Machine Generated Data
Tags
Amazon
created on 2022-06-04
Nature | 88.8 | |
| ||
Walkway | 88.7 | |
| ||
Path | 88.7 | |
| ||
Outdoors | 88.5 | |
| ||
Urban | 85.9 | |
| ||
Building | 82.6 | |
| ||
Neighborhood | 69.8 | |
| ||
Weather | 65.1 | |
| ||
Intersection | 64.7 | |
| ||
Road | 64.7 | |
| ||
Tarmac | 64.1 | |
| ||
Asphalt | 64.1 | |
| ||
Spoke | 63.9 | |
| ||
Machine | 63.9 | |
| ||
Vehicle | 62.5 | |
| ||
Transportation | 62.5 | |
| ||
Shelter | 61 | |
| ||
Countryside | 61 | |
| ||
Rural | 61 | |
| ||
Home Decor | 60.2 | |
| ||
City | 59.9 | |
| ||
Town | 59.9 | |
| ||
Ice | 59.8 | |
| ||
Meal | 58.6 | |
| ||
Food | 58.6 | |
| ||
Housing | 58.5 | |
| ||
High Rise | 57.9 | |
| ||
Sidewalk | 57.8 | |
| ||
Pavement | 57.8 | |
| ||
Window | 57 | |
| ||
Spire | 56.2 | |
| ||
Architecture | 56.2 | |
| ||
Tower | 56.2 | |
| ||
Steeple | 56.2 | |
|
Imagga
created on 2022-06-04
architecture | 82 | |
| ||
building | 61.5 | |
| ||
office | 48.4 | |
| ||
city | 38.3 | |
| ||
house | 35.1 | |
| ||
facade | 34.9 | |
| ||
town | 31.6 | |
| ||
old | 30 | |
| ||
center | 27.5 | |
| ||
structure | 25 | |
| ||
travel | 24 | |
| ||
tower | 22.4 | |
| ||
sky | 22.4 | |
| ||
tourism | 22.3 | |
| ||
houses | 20.4 | |
| ||
urban | 18.4 | |
| ||
buildings | 18 | |
| ||
palace | 17.7 | |
| ||
history | 17 | |
| ||
historical | 16 | |
| ||
street | 15.7 | |
| ||
university | 15.6 | |
| ||
historic | 15.6 | |
| ||
landmark | 15.4 | |
| ||
exterior | 14.8 | |
| ||
ancient | 14.7 | |
| ||
window | 14.1 | |
| ||
home | 13.6 | |
| ||
residential | 13.4 | |
| ||
river | 13.4 | |
| ||
castle | 13.1 | |
| ||
modern | 12.6 | |
| ||
windows | 12.5 | |
| ||
roof | 12.4 | |
| ||
cityscape | 12.3 | |
| ||
cinema | 12.3 | |
| ||
stone | 11.8 | |
| ||
tourist | 11.8 | |
| ||
village | 11.5 | |
| ||
capital | 11.4 | |
| ||
wall | 10.4 | |
| ||
residence | 10 | |
| ||
theater | 9.8 | |
| ||
property | 9.7 | |
| ||
architectural | 9.6 | |
| ||
construction | 9.4 | |
| ||
summer | 9 | |
| ||
landscape | 8.9 | |
| ||
skyline | 8.6 | |
| ||
estate | 8.6 | |
| ||
famous | 8.4 | |
| ||
balcony | 8.3 | |
| ||
water | 8 | |
| ||
homes | 7.9 | |
| ||
downtown | 7.7 | |
| ||
medieval | 7.7 | |
| ||
apartment | 7.7 | |
| ||
real | 7.6 | |
| ||
perspective | 7.5 | |
| ||
destination | 7.5 | |
| ||
monument | 7.5 | |
| ||
boat | 7.5 | |
| ||
vintage | 7.5 | |
| ||
square | 7.3 | |
| ||
glass | 7 | |
|
Google
created on 2022-06-04
Building | 96 | |
| ||
Property | 94.2 | |
| ||
Window | 93.9 | |
| ||
Black-and-white | 85.2 | |
| ||
Motor vehicle | 83 | |
| ||
Font | 80.5 | |
| ||
Residential area | 79.1 | |
| ||
Facade | 79 | |
| ||
City | 78.3 | |
| ||
Landmark | 77.5 | |
| ||
House | 76.1 | |
| ||
Monochrome | 73.5 | |
| ||
Monochrome photography | 72.9 | |
| ||
Mixed-use | 71.1 | |
| ||
Automotive lighting | 68.1 | |
| ||
Apartment | 67.6 | |
| ||
Street | 65.9 | |
| ||
History | 65 | |
| ||
Home | 64.5 | |
| ||
Night | 62.4 | |
|
Microsoft
created on 2022-06-04
building | 99.8 | |
| ||
black and white | 94 | |
| ||
window | 92.8 | |
| ||
house | 91.3 | |
| ||
outdoor | 85.5 | |
| ||
white | 64.1 | |
| ||
text | 60.4 | |
| ||
monochrome | 57.3 | |
|
Color Analysis
Categories
Imagga
streetview architecture | 56.7% | |
| ||
paintings art | 20.2% | |
| ||
cars vehicles | 19% | |
| ||
interior objects | 3.1% | |
|
Captions
Microsoft
created on 2022-06-04
a large building | 86.6% | |
| ||
a large building in the background | 86.5% | |
| ||
a store inside of a building | 85% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20489307/375,420,57,13/full/0/native.jpg)
UNION
![](https://ids.lib.harvard.edu/ids/iiif/20489307/569,505,40,14/full/0/native.jpg)
PANTS
![](https://ids.lib.harvard.edu/ids/iiif/20489307/375,418,119,16/full/0/native.jpg)
UNION MADE
![](https://ids.lib.harvard.edu/ids/iiif/20489307/441,418,52,15/full/0/native.jpg)
MADE
![](https://ids.lib.harvard.edu/ids/iiif/20489307/510,506,40,16/full/0/native.jpg)
COATS
![](https://ids.lib.harvard.edu/ids/iiif/20489307/102,452,24,13/full/0/native.jpg)
BREAD
![](https://ids.lib.harvard.edu/ids/iiif/20489307/57,442,37,16/full/0/native.jpg)
M.Barron
![](https://ids.lib.harvard.edu/ids/iiif/20489307/240,424,75,23/full/0/native.jpg)
CLOTHING
![](https://ids.lib.harvard.edu/ids/iiif/20489307/200,424,116,26/full/0/native.jpg)
MISFIT CLOTHING
![](https://ids.lib.harvard.edu/ids/iiif/20489307/201,434,36,16/full/0/native.jpg)
MISFIT
![](https://ids.lib.harvard.edu/ids/iiif/20489307/531,534,13,6/full/0/native.jpg)
THE
![](https://ids.lib.harvard.edu/ids/iiif/20489307/518,522,24,10/full/0/native.jpg)
SOLD
![](https://ids.lib.harvard.edu/ids/iiif/20489307/545,523,24,8/full/0/native.jpg)
UPON
![](https://ids.lib.harvard.edu/ids/iiif/20489307/545,531,47,10/full/0/native.jpg)
GUARANTEED
![](https://ids.lib.harvard.edu/ids/iiif/20489307/530,531,80,11/full/0/native.jpg)
THE GUARANTEED KIND
![](https://ids.lib.harvard.edu/ids/iiif/20489307/98,440,31,13/full/0/native.jpg)
BUTTERNUT
![](https://ids.lib.harvard.edu/ids/iiif/20489307/592,531,18,9/full/0/native.jpg)
KIND
![](https://ids.lib.harvard.edu/ids/iiif/20489307/156,544,16,9/full/0/native.jpg)
DATS
![](https://ids.lib.harvard.edu/ids/iiif/20489307/510,505,98,17/full/0/native.jpg)
COATS & PANTS
![](https://ids.lib.harvard.edu/ids/iiif/20489307/176,441,10,11/full/0/native.jpg)
NI
![](https://ids.lib.harvard.edu/ids/iiif/20489307/518,521,81,10/full/0/native.jpg)
SOLD UPON MERIT
![](https://ids.lib.harvard.edu/ids/iiif/20489307/373,406,24,7/full/0/native.jpg)
SILVER
![](https://ids.lib.harvard.edu/ids/iiif/20489307/154,500,16,10/full/0/native.jpg)
HOES
![](https://ids.lib.harvard.edu/ids/iiif/20489307/553,506,10,13/full/0/native.jpg)
&
![](https://ids.lib.harvard.edu/ids/iiif/20489307/571,521,28,9/full/0/native.jpg)
MERIT
![](https://ids.lib.harvard.edu/ids/iiif/20489307/373,406,40,7/full/0/native.jpg)
SILVER ST.
![](https://ids.lib.harvard.edu/ids/iiif/20489307/516,489,89,17/full/0/native.jpg)
OVERALLS.
![](https://ids.lib.harvard.edu/ids/iiif/20489307/78,457,20,10/full/0/native.jpg)
-
![](https://ids.lib.harvard.edu/ids/iiif/20489307/10,463,27,10/full/0/native.jpg)
.. BREAD
![](https://ids.lib.harvard.edu/ids/iiif/20489307/401,407,12,6/full/0/native.jpg)
ST.
![](https://ids.lib.harvard.edu/ids/iiif/20489307/569,417,29,10/full/0/native.jpg)
HONOR
![](https://ids.lib.harvard.edu/ids/iiif/20489307/544,417,54,10/full/0/native.jpg)
FROM HONOR
![](https://ids.lib.harvard.edu/ids/iiif/20489307/58,457,40,12/full/0/native.jpg)
I -
![](https://ids.lib.harvard.edu/ids/iiif/20489307/544,417,22,8/full/0/native.jpg)
FROM
![](https://ids.lib.harvard.edu/ids/iiif/20489307/10,468,10,5/full/0/native.jpg)
..
![](https://ids.lib.harvard.edu/ids/iiif/20489307/8,448,30,16/full/0/native.jpg)
Opernot
![](https://ids.lib.harvard.edu/ids/iiif/20489307/154,487,16,10/full/0/native.jpg)
0013
![](https://ids.lib.harvard.edu/ids/iiif/20489307/59,459,19,9/full/0/native.jpg)
I
![](https://ids.lib.harvard.edu/ids/iiif/20489307/0,513,8,6/full/0/native.jpg)
قه
![](https://ids.lib.harvard.edu/ids/iiif/20489307/0,504,13,6/full/0/native.jpg)
Like
![](https://ids.lib.harvard.edu/ids/iiif/20489307/155,514,16,10/full/0/native.jpg)
1661
![](https://ids.lib.harvard.edu/ids/iiif/20489307/-1,518,33,12/full/0/native.jpg)
& PRODUCTIONS
![](https://ids.lib.harvard.edu/ids/iiif/20489307/10,407,605,141/full/0/native.jpg)
Cernat
BREAD
500
M.Barron BUTTERNUT
BREAD
MISFIT CLOTHING
M
SILVER ST
UNION MADE
0295
SPON HEMOR
OVERALLS,
COATS & PANTS
SOLD UPON MERIT
THE GUARANTEED KIND
![](https://ids.lib.harvard.edu/ids/iiif/20489307/10,450,31,17/full/0/native.jpg)
Cernat
![](https://ids.lib.harvard.edu/ids/iiif/20489307/19,462,24,15/full/0/native.jpg)
BREAD
![](https://ids.lib.harvard.edu/ids/iiif/20489307/16,522,18,10/full/0/native.jpg)
500
![](https://ids.lib.harvard.edu/ids/iiif/20489307/58,444,39,20/full/0/native.jpg)
M.Barron
![](https://ids.lib.harvard.edu/ids/iiif/20489307/98,441,37,18/full/0/native.jpg)
BUTTERNUT
![](https://ids.lib.harvard.edu/ids/iiif/20489307/203,434,38,21/full/0/native.jpg)
MISFIT
![](https://ids.lib.harvard.edu/ids/iiif/20489307/242,426,75,24/full/0/native.jpg)
CLOTHING
![](https://ids.lib.harvard.edu/ids/iiif/20489307/238,486,16,16/full/0/native.jpg)
M
![](https://ids.lib.harvard.edu/ids/iiif/20489307/373,408,29,12/full/0/native.jpg)
SILVER
![](https://ids.lib.harvard.edu/ids/iiif/20489307/402,408,15,12/full/0/native.jpg)
ST
![](https://ids.lib.harvard.edu/ids/iiif/20489307/376,419,60,20/full/0/native.jpg)
UNION
![](https://ids.lib.harvard.edu/ids/iiif/20489307/442,419,55,19/full/0/native.jpg)
MADE
![](https://ids.lib.harvard.edu/ids/iiif/20489307/404,475,61,17/full/0/native.jpg)
0295
![](https://ids.lib.harvard.edu/ids/iiif/20489307/547,418,23,12/full/0/native.jpg)
SPON
![](https://ids.lib.harvard.edu/ids/iiif/20489307/569,418,33,11/full/0/native.jpg)
HEMOR
![](https://ids.lib.harvard.edu/ids/iiif/20489307/518,491,87,18/full/0/native.jpg)
OVERALLS
![](https://ids.lib.harvard.edu/ids/iiif/20489307/601,491,8,16/full/0/native.jpg)
,
![](https://ids.lib.harvard.edu/ids/iiif/20489307/512,507,41,19/full/0/native.jpg)
COATS
![](https://ids.lib.harvard.edu/ids/iiif/20489307/554,507,13,17/full/0/native.jpg)
&
![](https://ids.lib.harvard.edu/ids/iiif/20489307/569,505,43,19/full/0/native.jpg)
PANTS
![](https://ids.lib.harvard.edu/ids/iiif/20489307/520,523,27,14/full/0/native.jpg)
SOLD
![](https://ids.lib.harvard.edu/ids/iiif/20489307/546,522,26,14/full/0/native.jpg)
UPON
![](https://ids.lib.harvard.edu/ids/iiif/20489307/572,521,31,14/full/0/native.jpg)
MERIT
![](https://ids.lib.harvard.edu/ids/iiif/20489307/531,533,18,15/full/0/native.jpg)
THE
![](https://ids.lib.harvard.edu/ids/iiif/20489307/546,531,49,16/full/0/native.jpg)
GUARANTEED
![](https://ids.lib.harvard.edu/ids/iiif/20489307/591,531,23,15/full/0/native.jpg)
KIND