Human Generated Data

Title

Education, Industrial: United States. New York. New York City. Public Schools, Adaptation to Special City Needs: Agencies Promoting the Assimilation of the Immigrant. Imparting American Standards to the Foreign Born. New York City Public Schools. Examples of Adaptation of Education to Special City Needs: English Lessons to Foreigners. Evening. Public School No. 160 Manhattan.
Date

c. 1900
People

Artist: Unidentified Artist,

Classification

Photographs
Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, Social Museum Collection, 3.2002.245.2

Human Generated Data

Title

Education, Industrial: United States. New York. New York City. Public Schools, Adaptation to Special City Needs: Agencies Promoting the Assimilation of the Immigrant. Imparting American Standards to the Foreign Born. New York City Public Schools. Examples of Adaptation of Education to Special City Needs: English Lessons to Foreigners. Evening. Public School No. 160 Manhattan.

People

Artist: Unidentified Artist,

Date

c. 1900

Classification

Photographs

Machine Generated Data

Tags

Amazon
created on 2022-06-25

Restaurant 99.6
Person 99.5
Human 99.5
Person 98.7
Person 98
Person 97.6
Person 96.5
Person 94
Person 92.9
Cafeteria 92.5
Person 89.9
Person 80
Clinic 79.2
Person 75.7
Person 70.2
Person 68.4
Cafe 61.8
Room 57.2
Indoors 57.2
Building 56.3
School 55.8
Person 50.2

Imagga
created on 2022-06-25

room 28
man 26.9
people 23.4
restaurant 21.9
table 19.9
classroom 18.1
interior 16.8
person 16.3
musical instrument 15.2
male 14.9
indoors 14
building 14
business 14
men 13.7
chair 11.7
life 11.5
light 11.3
couple 11.3
work 11
black 10.8
night 10.6
adult 10.1
office 10
brass 9.9
family 9.8
furniture 9.7
group 9.7
hall 9.5
smiling 9.4
wind instrument 9.3
window 9.3
city 9.1
old 9
design 9
businessman 8.8
home 8.8
lamp 8.8
musician 8.7
party 8.6
architecture 8.6
sitting 8.6
house 8.3
uniform 8.3
fashion 8.3
lifestyle 7.9
love 7.9
teacher 7.9
happiness 7.8
chairs 7.8
stage 7.8
professional 7.5
silhouette 7.4
percussion instrument 7.4
music 7.4
inside 7.4
street 7.4
occupation 7.3
indoor 7.3
singer 7.1

Google
created on 2022-06-25

Furniture 94.4
Table 93.2
Chair 91.5
Suit 79.3
Monochrome 73.7
Event 73.4
Vintage clothing 71.7
Monochrome photography 69.3
Building 68.8
Room 68.5
Crowd 65.5
History 65.3
Class 58.5
Recreation 58.5
Art 55.6
Cafeteria 52.6

Microsoft
created on 2022-06-25

person 98.8
clothing 94.4
table 90.8
group 89.4
furniture 88.8
chair 78.6
people 77.1
text 62.5
man 61
old 56.3
posing 50.7

Face analysis

Amazon

Google

AWS Rekognition

Age 19-27
Gender Male, 100%
Calm 84.2%
Surprised 8.3%
Fear 7.6%
Sad 3%
Disgusted 2%
Happy 1.6%
Angry 1.4%
Confused 0.6%

AWS Rekognition

Age 23-33
Gender Male, 96.6%
Sad 30.2%
Calm 24.9%
Angry 13.3%
Surprised 12.6%
Disgusted 11.2%
Fear 8.8%
Confused 8%
Happy 6.2%

AWS Rekognition

Age 27-37
Gender Male, 96.8%
Calm 96.9%
Surprised 6.4%
Fear 5.9%
Sad 2.3%
Confused 1.4%
Angry 0.4%
Disgusted 0.2%
Happy 0.2%

AWS Rekognition

Age 23-31
Gender Male, 99.8%
Calm 86.2%
Surprised 6.6%
Fear 6.4%
Sad 4.9%
Angry 2.7%
Happy 1.9%
Confused 0.6%
Disgusted 0.6%

AWS Rekognition

Age 18-26
Gender Male, 99%
Calm 94.5%
Surprised 6.8%
Fear 6%
Sad 2.7%
Happy 0.7%
Confused 0.7%
Angry 0.6%
Disgusted 0.5%

AWS Rekognition

Age 22-30
Gender Male, 98.7%
Angry 92.5%
Surprised 6.4%
Fear 6.1%
Sad 3.3%
Calm 2.3%
Disgusted 0.9%
Confused 0.2%
Happy 0.2%

AWS Rekognition

Age 21-29
Gender Female, 69.3%
Sad 98.1%
Calm 29%
Happy 9.2%
Surprised 7.6%
Fear 6.1%
Angry 2.3%
Confused 1.1%
Disgusted 0.9%

AWS Rekognition

Age 29-39
Gender Female, 89.8%
Calm 98.5%
Surprised 6.3%
Fear 5.9%
Sad 2.3%
Happy 0.6%
Angry 0.1%
Disgusted 0.1%
Confused 0.1%

AWS Rekognition

Age 43-51
Gender Male, 96.3%
Calm 86.3%
Sad 11.6%
Surprised 6.3%
Fear 5.9%
Confused 0.4%
Disgusted 0.2%
Happy 0.1%
Angry 0.1%

AWS Rekognition

Age 33-41
Gender Male, 99.9%
Sad 100%
Calm 8.4%
Surprised 6.4%
Fear 6%
Confused 2.3%
Disgusted 0.8%
Angry 0.2%
Happy 0.1%

AWS Rekognition

Age 24-34
Gender Male, 82.1%
Calm 98%
Surprised 6.7%
Fear 5.9%
Sad 2.3%
Happy 0.2%
Angry 0.2%
Disgusted 0.1%
Confused 0.1%

AWS Rekognition

Age 26-36
Gender Male, 99.2%
Angry 44.1%
Calm 44%
Surprised 6.9%
Fear 6.7%
Happy 4.2%
Sad 3%
Disgusted 1.3%
Confused 0.8%

AWS Rekognition

Age 20-28
Gender Male, 99.5%
Calm 95.7%
Surprised 6.3%
Fear 5.9%
Sad 3.7%
Confused 0.1%
Angry 0.1%
Disgusted 0.1%
Happy 0%

AWS Rekognition

Age 28-38
Gender Male, 100%
Calm 99%
Surprised 6.3%
Fear 5.9%
Sad 2.4%
Happy 0.1%
Confused 0%
Disgusted 0%
Angry 0%

AWS Rekognition

Age 23-31
Gender Female, 93.9%
Calm 88%
Sad 8.6%
Surprised 6.5%
Fear 5.9%
Confused 0.4%
Angry 0.3%
Disgusted 0.3%
Happy 0.2%

AWS Rekognition

Age 21-29
Gender Female, 99.6%
Calm 98.9%
Surprised 6.3%
Fear 5.9%
Sad 2.4%
Angry 0.1%
Disgusted 0%
Confused 0%
Happy 0%

AWS Rekognition

Age 34-42
Gender Male, 99.7%
Calm 99.4%
Surprised 6.3%
Fear 5.9%
Sad 2.2%
Confused 0.1%
Angry 0%
Disgusted 0%
Happy 0%

AWS Rekognition

Age 25-35
Gender Male, 99.4%
Surprised 63.1%
Calm 38.2%
Fear 11.6%
Confused 8.2%
Sad 2.8%
Angry 1.2%
Disgusted 0.9%
Happy 0.8%

AWS Rekognition

Age 47-53
Gender Male, 95.8%
Calm 78.8%
Surprised 12.3%
Fear 6.5%
Happy 3.6%
Sad 3.2%
Angry 2.2%
Disgusted 1.1%
Confused 0.9%

AWS Rekognition

Age 29-39
Gender Male, 100%
Calm 62.8%
Happy 27%
Surprised 7.1%
Fear 6.6%
Sad 3.8%
Angry 1.2%
Disgusted 1.2%
Confused 0.3%

AWS Rekognition

Age 19-27
Gender Female, 58.9%
Calm 73.7%
Sad 15.7%
Surprised 7%
Fear 6.4%
Confused 4.1%
Angry 1.8%
Happy 1.6%
Disgusted 1.1%

AWS Rekognition

Age 19-27
Gender Male, 99.7%
Calm 70.8%
Surprised 10.7%
Angry 9.4%
Fear 7.4%
Sad 4%
Happy 1.7%
Confused 1.7%
Disgusted 1.5%

AWS Rekognition

Age 23-31
Gender Male, 97.9%
Calm 61.3%
Sad 52.1%
Surprised 7.1%
Fear 6.8%
Happy 2.3%
Angry 2%
Disgusted 1.7%
Confused 1.7%

AWS Rekognition

Age 20-28
Gender Male, 99.9%
Calm 89.3%
Surprised 7.4%
Fear 6.1%
Sad 3.9%
Happy 1.2%
Angry 1.1%
Confused 0.9%
Disgusted 0.6%

AWS Rekognition

Age 37-45
Gender Female, 82.9%
Calm 85.7%
Surprised 6.8%
Fear 6%
Happy 5.1%
Sad 4.5%
Confused 1%
Angry 0.7%
Disgusted 0.6%

AWS Rekognition

Age 22-30
Gender Male, 99.4%
Sad 39.9%
Calm 26.6%
Angry 24.1%
Confused 13.5%
Fear 7.7%
Surprised 7.4%
Happy 3.2%
Disgusted 2.4%

AWS Rekognition

Age 16-24
Gender Male, 69.6%
Sad 99.4%
Calm 16.6%
Disgusted 7.2%
Angry 7.1%
Surprised 6.9%
Fear 6.3%
Confused 3.4%
Happy 0.9%

AWS Rekognition

Age 23-31
Gender Male, 99.5%
Calm 45.7%
Fear 16%
Sad 10.9%
Angry 10.5%
Surprised 7%
Disgusted 5.9%
Happy 4.8%
Confused 3.1%

AWS Rekognition

Age 14-22
Gender Female, 98.1%
Calm 59.2%
Sad 16.6%
Fear 9%
Surprised 8%
Happy 7.6%
Confused 4.2%
Angry 2%
Disgusted 1.4%

AWS Rekognition

Age 37-45
Gender Female, 54.3%
Calm 80.6%
Happy 13.8%
Surprised 6.4%
Fear 6%
Sad 2.8%
Angry 1.9%
Confused 0.6%
Disgusted 0.5%

AWS Rekognition

Age 18-26
Gender Male, 99.8%
Fear 59.6%
Confused 24.5%
Surprised 14.6%
Sad 10.6%
Happy 2.2%
Disgusted 1.5%
Angry 1%
Calm 0.9%

AWS Rekognition

Age 20-28
Gender Female, 50.8%
Calm 95.2%
Surprised 6.5%
Fear 6%
Sad 3%
Happy 0.7%
Confused 0.6%
Disgusted 0.1%
Angry 0.1%

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very likely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Likely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Likely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very likely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Likely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very likely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Feature analysis

Amazon

Person 99.5%

Captions

Microsoft

a group of people standing in front of a crowd posing for the camera 94.6%
a group of people posing for a photo 94.5%
a group of people posing for a photo in front of a crowd 94.4%

Text analysis

Amazon

with
c48
of
with Our
of Seat
EVC.P.S.160.MAN.
Seat
Our

Google

HU e 48. Evd. P.S.160.MAN.
HU
e
48
.
Evd
P.S.160.MAN