Machine Generated Data
Tags
Amazon
created on 2022-01-08
Clarifai
created on 2023-10-25
adult | 97.3 | |
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people | 97 | |
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technology | 96.4 | |
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industry | 95.1 | |
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man | 95.1 | |
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monochrome | 94.2 | |
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scientist | 93.7 | |
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grinder | 93.1 | |
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indoors | 92.7 | |
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science | 90.2 | |
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business | 82.9 | |
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chemistry | 75.4 | |
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horizontal | 72.9 | |
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equipment | 72.8 | |
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biology | 70.2 | |
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reflection | 69.2 | |
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modern | 69.1 | |
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research | 68 | |
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connection | 64.2 | |
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laboratory | 63.1 | |
|
Imagga
created on 2022-01-08
glass | 26.4 | |
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menorah | 24.6 | |
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table | 23.4 | |
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dishwasher | 22.1 | |
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restaurant | 19.5 | |
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candelabrum | 18.9 | |
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white goods | 18 | |
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dinner | 17.7 | |
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glasses | 16.6 | |
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business | 16.4 | |
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equipment | 16 | |
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party | 15.5 | |
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interior | 15 | |
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napkin | 14.6 | |
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luxury | 14.6 | |
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candlestick | 14.2 | |
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wine | 14 | |
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home appliance | 14 | |
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food | 13.9 | |
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plate | 13.8 | |
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drink | 13.4 | |
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technology | 13.3 | |
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kitchen | 12.7 | |
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setting | 12.5 | |
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meal | 12.2 | |
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lunch | 12 | |
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home | 12 | |
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celebration | 12 | |
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house | 11.7 | |
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holder | 11.4 | |
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container | 11.3 | |
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design | 11.2 | |
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knife | 10.6 | |
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work | 10.5 | |
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modern | 10.5 | |
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spoon | 10.5 | |
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appliance | 10.2 | |
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architecture | 10.1 | |
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banquet | 9.8 | |
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silver | 9.7 | |
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chair | 9.7 | |
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office | 9.6 | |
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fork | 9.6 | |
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hotel | 9.5 | |
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dining | 9.5 | |
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empty | 9.4 | |
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man | 9.4 | |
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decoration | 9.4 | |
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silverware | 9.4 | |
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service | 9.3 | |
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event | 9.2 | |
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building | 9.2 | |
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indoors | 8.8 | |
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preparation | 8.6 | |
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engineering | 8.6 | |
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room | 8.5 | |
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plan | 8.5 | |
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elegance | 8.4 | |
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place | 8.4 | |
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hand | 8.3 | |
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new | 8.1 | |
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computer | 8 | |
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science | 8 | |
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tablecloth | 7.8 | |
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reception | 7.8 | |
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construction | 7.7 | |
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vessel | 7.5 | |
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clean | 7.5 | |
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light | 7.3 | |
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dish | 7.3 | |
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wineglass | 7.3 | |
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bartender | 7.3 | |
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lifestyle | 7.2 | |
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holiday | 7.2 | |
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barroom | 7.1 | |
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male | 7.1 | |
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medical | 7.1 | |
|
Google
created on 2022-01-08
White | 92.2 | |
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Black | 89.5 | |
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Black-and-white | 85.8 | |
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Style | 84 | |
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Barware | 79.5 | |
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Engineering | 78.1 | |
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Automotive design | 77.5 | |
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Factory | 77 | |
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Monochrome | 75 | |
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Monochrome photography | 74.5 | |
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Science | 73.8 | |
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Machine | 73.4 | |
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Automotive wheel system | 71.3 | |
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Industry | 71.1 | |
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Circle | 70.2 | |
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Metal | 70 | |
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Auto part | 66.6 | |
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Research | 66.3 | |
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Glass | 65.6 | |
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Cooking | 65.5 | |
|
Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18785385/488,75,56,80/full/0/native.jpg)
AWS Rekognition
Age | 56-64 |
Gender | Male, 99.6% |
Calm | 97.8% |
Disgusted | 0.9% |
Confused | 0.3% |
Sad | 0.3% |
Happy | 0.3% |
Surprised | 0.1% |
Angry | 0.1% |
Fear | 0% |
![](https://ids.lib.harvard.edu/ids/iiif/18785385/472,60,74,86/full/0/native.jpg)
Google Vision
Surprise | Very unlikely |
Anger | Very unlikely |
Sorrow | Very unlikely |
Joy | Very unlikely |
Headwear | Very unlikely |
Blurred | Very unlikely |
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18785385/399,65,179,351/full/0/native.jpg)
Person | 99.4% | |
|
Categories
Imagga
paintings art | 98% | |
| ||
interior objects | 2% | |
|
Captions
Microsoft
created on 2022-01-08
a man cooking in a kitchen | 76.1% | |
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a man standing in a kitchen | 76% | |
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a man cooking in the kitchen | 75% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18785385/324,787,113,20/full/0/native.jpg)
STEINMETZ,
![](https://ids.lib.harvard.edu/ids/iiif/18785385/449,786,113,21/full/0/native.jpg)
SARASOTA,
![](https://ids.lib.harvard.edu/ids/iiif/18785385/574,785,85,19/full/0/native.jpg)
FLORIDA
![](https://ids.lib.harvard.edu/ids/iiif/18785385/633,604,53,26/full/0/native.jpg)
Crop
![](https://ids.lib.harvard.edu/ids/iiif/18785385/630,585,61,28/full/0/native.jpg)
Snow
![](https://ids.lib.harvard.edu/ids/iiif/18785385/848,513,27,8/full/0/native.jpg)
JUICE
![](https://ids.lib.harvard.edu/ids/iiif/18785385/739,529,37,17/full/0/native.jpg)
ORANGE
![](https://ids.lib.harvard.edu/ids/iiif/18785385/586,445,13,8/full/0/native.jpg)
il
![](https://ids.lib.harvard.edu/ids/iiif/18785385/324,785,497,32/full/0/native.jpg)
STEINMETZ, SARASOTA, FLORIDA 25657.
![](https://ids.lib.harvard.edu/ids/iiif/18785385/786,509,14,12/full/0/native.jpg)
=
![](https://ids.lib.harvard.edu/ids/iiif/18785385/729,409,11,8/full/0/native.jpg)
Cr
![](https://ids.lib.harvard.edu/ids/iiif/18785385/25,785,188,31/full/0/native.jpg)
25657.
![](https://ids.lib.harvard.edu/ids/iiif/18785385/728,399,24,9/full/0/native.jpg)
Sno
![](https://ids.lib.harvard.edu/ids/iiif/18785385/384,440,30,11/full/0/native.jpg)
Crap
![](https://ids.lib.harvard.edu/ids/iiif/18785385/564,436,18,11/full/0/native.jpg)
OW
![](https://ids.lib.harvard.edu/ids/iiif/18785385/566,447,12,8/full/0/native.jpg)
019
![](https://ids.lib.harvard.edu/ids/iiif/18785385/990,428,7,20/full/0/native.jpg)
COVID
![](https://ids.lib.harvard.edu/ids/iiif/18785385/321,399,650,419/full/0/native.jpg)
Sne
now
Snow
Crop
Crap
Snow
Crop
ORANDE
now
Crop
now
Snow
Crop
STEINMETZ, SARASOTA, FLORIDA 2S657.
![](https://ids.lib.harvard.edu/ids/iiif/18785385/847,472,45,23/full/0/native.jpg)
Snow
![](https://ids.lib.harvard.edu/ids/iiif/18785385/741,511,44,26/full/0/native.jpg)
Crop
![](https://ids.lib.harvard.edu/ids/iiif/18785385/728,399,32,14/full/0/native.jpg)
Sne
![](https://ids.lib.harvard.edu/ids/iiif/18785385/321,408,32,15/full/0/native.jpg)
now
![](https://ids.lib.harvard.edu/ids/iiif/18785385/380,441,40,16/full/0/native.jpg)
Crap
![](https://ids.lib.harvard.edu/ids/iiif/18785385/847,503,36,17/full/0/native.jpg)
ORANDE
![](https://ids.lib.harvard.edu/ids/iiif/18785385/327,785,124,27/full/0/native.jpg)
STEINMETZ,
![](https://ids.lib.harvard.edu/ids/iiif/18785385/451,786,116,25/full/0/native.jpg)
SARASOTA,
![](https://ids.lib.harvard.edu/ids/iiif/18785385/574,788,91,27/full/0/native.jpg)
FLORIDA
![](https://ids.lib.harvard.edu/ids/iiif/18785385/673,789,157,29/full/0/native.jpg)
2S657.