CL,
fr-US,
en-CA,
ko-KR,
da-DK,
ru-RU,
nl-BE,
cs-CZ,
vi-VN,
gu-IN,
ar-MSA,
fa-IR,
en-IE,
is-is,
sk-sk,
lt-lt,
uk-ua,
rmn-ro,
cy-gb,
kxu-in,
sgs-lt,
la-latn
Amount
550.4K images