Machine Generated Data
Tags
Amazon
created on 2022-01-08
Person | 99.5 | |
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Human | 99.5 | |
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Person | 99.4 | |
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Airplane | 97.7 | |
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Aircraft | 97.7 | |
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Vehicle | 97.7 | |
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Transportation | 97.7 | |
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Machine | 73 | |
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Airplane | 71.3 | |
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Spaceship | 71 | |
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Wheel | 67.2 | |
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Nature | 66.3 | |
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Ship | 64.8 | |
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Dock | 63.7 | |
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Port | 63.7 | |
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Waterfront | 63.7 | |
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Harbor | 63.7 | |
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Water | 63.7 | |
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Pier | 63.7 | |
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Smoke | 63.3 | |
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Airfield | 61 | |
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Airport | 61 | |
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Weapon | 59.6 | |
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Weaponry | 59.6 | |
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Military | 58.1 | |
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Battleship | 58.1 | |
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Navy | 58.1 | |
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Clarifai
created on 2023-10-25
Imagga
created on 2022-01-08
negative | 59.5 | |
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film | 47.6 | |
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photographic paper | 36 | |
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ship | 34.3 | |
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architecture | 30.8 | |
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city | 29.9 | |
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town | 29.7 | |
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cargo ship | 25.2 | |
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photographic equipment | 24 | |
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vessel | 23.9 | |
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building | 23.3 | |
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container ship | 22.8 | |
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cityscape | 18.9 | |
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sky | 18.5 | |
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urban | 17.5 | |
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business | 17 | |
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construction | 15.4 | |
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bridge | 14.2 | |
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travel | 14.1 | |
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sea | 14.1 | |
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port | 13.5 | |
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water | 13.3 | |
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skyline | 13.3 | |
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buildings | 13.2 | |
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shipping | 13 | |
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transport | 12.8 | |
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old | 12.5 | |
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house | 12.5 | |
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harbor | 12.5 | |
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modern | 11.9 | |
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high | 11.3 | |
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industry | 11.1 | |
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transportation | 10.8 | |
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dock | 10.7 | |
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cargo | 10.7 | |
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roof | 10.5 | |
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landscape | 10.4 | |
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historical | 10.3 | |
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crane | 10.1 | |
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design | 10.1 | |
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street | 10.1 | |
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power | 10.1 | |
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river | 9.8 | |
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district | 9.7 | |
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oil tanker | 9.7 | |
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3d | 9.3 | |
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ocean | 9.1 | |
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industrial | 9.1 | |
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tourism | 9.1 | |
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world | 9 | |
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tower | 8.9 | |
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home | 8.8 | |
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aerial | 8.7 | |
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panorama | 8.6 | |
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plan | 8.5 | |
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commerce | 8.4 | |
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church | 8.3 | |
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technology | 8.2 | |
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boat | 8.1 | |
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structure | 8 | |
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container | 7.9 | |
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freight | 7.8 | |
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skyscrapers | 7.8 | |
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scene | 7.8 | |
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houses | 7.7 | |
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center | 7.7 | |
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trade | 7.6 | |
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drawing | 7.5 | |
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silhouette | 7.4 | |
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vacation | 7.4 | |
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tourist | 7.2 | |
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square | 7.2 | |
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work | 7.1 | |
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Google
created on 2022-01-08
Vehicle | 91.9 | |
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Aircraft | 88.3 | |
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Aerospace manufacturer | 83.9 | |
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Airplane | 83 | |
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Wheel | 78.8 | |
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Aircraft engine | 78.2 | |
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Propeller | 77.1 | |
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Naval architecture | 75.9 | |
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Propeller-driven aircraft | 75.8 | |
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Rectangle | 75.6 | |
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Propeller | 74.9 | |
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Monoplane | 73.6 | |
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Aviation | 70.3 | |
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Font | 67.9 | |
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Machine | 64.3 | |
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Stock photography | 63.3 | |
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Jet engine | 60.4 | |
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Engineering | 60.1 | |
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Military aircraft | 59.2 | |
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Monochrome photography | 57.5 | |
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Microsoft
created on 2022-01-08
text | 99.7 | |
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ship | 99.4 | |
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black | 86.6 | |
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old | 85.5 | |
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white | 78.6 | |
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vehicle | 78.2 | |
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watercraft | 71.5 | |
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black and white | 59.7 | |
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vintage | 45.9 | |
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Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18785629/249,516,15,21/full/0/native.jpg)
AWS Rekognition
Age | 19-27 |
Gender | Male, 97.1% |
Surprised | 70.3% |
Angry | 14.6% |
Disgusted | 6.2% |
Happy | 3.5% |
Fear | 2.1% |
Calm | 1.4% |
Confused | 1% |
Sad | 0.9% |
Feature analysis
Categories
Imagga
paintings art | 33.9% | |
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text visuals | 28.2% | |
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interior objects | 24.5% | |
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beaches seaside | 5.2% | |
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streetview architecture | 2.8% | |
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cars vehicles | 2.6% | |
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food drinks | 1.9% | |
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Captions
Microsoft
created on 2022-01-08
a vintage photo of an old airplane | 77.5% | |
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a vintage photo of a plane | 77.4% | |
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a vintage photo of a large ship in the background | 74.5% | |
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Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18785629/520,534,99,53/full/0/native.jpg)
Dodgers
![](https://ids.lib.harvard.edu/ids/iiif/18785629/764,512,37,29/full/0/native.jpg)
NC
![](https://ids.lib.harvard.edu/ids/iiif/18785629/739,546,87,42/full/0/native.jpg)
80480
![](https://ids.lib.harvard.edu/ids/iiif/18785629/661,424,41,19/full/0/native.jpg)
LINES
![](https://ids.lib.harvard.edu/ids/iiif/18785629/629,427,27,18/full/0/native.jpg)
AIR
![](https://ids.lib.harvard.edu/ids/iiif/18785629/571,774,82,18/full/0/native.jpg)
FLORIDA
![](https://ids.lib.harvard.edu/ids/iiif/18785629/569,424,134,26/full/0/native.jpg)
EASTERN AIR LINES
![](https://ids.lib.harvard.edu/ids/iiif/18785629/324,773,329,25/full/0/native.jpg)
STEINMETZ, SARASOTA, FLORIDA
![](https://ids.lib.harvard.edu/ids/iiif/18785629/447,774,112,22/full/0/native.jpg)
SARASOTA,
![](https://ids.lib.harvard.edu/ids/iiif/18785629/324,777,111,20/full/0/native.jpg)
STEINMETZ,
![](https://ids.lib.harvard.edu/ids/iiif/18785629/569,430,56,20/full/0/native.jpg)
EASTERN
![](https://ids.lib.harvard.edu/ids/iiif/18785629/111,779,153,26/full/0/native.jpg)
25728
![](https://ids.lib.harvard.edu/ids/iiif/18785629/644,446,43,16/full/0/native.jpg)
ROOM
![](https://ids.lib.harvard.edu/ids/iiif/18785629/581,446,107,19/full/0/native.jpg)
WAITING ROOM
![](https://ids.lib.harvard.edu/ids/iiif/18785629/617,339,41,16/full/0/native.jpg)
PILOTS
![](https://ids.lib.harvard.edu/ids/iiif/18785629/582,449,55,16/full/0/native.jpg)
WAITING
![](https://ids.lib.harvard.edu/ids/iiif/18785629/614,326,48,19/full/0/native.jpg)
VISITING
![](https://ids.lib.harvard.edu/ids/iiif/18785629/992,277,12,23/full/0/native.jpg)
SB
![](https://ids.lib.harvard.edu/ids/iiif/18785629/989,448,18,168/full/0/native.jpg)
KODAK-
![](https://ids.lib.harvard.edu/ids/iiif/18785629/696,505,42,22/full/0/native.jpg)
Beecherall
![](https://ids.lib.harvard.edu/ids/iiif/18785629/114,327,896,482/full/0/native.jpg)
VISITING
PILOTS
EASTERN AIR LINES
WAITING ROOM
NC
Dedgers
80480
25728
STEINMETZ, SARASOTA, FLORIDA
YT3RA8 MAO
![](https://ids.lib.harvard.edu/ids/iiif/18785629/620,340,42,20/full/0/native.jpg)
PILOTS
![](https://ids.lib.harvard.edu/ids/iiif/18785629/571,431,59,23/full/0/native.jpg)
EASTERN
![](https://ids.lib.harvard.edu/ids/iiif/18785629/631,429,29,20/full/0/native.jpg)
AIR
![](https://ids.lib.harvard.edu/ids/iiif/18785629/663,426,44,22/full/0/native.jpg)
LINES
![](https://ids.lib.harvard.edu/ids/iiif/18785629/645,446,49,23/full/0/native.jpg)
ROOM
![](https://ids.lib.harvard.edu/ids/iiif/18785629/513,531,119,64/full/0/native.jpg)
Dedgers
![](https://ids.lib.harvard.edu/ids/iiif/18785629/620,328,46,21/full/0/native.jpg)
VISITING
![](https://ids.lib.harvard.edu/ids/iiif/18785629/579,451,63,22/full/0/native.jpg)
WAITING
![](https://ids.lib.harvard.edu/ids/iiif/18785629/770,516,33,30/full/0/native.jpg)
NC
![](https://ids.lib.harvard.edu/ids/iiif/18785629/730,542,99,53/full/0/native.jpg)
80480
![](https://ids.lib.harvard.edu/ids/iiif/18785629/114,781,156,28/full/0/native.jpg)
25728
![](https://ids.lib.harvard.edu/ids/iiif/18785629/328,778,115,25/full/0/native.jpg)
STEINMETZ,
![](https://ids.lib.harvard.edu/ids/iiif/18785629/450,776,116,26/full/0/native.jpg)
SARASOTA,
![](https://ids.lib.harvard.edu/ids/iiif/18785629/576,774,80,26/full/0/native.jpg)
FLORIDA
![](https://ids.lib.harvard.edu/ids/iiif/18785629/992,454,15,75/full/0/native.jpg)
YT3RA8
![](https://ids.lib.harvard.edu/ids/iiif/18785629/989,547,22,69/full/0/native.jpg)
MAO