Machine Generated Data
Tags
Amazon
created on 2022-01-15
Clarifai
created on 2023-10-25
Imagga
created on 2022-01-15
people | 25.1 | |
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man | 23.5 | |
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city | 20.8 | |
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business | 20 | |
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urban | 18.3 | |
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clothing | 17.1 | |
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male | 16.3 | |
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brass | 15.4 | |
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fashion | 15.1 | |
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trombone | 14.8 | |
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person | 14.2 | |
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men | 13.7 | |
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uniform | 13.6 | |
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building | 13.3 | |
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adult | 13 | |
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standing | 13 | |
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life | 12.8 | |
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window | 12.8 | |
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military uniform | 12.8 | |
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old | 12.5 | |
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travel | 12 | |
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women | 11.9 | |
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portrait | 11.6 | |
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walk | 11.4 | |
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shop | 11.4 | |
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equipment | 11.2 | |
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home | 11.2 | |
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room | 11.1 | |
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device | 11 | |
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work | 11 | |
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telephone | 10.9 | |
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office | 10.7 | |
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family | 10.7 | |
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wind instrument | 10.7 | |
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black | 10.4 | |
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machine | 10.3 | |
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clothes | 10.3 | |
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architecture | 10.1 | |
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musical instrument | 9.9 | |
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pay-phone | 9.7 | |
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indoors | 9.7 | |
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style | 9.6 | |
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worker | 8.8 | |
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interior | 8.8 | |
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light | 8.7 | |
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scene | 8.7 | |
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crutch | 8.5 | |
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modern | 8.4 | |
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street | 8.3 | |
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shopping | 8.3 | |
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human | 8.2 | |
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occupation | 8.2 | |
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group | 8.1 | |
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electronic equipment | 8 | |
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call | 8 | |
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working | 7.9 | |
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businessman | 7.9 | |
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station | 7.9 | |
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smile | 7.8 | |
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boy | 7.8 | |
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mall | 7.8 | |
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corporate | 7.7 | |
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crowd | 7.7 | |
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walking | 7.6 | |
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happy | 7.5 | |
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staff | 7.5 | |
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buy | 7.5 | |
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holding | 7.4 | |
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inside | 7.4 | |
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transportation | 7.2 | |
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job | 7.1 | |
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Google
created on 2022-01-15
Gesture | 85.3 | |
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Chair | 80.2 | |
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Tints and shades | 74.4 | |
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Snapshot | 74.3 | |
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Monochrome photography | 71.6 | |
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Rectangle | 71.2 | |
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Vintage clothing | 71.2 | |
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Art | 70 | |
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Event | 65.1 | |
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Monochrome | 63.9 | |
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Stock photography | 62.5 | |
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Visual arts | 62.5 | |
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History | 62.4 | |
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Room | 61.5 | |
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Classic | 60.8 | |
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Door | 55.4 | |
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Suit | 54 | |
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Photographic paper | 53.2 | |
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Picture frame | 50 | |
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Microsoft
created on 2022-01-15
text | 99.5 | |
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street | 98.8 | |
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clothing | 96.8 | |
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black and white | 96.2 | |
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person | 94.9 | |
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outdoor | 93.7 | |
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man | 85.5 | |
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monochrome | 74.5 | |
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footwear | 72.1 | |
|
Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18815589/681,139,20,26/full/0/native.jpg)
AWS Rekognition
Age | 23-31 |
Gender | Female, 87.6% |
Calm | 71.2% |
Happy | 15.2% |
Fear | 5.5% |
Sad | 4.5% |
Angry | 1% |
Surprised | 1% |
Confused | 0.9% |
Disgusted | 0.7% |
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18815589/224,118,174,557/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18815589/402,147,156,538/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18815589/54,153,186,535/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18815589/666,147,79,258/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18815589/375,174,59,170/full/0/native.jpg)
Person | 99.8% | |
|
Categories
Imagga
streetview architecture | 81.1% | |
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interior objects | 17.9% | |
|
Captions
Microsoft
created on 2022-01-15
a group of people standing in front of a window | 84.5% | |
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a group of people standing in front of a store window | 79.8% | |
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a group of people standing in front of a building | 79.7% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18815589/586,277,45,55/full/0/native.jpg)
5
![](https://ids.lib.harvard.edu/ids/iiif/18815589/510,192,26,16/full/0/native.jpg)
es
![](https://ids.lib.harvard.edu/ids/iiif/18815589/364,134,37,15/full/0/native.jpg)
MILK
![](https://ids.lib.harvard.edu/ids/iiif/18815589/70,142,29,13/full/0/native.jpg)
DRINK
![](https://ids.lib.harvard.edu/ids/iiif/18815589/336,133,66,19/full/0/native.jpg)
TED MILK
![](https://ids.lib.harvard.edu/ids/iiif/18815589/336,136,24,14/full/0/native.jpg)
TED
![](https://ids.lib.harvard.edu/ids/iiif/18815589/219,74,38,25/full/0/native.jpg)
10c
![](https://ids.lib.harvard.edu/ids/iiif/18815589/516,225,18,10/full/0/native.jpg)
ER
![](https://ids.lib.harvard.edu/ids/iiif/18815589/543,218,17,10/full/0/native.jpg)
ICE
![](https://ids.lib.harvard.edu/ids/iiif/18815589/385,330,37,15/full/0/native.jpg)
dires
![](https://ids.lib.harvard.edu/ids/iiif/18815589/47,142,51,13/full/0/native.jpg)
PPLE DRINK
![](https://ids.lib.harvard.edu/ids/iiif/18815589/48,130,29,14/full/0/native.jpg)
NGE
![](https://ids.lib.harvard.edu/ids/iiif/18815589/48,145,18,10/full/0/native.jpg)
PPLE
![](https://ids.lib.harvard.edu/ids/iiif/18815589/366,150,9,3/full/0/native.jpg)
-
![](https://ids.lib.harvard.edu/ids/iiif/18815589/346,107,56,24/full/0/native.jpg)
Special
![](https://ids.lib.harvard.edu/ids/iiif/18815589/351,124,47,12/full/0/native.jpg)
CHOCOLATE
![](https://ids.lib.harvard.edu/ids/iiif/18815589/48,129,46,15/full/0/native.jpg)
NGE and
![](https://ids.lib.harvard.edu/ids/iiif/18815589/366,149,28,5/full/0/native.jpg)
- THE
![](https://ids.lib.harvard.edu/ids/iiif/18815589/315,107,86,28/full/0/native.jpg)
the ANT Special
![](https://ids.lib.harvard.edu/ids/iiif/18815589/543,229,17,9/full/0/native.jpg)
COLI
![](https://ids.lib.harvard.edu/ids/iiif/18815589/333,129,13,6/full/0/native.jpg)
ANT
![](https://ids.lib.harvard.edu/ids/iiif/18815589/390,317,13,6/full/0/native.jpg)
Drum
![](https://ids.lib.harvard.edu/ids/iiif/18815589/64,162,22,7/full/0/native.jpg)
are
![](https://ids.lib.harvard.edu/ids/iiif/18815589/70,946,142,67/full/0/native.jpg)
Pran
![](https://ids.lib.harvard.edu/ids/iiif/18815589/62,152,36,17/full/0/native.jpg)
Stock free are
![](https://ids.lib.harvard.edu/ids/iiif/18815589/51,120,43,11/full/0/native.jpg)
Combination
![](https://ids.lib.harvard.edu/ids/iiif/18815589/315,114,15,10/full/0/native.jpg)
the
![](https://ids.lib.harvard.edu/ids/iiif/18815589/221,114,31,7/full/0/native.jpg)
Number
![](https://ids.lib.harvard.edu/ids/iiif/18815589/206,114,45,8/full/0/native.jpg)
en Number
![](https://ids.lib.harvard.edu/ids/iiif/18815589/206,115,13,6/full/0/native.jpg)
en
![](https://ids.lib.harvard.edu/ids/iiif/18815589/199,90,19,8/full/0/native.jpg)
MIX
![](https://ids.lib.harvard.edu/ids/iiif/18815589/376,149,19,5/full/0/native.jpg)
THE
![](https://ids.lib.harvard.edu/ids/iiif/18815589/62,153,36,11/full/0/native.jpg)
Stock free
![](https://ids.lib.harvard.edu/ids/iiif/18815589/83,131,11,7/full/0/native.jpg)
and
![](https://ids.lib.harvard.edu/ids/iiif/18815589/45,108,597,904/full/0/native.jpg)
Speril
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PPLE DRINK
TED MILK
veRE E
lires
DRINK
1234
![](https://ids.lib.harvard.edu/ids/iiif/18815589/345,108,58,30/full/0/native.jpg)
Speril
![](https://ids.lib.harvard.edu/ids/iiif/18815589/45,129,38,20/full/0/native.jpg)
ANGE
![](https://ids.lib.harvard.edu/ids/iiif/18815589/47,144,28,19/full/0/native.jpg)
PPLE
![](https://ids.lib.harvard.edu/ids/iiif/18815589/72,143,33,20/full/0/native.jpg)
DRINK
![](https://ids.lib.harvard.edu/ids/iiif/18815589/336,139,28,15/full/0/native.jpg)
TED
![](https://ids.lib.harvard.edu/ids/iiif/18815589/366,138,39,16/full/0/native.jpg)
MILK
![](https://ids.lib.harvard.edu/ids/iiif/18815589/203,148,46,23/full/0/native.jpg)
veRE
![](https://ids.lib.harvard.edu/ids/iiif/18815589/251,149,24,23/full/0/native.jpg)
E
![](https://ids.lib.harvard.edu/ids/iiif/18815589/376,334,50,17/full/0/native.jpg)
lires
![](https://ids.lib.harvard.edu/ids/iiif/18815589/88,997,132,15/full/0/native.jpg)
1234