Machine Generated Data
Tags
Amazon
created on 2023-01-24
Neighborhood | 99.9 | |
| ||
Sidewalk | 99.9 | |
| ||
Path | 99.9 | |
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License Plate | 99.7 | |
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Vehicle | 99.7 | |
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Transportation | 99.7 | |
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Car | 99.6 | |
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Car | 97.3 | |
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Car | 96.1 | |
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Spoke | 92.9 | |
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Machine | 92.9 | |
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Bird | 87.6 | |
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Animal | 87.6 | |
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Indoors | 73.7 | |
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Restaurant | 73.7 | |
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Road | 70.1 | |
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Canopy | 68.1 | |
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Awning | 68.1 | |
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Motel | 63 | |
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Hotel | 63 | |
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Building | 63 | |
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Architecture | 63 | |
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Wheel | 60.8 | |
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City | 57.4 | |
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Coupe | 57 | |
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Sports Car | 57 | |
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Alloy Wheel | 56.9 | |
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Tire | 56.9 | |
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Car Wheel | 56.9 | |
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Intersection | 56.8 | |
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Sign | 56.5 | |
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Symbol | 56.5 | |
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Diner | 55.7 | |
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Food | 55.7 | |
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Urban | 55.2 | |
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Shelter | 55.2 | |
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Outdoors | 55.2 | |
|
Clarifai
created on 2023-10-13
street | 99.7 | |
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monochrome | 99.4 | |
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people | 99.3 | |
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town | 95.7 | |
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car | 93.8 | |
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gas station | 93.7 | |
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road | 90.6 | |
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transportation system | 90.3 | |
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no person | 88.1 | |
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vehicle | 85.9 | |
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pavement | 85.5 | |
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city | 84.8 | |
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classic | 84.7 | |
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black and white | 84.2 | |
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architecture | 84.1 | |
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adult | 82.2 | |
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vintage | 82.2 | |
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man | 81.8 | |
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group together | 81.6 | |
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square | 81.1 | |
|
Imagga
created on 2023-01-24
garage | 78.5 | |
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car | 64.4 | |
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road | 39.7 | |
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transportation | 30.5 | |
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sidewalk | 29.5 | |
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travel | 28.9 | |
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street | 24.8 | |
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motor vehicle | 23 | |
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transport | 22.8 | |
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drive | 20.8 | |
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vehicle | 18.8 | |
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sky | 18.5 | |
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urban | 18.3 | |
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building | 18.2 | |
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automobile | 18.2 | |
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house | 17.5 | |
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minivan | 17.2 | |
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landscape | 16.4 | |
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traffic | 16.1 | |
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city | 15.8 | |
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auto | 15.3 | |
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vacation | 14.7 | |
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cars | 14.7 | |
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architecture | 14.2 | |
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truck | 14.2 | |
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passenger van | 13.7 | |
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driving | 13.5 | |
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old | 13.2 | |
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van | 13.2 | |
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outdoors | 12.8 | |
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highway | 12.5 | |
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tourist | 11.8 | |
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holiday | 11.5 | |
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rural | 11.4 | |
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structure | 10.9 | |
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tree | 10.8 | |
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trees | 10.7 | |
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scene | 10.4 | |
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home | 10.4 | |
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tourism | 9.9 | |
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new | 9.7 | |
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summer | 9.6 | |
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residential | 9.6 | |
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mountains | 9.3 | |
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speed | 9.2 | |
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park | 9.1 | |
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intersection | 9 | |
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asphalt | 8.8 | |
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motor | 8.7 | |
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construction | 8.6 | |
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estate | 8.5 | |
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snow | 8.5 | |
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beach | 8.4 | |
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exterior | 8.3 | |
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vintage | 8.3 | |
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freedom | 8.2 | |
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light | 8 | |
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beach wagon | 8 | |
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wheeled vehicle | 8 | |
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sea | 7.8 | |
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wheels | 7.8 | |
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residence | 7.8 | |
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sunny | 7.7 | |
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adventure | 7.6 | |
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wheel | 7.5 | |
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brick | 7.5 | |
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town | 7.4 | |
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land | 7.4 | |
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business | 7.3 | |
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sun | 7.2 | |
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Google
created on 2023-01-24
Automotive parking light | 97.7 | |
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Car | 96.1 | |
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Tire | 95.2 | |
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Vehicle | 94.6 | |
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Vehicle registration plate | 93.4 | |
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Building | 91.4 | |
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Automotive lighting | 90.6 | |
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Motor vehicle | 90.2 | |
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Hood | 89.2 | |
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Window | 84 | |
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Automotive design | 82.3 | |
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Automotive tail & brake light | 80.8 | |
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Notchback | 80.8 | |
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Automotive exterior | 80.1 | |
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Sky | 79.6 | |
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Bumper | 77.3 | |
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House | 77.3 | |
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Kit car | 77.1 | |
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Road | 75.9 | |
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Classic car | 74.1 | |
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Microsoft
created on 2023-01-24
outdoor | 99.7 | |
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building | 99.7 | |
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text | 98.1 | |
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road | 96.3 | |
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car | 95.3 | |
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vehicle | 95.2 | |
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black and white | 93.2 | |
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land vehicle | 92.8 | |
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street | 78.4 | |
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house | 76.4 | |
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monochrome | 67.8 | |
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parked | 67.5 | |
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wheel | 58.4 | |
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sign | 17 | |
|
Color Analysis
Feature analysis
Categories
Imagga
streetview architecture | 43.2% | |
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nature landscape | 30.5% | |
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cars vehicles | 23.5% | |
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beaches seaside | 2.1% | |
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Captions
Microsoft
created on 2023-01-24
a car parked on the side of a building | 89.3% | |
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a car parked in front of a house | 89.2% | |
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a car parked on the side of a house | 89.1% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/496065194/196,87,460,162/full/0/native.jpg)
MOTEL
![](https://ids.lib.harvard.edu/ids/iiif/496065194/658,370,55,44/full/0/native.jpg)
50
![](https://ids.lib.harvard.edu/ids/iiif/496065194/1235,987,48,26/full/0/native.jpg)
AUZ
![](https://ids.lib.harvard.edu/ids/iiif/496065194/1188,987,95,28/full/0/native.jpg)
135 AUZ
![](https://ids.lib.harvard.edu/ids/iiif/496065194/563,366,84,154/full/0/native.jpg)
3
![](https://ids.lib.harvard.edu/ids/iiif/496065194/213,32,429,101/full/0/native.jpg)
MITCHELL'S
![](https://ids.lib.harvard.edu/ids/iiif/496065194/1188,987,42,28/full/0/native.jpg)
135
![](https://ids.lib.harvard.edu/ids/iiif/496065194/440,585,23,8/full/0/native.jpg)
RE
![](https://ids.lib.harvard.edu/ids/iiif/496065194/401,231,215,52/full/0/native.jpg)
VACANCY
![](https://ids.lib.harvard.edu/ids/iiif/496065194/1051,1020,102,30/full/0/native.jpg)
AMERICA
![](https://ids.lib.harvard.edu/ids/iiif/496065194/392,678,33,15/full/0/native.jpg)
NO
![](https://ids.lib.harvard.edu/ids/iiif/496065194/400,582,63,13/full/0/native.jpg)
FOR RE
![](https://ids.lib.harvard.edu/ids/iiif/496065194/400,582,31,13/full/0/native.jpg)
FOR
![](https://ids.lib.harvard.edu/ids/iiif/496065194/318,415,45,57/full/0/native.jpg)
L
![](https://ids.lib.harvard.edu/ids/iiif/496065194/659,467,28,13/full/0/native.jpg)
AND
![](https://ids.lib.harvard.edu/ids/iiif/496065194/530,382,23,79/full/0/native.jpg)
$
![](https://ids.lib.harvard.edu/ids/iiif/496065194/316,343,47,55/full/0/native.jpg)
E
![](https://ids.lib.harvard.edu/ids/iiif/496065194/1026,1048,35,11/full/0/native.jpg)
LOVE
![](https://ids.lib.harvard.edu/ids/iiif/496065194/314,276,42,48/full/0/native.jpg)
T
![](https://ids.lib.harvard.edu/ids/iiif/496065194/659,467,45,13/full/0/native.jpg)
AND UP
![](https://ids.lib.harvard.edu/ids/iiif/496065194/391,677,79,20/full/0/native.jpg)
NO UAC
![](https://ids.lib.harvard.edu/ids/iiif/496065194/693,469,11,10/full/0/native.jpg)
UP
![](https://ids.lib.harvard.edu/ids/iiif/496065194/1026,1045,109,15/full/0/native.jpg)
LOVE IT - LEAVE
![](https://ids.lib.harvard.edu/ids/iiif/496065194/375,597,92,21/full/0/native.jpg)
FURNIS
![](https://ids.lib.harvard.edu/ids/iiif/496065194/436,679,33,17/full/0/native.jpg)
UAC
![](https://ids.lib.harvard.edu/ids/iiif/496065194/368,345,50,38/full/0/native.jpg)
lobj
![](https://ids.lib.harvard.edu/ids/iiif/496065194/1067,1045,69,15/full/0/native.jpg)
IT - LEAVE
![](https://ids.lib.harvard.edu/ids/iiif/496065194/385,619,82,28/full/0/native.jpg)
ART
![](https://ids.lib.harvard.edu/ids/iiif/496065194/206,37,1083,1027/full/0/native.jpg)
MITCHELL'S
MOTEL
NO VACANCY
sobil
FOR RE
FURNISI
NO URCI
50
$35
AND UP
AMERICA
LOVE IT LEAVE IT
135 AUZ
![](https://ids.lib.harvard.edu/ids/iiif/496065194/224,37,413,96/full/0/native.jpg)
MITCHELL'S
![](https://ids.lib.harvard.edu/ids/iiif/496065194/211,95,435,147/full/0/native.jpg)
MOTEL
![](https://ids.lib.harvard.edu/ids/iiif/496065194/296,224,63,32/full/0/native.jpg)
NO
![](https://ids.lib.harvard.edu/ids/iiif/496065194/406,235,207,49/full/0/native.jpg)
VACANCY
![](https://ids.lib.harvard.edu/ids/iiif/496065194/361,344,71,45/full/0/native.jpg)
sobil
![](https://ids.lib.harvard.edu/ids/iiif/496065194/400,584,36,15/full/0/native.jpg)
FOR
![](https://ids.lib.harvard.edu/ids/iiif/496065194/442,584,24,15/full/0/native.jpg)
RE
![](https://ids.lib.harvard.edu/ids/iiif/496065194/378,600,96,23/full/0/native.jpg)
FURNISI
![](https://ids.lib.harvard.edu/ids/iiif/496065194/437,681,37,19/full/0/native.jpg)
URCI
![](https://ids.lib.harvard.edu/ids/iiif/496065194/660,376,59,41/full/0/native.jpg)
50
![](https://ids.lib.harvard.edu/ids/iiif/496065194/519,377,57,139/full/0/native.jpg)
$
![](https://ids.lib.harvard.edu/ids/iiif/496065194/561,377,151,139/full/0/native.jpg)
35
![](https://ids.lib.harvard.edu/ids/iiif/496065194/661,467,31,16/full/0/native.jpg)
AND
![](https://ids.lib.harvard.edu/ids/iiif/496065194/692,469,20,15/full/0/native.jpg)
UP
![](https://ids.lib.harvard.edu/ids/iiif/496065194/1056,1024,100,28/full/0/native.jpg)
AMERICA
![](https://ids.lib.harvard.edu/ids/iiif/496065194/1034,1047,32,16/full/0/native.jpg)
LOVE
![](https://ids.lib.harvard.edu/ids/iiif/496065194/1069,1048,16,14/full/0/native.jpg)
IT
![](https://ids.lib.harvard.edu/ids/iiif/496065194/1096,1046,41,16/full/0/native.jpg)
LEAVE
![](https://ids.lib.harvard.edu/ids/iiif/496065194/1188,990,44,28/full/0/native.jpg)
135
![](https://ids.lib.harvard.edu/ids/iiif/496065194/1235,989,53,27/full/0/native.jpg)
AUZ