Machine Generated Data
Tags
Amazon
created on 2022-01-09
Building | 92.8 | |
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Road | 92.1 | |
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Tarmac | 88.7 | |
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Asphalt | 88.7 | |
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Architecture | 81.7 | |
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Urban | 70.7 | |
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Nature | 70.3 | |
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Symbol | 69.4 | |
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Highway | 68.2 | |
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Freeway | 68.2 | |
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Hotel | 63.6 | |
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City | 63.1 | |
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Town | 63.1 | |
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Tower | 63.1 | |
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Street | 59.3 | |
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Car | 57.3 | |
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Automobile | 57.3 | |
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Vehicle | 57.3 | |
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Transportation | 57.3 | |
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Weather | 56.6 | |
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Boardwalk | 55.7 | |
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Bridge | 55.7 | |
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Theme Park | 55.1 | |
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Amusement Park | 55.1 | |
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Intersection | 55.1 | |
|
Clarifai
created on 2023-10-25
Imagga
created on 2022-01-09
Google
created on 2022-01-09
Black | 89.5 | |
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Black-and-white | 83.9 | |
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Rectangle | 83.3 | |
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Font | 82.4 | |
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Line | 81.9 | |
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City | 73.6 | |
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Monochrome | 73.4 | |
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Monochrome photography | 72.8 | |
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Building | 66.8 | |
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Darkness | 64.6 | |
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Still life photography | 63.1 | |
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Stock photography | 61.8 | |
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Tower | 60.7 | |
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Logo | 57.6 | |
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Landscape | 57.3 | |
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Grass | 57.3 | |
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Billboard | 56.3 | |
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Signage | 54.1 | |
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Art | 52.9 | |
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Street | 52.6 | |
|
Microsoft
created on 2022-01-09
text | 99.8 | |
| ||
ship | 82.6 | |
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black and white | 77.8 | |
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sign | 23.8 | |
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Color Analysis
Categories
Imagga
cars vehicles | 98.4% | |
| ||
food drinks | 1.1% | |
|
Captions
Microsoft
created on 2022-01-09
a close up of a sign | 70% | |
| ||
a sign for a photo | 52.6% | |
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close up of a sign | 52.5% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18810991/518,334,101,72/full/0/native.jpg)
South
![](https://ids.lib.harvard.edu/ids/iiif/18810991/555,444,84,24/full/0/native.jpg)
PLAZA
![](https://ids.lib.harvard.edu/ids/iiif/18810991/541,419,111,29/full/0/native.jpg)
SHOPPING
![](https://ids.lib.harvard.edu/ids/iiif/18810991/454,539,37,10/full/0/native.jpg)
LIGGETT
![](https://ids.lib.harvard.edu/ids/iiif/18810991/409,536,25,9/full/0/native.jpg)
BEAUTY
![](https://ids.lib.harvard.edu/ids/iiif/18810991/516,328,168,78/full/0/native.jpg)
South Gate
![](https://ids.lib.harvard.edu/ids/iiif/18810991/607,328,75,68/full/0/native.jpg)
Gate
![](https://ids.lib.harvard.edu/ids/iiif/18810991/529,540,29,8/full/0/native.jpg)
DRUG
![](https://ids.lib.harvard.edu/ids/iiif/18810991/420,544,19,7/full/0/native.jpg)
SALON
![](https://ids.lib.harvard.edu/ids/iiif/18810991/982,495,39,189/full/0/native.jpg)
42423
![](https://ids.lib.harvard.edu/ids/iiif/18810991/454,538,104,11/full/0/native.jpg)
LIGGETT Perati DRUG
![](https://ids.lib.harvard.edu/ids/iiif/18810991/208,543,15,10/full/0/native.jpg)
Stag
![](https://ids.lib.harvard.edu/ids/iiif/18810991/982,422,40,263/full/0/native.jpg)
--٤١٢٣ 42423
![](https://ids.lib.harvard.edu/ids/iiif/18810991/191,543,32,10/full/0/native.jpg)
und Stag
![](https://ids.lib.harvard.edu/ids/iiif/18810991/494,538,33,11/full/0/native.jpg)
Perati
![](https://ids.lib.harvard.edu/ids/iiif/18810991/365,544,26,9/full/0/native.jpg)
MARRI
![](https://ids.lib.harvard.edu/ids/iiif/18810991/996,422,16,77/full/0/native.jpg)
--٤١٢٣
![](https://ids.lib.harvard.edu/ids/iiif/18810991/191,546,11,6/full/0/native.jpg)
und
![](https://ids.lib.harvard.edu/ids/iiif/18810991/235,540,26,13/full/0/native.jpg)
Cheese
![](https://ids.lib.harvard.edu/ids/iiif/18810991/499,331,126,88/full/0/native.jpg)
Soili
![](https://ids.lib.harvard.edu/ids/iiif/18810991/614,323,81,82/full/0/native.jpg)
Gaite
![](https://ids.lib.harvard.edu/ids/iiif/18810991/539,420,118,34/full/0/native.jpg)
SHOPPING
![](https://ids.lib.harvard.edu/ids/iiif/18810991/449,323,246,233/full/0/native.jpg)
Soili Gaite
.---
SHOPPING
PLAZA
LIG
Resail DRUG!
![](https://ids.lib.harvard.edu/ids/iiif/18810991/569,405,73,20/full/0/native.jpg)
.---
![](https://ids.lib.harvard.edu/ids/iiif/18810991/558,446,84,25/full/0/native.jpg)
PLAZA
![](https://ids.lib.harvard.edu/ids/iiif/18810991/449,540,33,16/full/0/native.jpg)
LIG
![](https://ids.lib.harvard.edu/ids/iiif/18810991/497,537,37,18/full/0/native.jpg)
Resail
![](https://ids.lib.harvard.edu/ids/iiif/18810991/531,537,34,18/full/0/native.jpg)
DRUG!