Machine Generated Data
Tags
Amazon
created on 2022-06-04
Railway | 99.6 | |
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Rail | 99.6 | |
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Train Track | 99.6 | |
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Transportation | 99.6 | |
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Person | 77.4 | |
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Human | 77.4 | |
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Theme Park | 56.2 | |
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Amusement Park | 56.2 | |
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Building | 55.3 | |
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Imagga
created on 2022-06-04
sketch | 80.8 | |
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drawing | 59.1 | |
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representation | 47 | |
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city | 26.6 | |
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architecture | 24 | |
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urban | 23.6 | |
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travel | 21.1 | |
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building | 20.9 | |
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sky | 19.2 | |
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structure | 18 | |
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landscape | 16.4 | |
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construction | 16.3 | |
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outdoor | 14.5 | |
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winter | 14.5 | |
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road | 14.5 | |
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transportation | 14.3 | |
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river | 14.2 | |
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snow | 14 | |
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water | 14 | |
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town | 13.9 | |
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station | 13.8 | |
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tower | 13.4 | |
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cold | 12.9 | |
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transport | 12.8 | |
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exterior | 12 | |
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industry | 12 | |
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house | 11.9 | |
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modern | 11.2 | |
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street | 11 | |
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step | 11 | |
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industrial | 10.9 | |
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bridge | 10.6 | |
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track | 10.6 | |
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scene | 10.4 | |
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old | 9.8 | |
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train | 9.6 | |
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cityscape | 9.5 | |
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season | 9.4 | |
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power | 9.2 | |
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tourism | 9.1 | |
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metal | 8.9 | |
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line | 8.8 | |
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day | 8.6 | |
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equipment | 8.6 | |
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outside | 8.6 | |
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tree | 8.5 | |
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horizontal | 8.4 | |
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ice | 8.3 | |
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support | 8.3 | |
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environment | 8.2 | |
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outdoors | 8.2 | |
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technology | 8.2 | |
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device | 8.1 | |
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landmark | 8.1 | |
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reflection | 8.1 | |
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new | 8.1 | |
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lines | 8.1 | |
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light | 8 | |
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trees | 8 | |
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home | 8 | |
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steel | 8 | |
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black | 7.8 | |
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gas | 7.7 | |
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weather | 7.6 | |
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traffic | 7.6 | |
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buildings | 7.6 | |
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electricity | 7.6 | |
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park | 7.4 | |
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turbine | 7.3 | |
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rural | 7.1 | |
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scenic | 7 | |
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Google
created on 2022-06-04
Black-and-white | 84.7 | |
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Style | 83.8 | |
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Electricity | 82 | |
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Line | 81.7 | |
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Road | 77 | |
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Monochrome | 76.9 | |
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Track | 75.2 | |
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Monochrome photography | 74.2 | |
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Automotive lighting | 72.5 | |
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City | 72.2 | |
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Railway | 71 | |
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Asphalt | 70.2 | |
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Street | 68.5 | |
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Recreation | 67.3 | |
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Metal | 67.2 | |
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Bridge | 66.1 | |
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Urban design | 64.3 | |
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Nonbuilding structure | 63.6 | |
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Overpass | 62.4 | |
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Public transport | 61 | |
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Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20488800/628,395,9,11/full/0/native.jpg)
AWS Rekognition
Age | 13-21 |
Gender | Male, 97.2% |
Calm | 70.2% |
Fear | 9.1% |
Surprised | 7.7% |
Angry | 7.6% |
Happy | 4.4% |
Sad | 3.3% |
Confused | 3.1% |
Disgusted | 1.9% |
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20488800/537,466,60,127/full/0/native.jpg)
Person | 77.4% | |
|
Categories
Imagga
text visuals | 59% | |
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paintings art | 26.5% | |
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cars vehicles | 5% | |
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interior objects | 4% | |
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streetview architecture | 3.6% | |
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Captions
Microsoft
created on 2022-06-04
a train on a steel track | 44.3% | |
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an old photo of a train yard | 44.2% | |
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an old photo of a train | 44.1% | |
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Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20488800/367,781,55,36/full/0/native.jpg)
lobby
![](https://ids.lib.harvard.edu/ids/iiif/20488800/920,340,43,19/full/0/native.jpg)
WARREN
![](https://ids.lib.harvard.edu/ids/iiif/20488800/871,299,60,30/full/0/native.jpg)
utter
![](https://ids.lib.harvard.edu/ids/iiif/20488800/246,553,13,7/full/0/native.jpg)
NO
![](https://ids.lib.harvard.edu/ids/iiif/20488800/971,287,48,37/full/0/native.jpg)
Fram
![](https://ids.lib.harvard.edu/ids/iiif/20488800/908,345,10,14/full/0/native.jpg)
19
![](https://ids.lib.harvard.edu/ids/iiif/20488800/53,792,59,22/full/0/native.jpg)
Dudley
![](https://ids.lib.harvard.edu/ids/iiif/20488800/909,793,59,18/full/0/native.jpg)
744B
![](https://ids.lib.harvard.edu/ids/iiif/20488800/868,325,61,27/full/0/native.jpg)
FOXBURY
![](https://ids.lib.harvard.edu/ids/iiif/20488800/908,340,69,19/full/0/native.jpg)
19 WARREN IT
![](https://ids.lib.harvard.edu/ids/iiif/20488800/53,781,369,38/full/0/native.jpg)
Dudley St.Station E.loop Molormens lobby
![](https://ids.lib.harvard.edu/ids/iiif/20488800/115,790,85,26/full/0/native.jpg)
St.Station
![](https://ids.lib.harvard.edu/ids/iiif/20488800/275,785,94,31/full/0/native.jpg)
Molormens
![](https://ids.lib.harvard.edu/ids/iiif/20488800/206,790,68,29/full/0/native.jpg)
E.loop
![](https://ids.lib.harvard.edu/ids/iiif/20488800/958,340,19,15/full/0/native.jpg)
IT
![](https://ids.lib.harvard.edu/ids/iiif/20488800/649,791,103,22/full/0/native.jpg)
Dec.(C.og
![](https://ids.lib.harvard.edu/ids/iiif/20488800/890,-2,122,30/full/0/native.jpg)
the
![](https://ids.lib.harvard.edu/ids/iiif/20488800/53,287,988,532/full/0/native.jpg)
Dudley St Stalion Eloop Flolarmens lobby
Dec. 16.09
uter Fram
ROXBURY
19 WARRENT
744 B
![](https://ids.lib.harvard.edu/ids/iiif/20488800/53,789,64,30/full/0/native.jpg)
Dudley
![](https://ids.lib.harvard.edu/ids/iiif/20488800/114,790,30,28/full/0/native.jpg)
St
![](https://ids.lib.harvard.edu/ids/iiif/20488800/139,788,64,30/full/0/native.jpg)
Stalion
![](https://ids.lib.harvard.edu/ids/iiif/20488800/207,787,69,30/full/0/native.jpg)
Eloop
![](https://ids.lib.harvard.edu/ids/iiif/20488800/275,786,98,30/full/0/native.jpg)
Flolarmens
![](https://ids.lib.harvard.edu/ids/iiif/20488800/370,785,56,30/full/0/native.jpg)
lobby
![](https://ids.lib.harvard.edu/ids/iiif/20488800/652,794,53,22/full/0/native.jpg)
Dec.
![](https://ids.lib.harvard.edu/ids/iiif/20488800/699,796,56,21/full/0/native.jpg)
16.09
![](https://ids.lib.harvard.edu/ids/iiif/20488800/870,292,65,40/full/0/native.jpg)
uter
![](https://ids.lib.harvard.edu/ids/iiif/20488800/870,328,65,30/full/0/native.jpg)
ROXBURY
![](https://ids.lib.harvard.edu/ids/iiif/20488800/920,341,60,23/full/0/native.jpg)
WARRENT
![](https://ids.lib.harvard.edu/ids/iiif/20488800/954,797,18,16/full/0/native.jpg)
B
![](https://ids.lib.harvard.edu/ids/iiif/20488800/970,292,50,38/full/0/native.jpg)
Fram
![](https://ids.lib.harvard.edu/ids/iiif/20488800/907,345,16,20/full/0/native.jpg)
19
![](https://ids.lib.harvard.edu/ids/iiif/20488800/912,795,43,18/full/0/native.jpg)
744