Human Generated Data

Title

Defectives, Epileptics: United States. Massachusetts. Palmer. State Hospital for Epileptics: Group of least efficient workers

Date

1901

People

Artist: Woodhead Studio, American active 1900s

Classification

Photographs

Human Generated Data

Title

Defectives, Epileptics: United States. Massachusetts. Palmer. State Hospital for Epileptics: Group of least efficient workers

People

Artist: Woodhead Studio, American active 1900s

Date

1901

Classification

Photographs

Machine Generated Data

Tags

Amazon

Human 99.6
Person 99.6
Poster 99.2
Advertisement 99.2
Person 99.1
Person 98.7
Person 96.2
Person 93.3
Person 86.7
People 83.9
Person 81.4
Person 81
Person 74.1
Person 71.2
Person 70.4
Face 70
Person 67.1
Text 64.7
Clothing 61.5
Suit 61.5
Overcoat 61.5
Coat 61.5
Apparel 61.5
Sailor Suit 57.9
Person 55
Person 46.4

Clarifai

people 99.7
adult 99.3
group 98.8
wear 97.5
art 96.1
man 95.7
many 95.5
woman 93.7
illustration 92.8
leader 91.7
furniture 90.2
painting 89.4
outfit 88.4
wall 86.6
print 84.8
room 84.3
one 84.1
portrait 83.5
vintage 83.2
old 82.2

Imagga

envelope 56.8
container 48.4
old 39
grunge 38.3
vintage 33.9
paper 32.1
retro 31.1
texture 28.5
aged 26.2
antique 25.9
wall 23.2
dirty 21.7
ancient 21.6
frame 20.8
rusty 19
empty 18.9
border 18.1
design 17
pattern 16.4
currency 16.1
grungy 16.1
blank 15.4
wallpaper 15.3
art 15.1
textured 14.9
money 14.5
damaged 14.3
note 13.8
letter 13.7
stamp 13.7
finance 13.5
decay 13.5
material 13.4
bill 13.3
backdrop 13.2
blade 12
close 12
cash 11.9
tray 11.7
business 11.5
parchment 11.5
detail 11.3
grain 11.1
card 11
message 11
postage 10.8
bank 10.7
grime 10.7
box 10.7
crumpled 10.7
backgrounds 10.5
mail 10.5
worn 10.5
old fashioned 10.5
decoration 10.3
brown 10.3
space 10.1
postmark 9.8
ragged 9.7
board 9.7
states 9.7
stained 9.6
receptacle 9.5
color 9.5
map 9.3
page 9.3
cutting implement 9.2
global 9.1
rough 9.1
paint 9
bag 9
history 8.9
financial 8.9
style 8.9
surface 8.8
structure 8.8
graphic 8.7
banknote 8.7
crack 8.7
rust 8.7
stain 8.6
cardboard 8.6
united 8.6
floral 8.5
historic 8.2
wallet 8.1
packet 8
atlas 8
postal 7.8
mottled 7.8
fracture 7.8
stains 7.8
hundred 7.7
torn 7.7
messy 7.7
geography 7.7
spot 7.7
international 7.6
post 7.6
savings 7.5
dollar 7.4
symbol 7.4
banking 7.3
case 7.3
artwork 7.3
wealth 7.2
package 7.2
world 7.1

Microsoft

person 98.6
clothing 91.3
man 74.7
picture frame 11.7

Face analysis

Amazon

AWS Rekognition

Age 16-27
Gender Female, 50.2%
Confused 49.6%
Surprised 49.6%
Sad 49.8%
Calm 49.6%
Happy 49.6%
Angry 49.6%
Disgusted 49.8%

AWS Rekognition

Age 26-43
Gender Male, 50.5%
Calm 50.1%
Disgusted 49.5%
Sad 49.7%
Happy 49.5%
Confused 49.6%
Surprised 49.5%
Angry 49.6%

AWS Rekognition

Age 23-38
Gender Female, 50.2%
Disgusted 49.5%
Happy 49.5%
Surprised 49.5%
Calm 49.6%
Angry 49.6%
Confused 49.5%
Sad 50.2%

AWS Rekognition

Age 30-47
Gender Female, 50.4%
Happy 49.5%
Disgusted 49.5%
Calm 49.5%
Sad 50.4%
Confused 49.5%
Surprised 49.5%
Angry 49.5%

AWS Rekognition

Age 26-43
Gender Female, 50.3%
Confused 49.5%
Surprised 49.5%
Sad 49.6%
Calm 49.7%
Happy 49.6%
Angry 50%
Disgusted 49.5%

AWS Rekognition

Age 26-43
Gender Female, 50.1%
Calm 50%
Angry 49.6%
Happy 49.5%
Surprised 49.5%
Confused 49.5%
Disgusted 49.6%
Sad 49.6%

AWS Rekognition

Age 26-43
Gender Female, 50.4%
Sad 49.7%
Calm 49.6%
Disgusted 49.6%
Confused 49.5%
Angry 50%
Surprised 49.6%
Happy 49.6%

AWS Rekognition

Age 35-52
Gender Male, 50.4%
Disgusted 49.6%
Confused 49.5%
Calm 49.8%
Angry 49.8%
Happy 49.6%
Sad 49.7%
Surprised 49.5%

AWS Rekognition

Age 35-53
Gender Male, 51.3%
Calm 45.1%
Sad 54.4%
Surprised 45%
Disgusted 45.1%
Happy 45.1%
Angry 45.2%
Confused 45.1%

AWS Rekognition

Age 26-43
Gender Male, 50.5%
Confused 49.5%
Surprised 49.7%
Angry 49.5%
Calm 50.2%
Sad 49.5%
Happy 49.5%
Disgusted 49.5%

AWS Rekognition

Age 20-38
Gender Male, 50.2%
Calm 49.6%
Confused 49.6%
Disgusted 49.8%
Happy 49.6%
Angry 49.8%
Sad 49.6%
Surprised 49.6%

AWS Rekognition

Age 20-38
Gender Male, 50.1%
Angry 49.6%
Disgusted 49.5%
Sad 50.3%
Calm 49.6%
Happy 49.5%
Surprised 49.5%
Confused 49.5%

AWS Rekognition

Age 38-57
Gender Male, 50.5%
Disgusted 49.5%
Confused 49.6%
Surprised 49.5%
Calm 49.9%
Happy 49.7%
Angry 49.6%
Sad 49.6%

AWS Rekognition

Age 35-52
Gender Female, 50.1%
Sad 50.2%
Disgusted 49.5%
Angry 49.5%
Surprised 49.5%
Calm 49.6%
Confused 49.5%
Happy 49.7%

AWS Rekognition

Age 35-52
Gender Female, 50.2%
Sad 49.7%
Disgusted 49.5%
Angry 49.5%
Surprised 49.5%
Calm 50.2%
Confused 49.5%
Happy 49.5%

AWS Rekognition

Age 45-63
Gender Male, 52.6%
Angry 54.5%
Calm 45%
Surprised 45%
Disgusted 45%
Happy 45.1%
Sad 45.2%
Confused 45%

AWS Rekognition

Age 48-68
Gender Male, 50.5%
Confused 49.6%
Angry 49.6%
Disgusted 49.5%
Surprised 49.5%
Sad 50.1%
Calm 49.6%
Happy 49.6%

AWS Rekognition

Age 20-38
Gender Male, 50.2%
Sad 49.9%
Disgusted 49.7%
Confused 49.5%
Happy 49.6%
Calm 49.6%
Surprised 49.5%
Angry 49.7%

AWS Rekognition

Age 23-38
Gender Female, 50.3%
Sad 50.1%
Confused 49.5%
Angry 49.6%
Calm 49.6%
Surprised 49.5%
Happy 49.7%
Disgusted 49.5%

AWS Rekognition

Age 35-52
Gender Male, 50.4%
Disgusted 49.5%
Happy 49.5%
Calm 49.6%
Angry 49.9%
Surprised 49.5%
Confused 49.6%
Sad 49.8%

AWS Rekognition

Age 35-52
Gender Female, 50.3%
Angry 49.5%
Surprised 49.5%
Happy 50%
Disgusted 49.6%
Sad 49.7%
Confused 49.5%
Calm 49.5%

AWS Rekognition

Age 35-52
Gender Male, 50.5%
Surprised 49.5%
Disgusted 49.5%
Sad 49.6%
Calm 49.7%
Happy 49.5%
Confused 49.5%
Angry 50.1%

AWS Rekognition

Age 26-43
Gender Female, 50.4%
Calm 49.5%
Angry 49.6%
Sad 50%
Happy 49.6%
Confused 49.5%
Surprised 49.5%
Disgusted 49.8%

Feature analysis

Amazon

Person 99.6%
Poster 99.2%

Text analysis

Amazon

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sHficiens
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amyp leat sHficiens wm keo
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