Machine Generated Data
Tags
Amazon
created on 2023-10-06
City | 98.8 | |
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Road | 98.8 | |
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Street | 98.8 | |
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Urban | 98.8 | |
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Person | 97.8 | |
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Person | 97.1 | |
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Machine | 96.7 | |
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Wheel | 96.7 | |
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Clothing | 94.9 | |
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Coat | 94.9 | |
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Car | 92.2 | |
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Transportation | 92.2 | |
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Vehicle | 92.2 | |
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Wheel | 91.5 | |
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Wheel | 87.2 | |
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Truck | 83.3 | |
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Car | 73.9 | |
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Person | 71.9 | |
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Outdoors | 67.8 | |
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Neighborhood | 62.6 | |
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Person | 57.6 | |
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Van | 57.6 | |
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Moving Van | 56.2 | |
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Walking | 55.7 | |
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Caravan | 55.6 | |
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Hardhat | 55.1 | |
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Helmet | 55.1 | |
|
Clarifai
created on 2018-05-11
people | 99.9 | |
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street | 99.6 | |
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group together | 99.2 | |
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vehicle | 98.7 | |
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group | 98.2 | |
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transportation system | 98 | |
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adult | 97.4 | |
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monochrome | 97.1 | |
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man | 96.5 | |
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police | 94.6 | |
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road | 93.8 | |
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two | 93.4 | |
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many | 92.4 | |
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railway | 92.2 | |
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three | 91.9 | |
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four | 91.8 | |
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several | 90.9 | |
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administration | 89.8 | |
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woman | 89.2 | |
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tram | 87.4 | |
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Imagga
created on 2023-10-06
street | 37.7 | |
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city | 33.3 | |
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urban | 25.3 | |
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container | 23.6 | |
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mailbox | 23.3 | |
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transportation | 23.3 | |
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streetcar | 23.2 | |
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building | 22 | |
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box | 20.6 | |
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travel | 20.4 | |
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office | 19.7 | |
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architecture | 19.6 | |
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sidewalk | 19.6 | |
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car | 19.5 | |
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old | 19.5 | |
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vehicle | 17.9 | |
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telephone | 17.6 | |
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town | 17.6 | |
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pay-phone | 17.4 | |
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transport | 16.4 | |
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wheeled vehicle | 16.4 | |
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road | 16.3 | |
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gas pump | 14.3 | |
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pump | 14.3 | |
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station | 13.5 | |
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business | 13.4 | |
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house | 12.5 | |
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traffic | 12.3 | |
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brick | 12.2 | |
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ashcan | 11.9 | |
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people | 11.7 | |
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electronic equipment | 11 | |
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equipment | 10.5 | |
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lamp | 10.5 | |
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bin | 10.5 | |
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historic | 10.1 | |
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man | 10.1 | |
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window | 10.1 | |
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conveyance | 10 | |
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tourism | 9.9 | |
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machine | 9.8 | |
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drive | 9.5 | |
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buildings | 9.4 | |
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wall | 9.4 | |
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industry | 9.4 | |
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train | 8.9 | |
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door | 8.9 | |
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public | 8.7 | |
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mechanical device | 8.7 | |
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automobile | 8.6 | |
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men | 8.6 | |
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stone | 8.4 | |
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call | 8 | |
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cobblestone | 7.9 | |
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rail | 7.9 | |
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pavement | 7.9 | |
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lantern | 7.8 | |
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scene | 7.8 | |
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modern | 7.7 | |
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power | 7.6 | |
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exterior | 7.4 | |
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device | 7.3 | |
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tramway | 7.3 | |
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tourist | 7.3 | |
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square | 7.2 | |
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black | 7.2 | |
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home | 7.2 | |
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history | 7.2 | |
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male | 7.1 | |
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truck | 7 | |
|
Google
created on 2018-05-11
car | 98.5 | |
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motor vehicle | 97.3 | |
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vehicle | 92.8 | |
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transport | 88.5 | |
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mode of transport | 87.5 | |
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black and white | 86.3 | |
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infrastructure | 85.8 | |
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street | 85.3 | |
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snapshot | 81.8 | |
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luxury vehicle | 74.9 | |
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monochrome photography | 69.5 | |
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family car | 64.5 | |
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road | 61.5 | |
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classic | 59.4 | |
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monochrome | 57.8 | |
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pedestrian | 55.8 | |
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compact car | 54.6 | |
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public utility | 51.2 | |
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van | 51 | |
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Color Analysis
Feature analysis
Categories
Imagga
streetview architecture | 98.9% | |
|
Captions
Microsoft
created on 2018-05-11
a black and white photo of a person | 88% | |
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a black and white photo of a building | 87.9% | |
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black and white photo of a person | 84.6% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/43158615/889,100,109,22/full/0/native.jpg)
BAKER
![](https://ids.lib.harvard.edu/ids/iiif/43158615/843,108,43,15/full/0/native.jpg)
AND
![](https://ids.lib.harvard.edu/ids/iiif/43158615/940,29,35,13/full/0/native.jpg)
REAL
![](https://ids.lib.harvard.edu/ids/iiif/43158615/526,295,19,10/full/0/native.jpg)
BEANS
![](https://ids.lib.harvard.edu/ids/iiif/43158615/604,100,394,38/full/0/native.jpg)
CLOTHING ROBINSON AND BAKER
![](https://ids.lib.harvard.edu/ids/iiif/43158615/702,109,138,24/full/0/native.jpg)
ROBINSON
![](https://ids.lib.harvard.edu/ids/iiif/43158615/748,312,56,43/full/0/native.jpg)
Peter
![](https://ids.lib.harvard.edu/ids/iiif/43158615/604,119,88,18/full/0/native.jpg)
CLOTHING
![](https://ids.lib.harvard.edu/ids/iiif/43158615/517,255,21,13/full/0/native.jpg)
PEARS
![](https://ids.lib.harvard.edu/ids/iiif/43158615/204,237,35,9/full/0/native.jpg)
REPAIRS
![](https://ids.lib.harvard.edu/ids/iiif/43158615/162,239,30,8/full/0/native.jpg)
PUMPS
![](https://ids.lib.harvard.edu/ids/iiif/43158615/519,277,17,10/full/0/native.jpg)
2-29
![](https://ids.lib.harvard.edu/ids/iiif/43158615/418,378,19,9/full/0/native.jpg)
9336
![](https://ids.lib.harvard.edu/ids/iiif/43158615/824,320,39,36/full/0/native.jpg)
Pan
![](https://ids.lib.harvard.edu/ids/iiif/43158615/164,227,75,13/full/0/native.jpg)
PLUMBING
![](https://ids.lib.harvard.edu/ids/iiif/43158615/481,278,10,8/full/0/native.jpg)
10
![](https://ids.lib.harvard.edu/ids/iiif/43158615/21,235,13,6/full/0/native.jpg)
.H.
![](https://ids.lib.harvard.edu/ids/iiif/43158615/162,237,77,10/full/0/native.jpg)
PUMPS г. REPAIRS
![](https://ids.lib.harvard.edu/ids/iiif/43158615/477,261,17,12/full/0/native.jpg)
RICE
![](https://ids.lib.harvard.edu/ids/iiif/43158615/45,240,35,9/full/0/native.jpg)
SUPPLES
![](https://ids.lib.harvard.edu/ids/iiif/43158615/21,232,58,9/full/0/native.jpg)
.H. ACKEEY
![](https://ids.lib.harvard.edu/ids/iiif/43158615/35,232,43,9/full/0/native.jpg)
ACKEEY
![](https://ids.lib.harvard.edu/ids/iiif/43158615/940,26,74,17/full/0/native.jpg)
REAL ESTAT
![](https://ids.lib.harvard.edu/ids/iiif/43158615/460,220,85,16/full/0/native.jpg)
GROUERY.
![](https://ids.lib.harvard.edu/ids/iiif/43158615/501,268,13,7/full/0/native.jpg)
ae
![](https://ids.lib.harvard.edu/ids/iiif/43158615/646,270,38,21/full/0/native.jpg)
Dater Pan
![](https://ids.lib.harvard.edu/ids/iiif/43158615/977,26,38,14/full/0/native.jpg)
ESTAT
![](https://ids.lib.harvard.edu/ids/iiif/43158615/196,240,5,4/full/0/native.jpg)
г.
![](https://ids.lib.harvard.edu/ids/iiif/43158615/530,312,10,7/full/0/native.jpg)
11
![](https://ids.lib.harvard.edu/ids/iiif/43158615/20,243,23,5/full/0/native.jpg)
ECTRIC
![](https://ids.lib.harvard.edu/ids/iiif/43158615/638,313,12,8/full/0/native.jpg)
SEAU
![](https://ids.lib.harvard.edu/ids/iiif/43158615/684,305,10,8/full/0/native.jpg)
00
![](https://ids.lib.harvard.edu/ids/iiif/43158615/163,28,845,281/full/0/native.jpg)
REAL EST
CLOTHING ROBINSON AND BAKER
PUMPS乙REPAIRS
GROCCRY
PEARS
BEANS
![](https://ids.lib.harvard.edu/ids/iiif/43158615/942,30,38,16/full/0/native.jpg)
REAL
![](https://ids.lib.harvard.edu/ids/iiif/43158615/978,28,30,15/full/0/native.jpg)
EST
![](https://ids.lib.harvard.edu/ids/iiif/43158615/607,118,86,26/full/0/native.jpg)
CLOTHING
![](https://ids.lib.harvard.edu/ids/iiif/43158615/700,109,142,29/full/0/native.jpg)
ROBINSON
![](https://ids.lib.harvard.edu/ids/iiif/43158615/846,107,41,23/full/0/native.jpg)
AND
![](https://ids.lib.harvard.edu/ids/iiif/43158615/890,100,105,27/full/0/native.jpg)
BAKER
![](https://ids.lib.harvard.edu/ids/iiif/43158615/163,240,33,12/full/0/native.jpg)
PUMPS
![](https://ids.lib.harvard.edu/ids/iiif/43158615/197,240,9,10/full/0/native.jpg)
乙
![](https://ids.lib.harvard.edu/ids/iiif/43158615/206,239,38,12/full/0/native.jpg)
REPAIRS
![](https://ids.lib.harvard.edu/ids/iiif/43158615/464,222,82,20/full/0/native.jpg)
GROCCRY
![](https://ids.lib.harvard.edu/ids/iiif/43158615/520,257,20,14/full/0/native.jpg)
PEARS
![](https://ids.lib.harvard.edu/ids/iiif/43158615/528,296,22,13/full/0/native.jpg)
BEANS