Machine Generated Data
Tags
Amazon
created on 2022-06-04
Street | 97.2 | |
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Road | 97.2 | |
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City | 97.2 | |
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Urban | 97.2 | |
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Building | 97.2 | |
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Town | 97.2 | |
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Train | 89.4 | |
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Transportation | 89.4 | |
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Vehicle | 89.4 | |
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Metropolis | 82.5 | |
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Flagstone | 78.4 | |
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Puddle | 77.5 | |
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Path | 73.2 | |
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Tarmac | 73.1 | |
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Asphalt | 73.1 | |
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Alley | 72.8 | |
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Alleyway | 72.8 | |
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Nature | 66.7 | |
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Outdoors | 63 | |
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Brick | 62.7 | |
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Crypt | 62.6 | |
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Walkway | 62 | |
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Water | 59.7 | |
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Downtown | 58.1 | |
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Architecture | 56.9 | |
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Clothing | 56.7 | |
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Apparel | 56.7 | |
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Imagga
created on 2022-06-04
architecture | 44.7 | |
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old | 41.8 | |
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building | 39.6 | |
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step | 33.5 | |
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support | 29.3 | |
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city | 28.3 | |
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stone | 28.1 | |
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wall | 26.8 | |
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prison | 25 | |
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device | 24.8 | |
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sidewalk | 24.8 | |
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ancient | 24.2 | |
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brick | 22.7 | |
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street | 22.1 | |
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travel | 21.8 | |
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urban | 20.1 | |
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window | 19.9 | |
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house | 19.4 | |
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cell | 19.3 | |
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correctional institution | 18.5 | |
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door | 18.5 | |
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town | 17.6 | |
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tunnel | 17.5 | |
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construction | 16.3 | |
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tourism | 15.7 | |
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history | 15.2 | |
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exterior | 14.7 | |
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medieval | 14.4 | |
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penal institution | 13.9 | |
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historic | 13.8 | |
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grunge | 13.6 | |
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structure | 13.2 | |
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dirty | 12.7 | |
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road | 12.7 | |
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landmark | 12.6 | |
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tower | 12.5 | |
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passage | 12.5 | |
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passageway | 12.1 | |
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church | 12 | |
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sky | 11.5 | |
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institution | 11.2 | |
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empty | 11.2 | |
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aged | 10.9 | |
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interior | 10.6 | |
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way | 10.6 | |
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antique | 10.4 | |
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dark | 10 | |
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tourist | 10 | |
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vintage | 9.9 | |
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cobblestone | 9.9 | |
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windows | 9.6 | |
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home | 9.6 | |
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scene | 9.5 | |
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buildings | 9.5 | |
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wood | 9.2 | |
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religion | 9 | |
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night | 8.9 | |
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facade | 8.8 | |
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alley | 8.7 | |
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concrete | 8.6 | |
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warehouse | 8.5 | |
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outdoors | 8.2 | |
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room | 8.1 | |
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balcony | 8.1 | |
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light | 8 | |
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narrow | 7.9 | |
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design | 7.9 | |
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art | 7.9 | |
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black | 7.8 | |
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ruin | 7.8 | |
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arch | 7.8 | |
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houses | 7.7 | |
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entrance | 7.7 | |
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culture | 7.7 | |
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traditional | 7.5 | |
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water | 7.3 | |
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industrial | 7.3 | |
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sill | 7.2 | |
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cathedral | 7.1 | |
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roof | 7.1 | |
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Google
created on 2022-06-04
Building | 95 | |
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Black | 89.7 | |
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Rectangle | 87.4 | |
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Black-and-white | 85.1 | |
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Style | 83.9 | |
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Font | 78 | |
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Tints and shades | 77.3 | |
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Monochrome photography | 75.5 | |
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Monochrome | 74.9 | |
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Composite material | 66.7 | |
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Stock photography | 63.8 | |
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Still life photography | 62.6 | |
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Room | 62.6 | |
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History | 61.2 | |
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Facade | 56.8 | |
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Art | 53.3 | |
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City | 51.1 | |
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Microsoft
created on 2022-06-04
text | 94.2 | |
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black and white | 94 | |
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white | 88.7 | |
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street | 83.8 | |
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black | 78.6 | |
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monochrome | 77.9 | |
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building | 75.6 | |
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window | 72.1 | |
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old | 56.6 | |
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Color Analysis
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20488883/324,19,654,652/full/0/native.jpg)
Train | 89.4% | |
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Categories
Imagga
interior objects | 57.5% | |
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streetview architecture | 20.4% | |
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paintings art | 16.1% | |
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food drinks | 2.1% | |
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pets animals | 1.6% | |
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Captions
Microsoft
created on 2022-06-04
a vintage photo of an old building | 75.7% | |
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a vintage photo of a building | 75.6% | |
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a vintage photo of an old building in the rain | 64.6% | |
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Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20488883/200,478,19,8/full/0/native.jpg)
304
![](https://ids.lib.harvard.edu/ids/iiif/20488883/25,478,52,14/full/0/native.jpg)
GENTS.
![](https://ids.lib.harvard.edu/ids/iiif/20488883/979,435,24,8/full/0/native.jpg)
BEEF
![](https://ids.lib.harvard.edu/ids/iiif/20488883/3,462,24,10/full/0/native.jpg)
FOR
![](https://ids.lib.harvard.edu/ids/iiif/20488883/38,443,28,23/full/0/native.jpg)
CA
![](https://ids.lib.harvard.edu/ids/iiif/20488883/0,477,78,14/full/0/native.jpg)
ESE GENTS.
![](https://ids.lib.harvard.edu/ids/iiif/20488883/28,304,121,22/full/0/native.jpg)
DRIGHTON
![](https://ids.lib.harvard.edu/ids/iiif/20488883/-3,436,71,30/full/0/native.jpg)
TON CA
![](https://ids.lib.harvard.edu/ids/iiif/20488883/0,480,24,9/full/0/native.jpg)
ESE
![](https://ids.lib.harvard.edu/ids/iiif/20488883/985,412,15,7/full/0/native.jpg)
308
![](https://ids.lib.harvard.edu/ids/iiif/20488883/157,302,115,21/full/0/native.jpg)
CAFE.30
![](https://ids.lib.harvard.edu/ids/iiif/20488883/0,440,38,19/full/0/native.jpg)
TON
![](https://ids.lib.harvard.edu/ids/iiif/20488883/3,302,269,24/full/0/native.jpg)
a DRIGHTON CAFE.30
![](https://ids.lib.harvard.edu/ids/iiif/20488883/139,455,18,92/full/0/native.jpg)
LUN
![](https://ids.lib.harvard.edu/ids/iiif/20488883/980,454,27,13/full/0/native.jpg)
Pork
![](https://ids.lib.harvard.edu/ids/iiif/20488883/980,471,27,12/full/0/native.jpg)
LAZO
![](https://ids.lib.harvard.edu/ids/iiif/20488883/980,444,26,11/full/0/native.jpg)
LAHY
![](https://ids.lib.harvard.edu/ids/iiif/20488883/45,785,104,24/full/0/native.jpg)
LindellPlace
![](https://ids.lib.harvard.edu/ids/iiif/20488883/980,480,32,13/full/0/native.jpg)
DAYIER
![](https://ids.lib.harvard.edu/ids/iiif/20488883/3,309,27,12/full/0/native.jpg)
a
![](https://ids.lib.harvard.edu/ids/iiif/20488883/0,403,1020,407/full/0/native.jpg)
TON
FOR
*S*GENTS.
ONCE
Landall Place
304
EXA
308
Persek
BEEF
LAME
Pozs
LARG
CAMERA
HEAD
![](https://ids.lib.harvard.edu/ids/iiif/20488883/4,444,36,18/full/0/native.jpg)
TON
![](https://ids.lib.harvard.edu/ids/iiif/20488883/5,463,27,12/full/0/native.jpg)
FOR
![](https://ids.lib.harvard.edu/ids/iiif/20488883/0,480,10,15/full/0/native.jpg)
*
![](https://ids.lib.harvard.edu/ids/iiif/20488883/7,480,12,15/full/0/native.jpg)
S
![](https://ids.lib.harvard.edu/ids/iiif/20488883/27,480,50,15/full/0/native.jpg)
GENTS
![](https://ids.lib.harvard.edu/ids/iiif/20488883/74,480,8,15/full/0/native.jpg)
.
![](https://ids.lib.harvard.edu/ids/iiif/20488883/141,464,19,64/full/0/native.jpg)
ONCE
![](https://ids.lib.harvard.edu/ids/iiif/20488883/48,789,62,20/full/0/native.jpg)
Landall
![](https://ids.lib.harvard.edu/ids/iiif/20488883/106,790,47,20/full/0/native.jpg)
Place
![](https://ids.lib.harvard.edu/ids/iiif/20488883/201,480,23,11/full/0/native.jpg)
304
![](https://ids.lib.harvard.edu/ids/iiif/20488883/979,404,18,11/full/0/native.jpg)
EXA
![](https://ids.lib.harvard.edu/ids/iiif/20488883/984,410,21,15/full/0/native.jpg)
308
![](https://ids.lib.harvard.edu/ids/iiif/20488883/979,422,33,13/full/0/native.jpg)
Persek
![](https://ids.lib.harvard.edu/ids/iiif/20488883/980,436,29,15/full/0/native.jpg)
BEEF
![](https://ids.lib.harvard.edu/ids/iiif/20488883/982,446,31,14/full/0/native.jpg)
LAME
![](https://ids.lib.harvard.edu/ids/iiif/20488883/982,457,29,14/full/0/native.jpg)
Pozs
![](https://ids.lib.harvard.edu/ids/iiif/20488883/982,472,29,14/full/0/native.jpg)
LARG
![](https://ids.lib.harvard.edu/ids/iiif/20488883/981,481,38,14/full/0/native.jpg)
CAMERA
![](https://ids.lib.harvard.edu/ids/iiif/20488883/989,493,29,13/full/0/native.jpg)
HEAD