Machine Generated Data
Tags
Amazon
created on 2022-01-09
Clarifai
created on 2023-10-25
gas station | 99.8 | |
| ||
people | 99.8 | |
| ||
vehicle | 98 | |
| ||
adult | 96.8 | |
| ||
group together | 96.3 | |
| ||
nozzle | 95.7 | |
| ||
man | 94.2 | |
| ||
transportation system | 93.7 | |
| ||
hose | 93 | |
| ||
pump | 92.9 | |
| ||
two | 92.7 | |
| ||
group | 92.3 | |
| ||
monochrome | 87.5 | |
| ||
one | 85.3 | |
| ||
fuel | 85.1 | |
| ||
petroleum | 85.1 | |
| ||
gasoline | 85 | |
| ||
three | 81.7 | |
| ||
truck | 81.4 | |
| ||
actor | 79.6 | |
|
Imagga
created on 2022-01-09
gas pump | 53.4 | |
| ||
pump | 43.4 | |
| ||
shopping cart | 35.7 | |
| ||
mechanical device | 31.6 | |
| ||
handcart | 28.9 | |
| ||
wheeled vehicle | 26.3 | |
| ||
mechanism | 21.4 | |
| ||
television | 18.4 | |
| ||
container | 17 | |
| ||
device | 14.7 | |
| ||
sky | 14.7 | |
| ||
building | 13.9 | |
| ||
industry | 13.7 | |
| ||
transportation | 13.4 | |
| ||
winter | 12.8 | |
| ||
road | 12.6 | |
| ||
man | 12.1 | |
| ||
travel | 12 | |
| ||
street | 12 | |
| ||
industrial | 11.8 | |
| ||
city | 11.6 | |
| ||
vacation | 11.4 | |
| ||
urban | 11.4 | |
| ||
old | 11.1 | |
| ||
snow | 10.9 | |
| ||
business | 10.9 | |
| ||
equipment | 10.4 | |
| ||
work | 10.3 | |
| ||
vehicle | 10 | |
| ||
outdoors | 9.7 | |
| ||
landscape | 9.7 | |
| ||
people | 9.5 | |
| ||
cold | 9.5 | |
| ||
construction | 9.4 | |
| ||
architecture | 9.4 | |
| ||
danger | 9.1 | |
| ||
environment | 9 | |
| ||
destruction | 8.8 | |
| ||
gas | 8.7 | |
| ||
male | 8.5 | |
| ||
structure | 8.5 | |
| ||
clouds | 8.4 | |
| ||
sign | 8.3 | |
| ||
conveyance | 8.3 | |
| ||
protection | 8.2 | |
| ||
scenery | 8.1 | |
| ||
trees | 8 | |
| ||
day | 7.8 | |
| ||
sea | 7.8 | |
| ||
car | 7.8 | |
| ||
broadcasting | 7.7 | |
| ||
outdoor | 7.6 | |
| ||
machine | 7.6 | |
| ||
house | 7.5 | |
| ||
person | 7.4 | |
| ||
mountains | 7.4 | |
| ||
truck | 7.4 | |
| ||
telecommunication system | 7.2 | |
| ||
seller | 7.2 | |
| ||
mountain | 7.1 | |
| ||
summer | 7.1 | |
| ||
working | 7.1 | |
|
Google
created on 2022-01-09
Tire | 93 | |
| ||
Wheel | 92 | |
| ||
Black | 89.5 | |
| ||
Motor vehicle | 86.5 | |
| ||
Vehicle | 85.4 | |
| ||
Black-and-white | 84.1 | |
| ||
Style | 83.9 | |
| ||
Truck | 79.3 | |
| ||
Gas | 77.2 | |
| ||
Monochrome photography | 75.8 | |
| ||
Gas pump | 74.6 | |
| ||
Monochrome | 74.1 | |
| ||
Machine | 71 | |
| ||
Advertising | 69.5 | |
| ||
Street | 68.3 | |
| ||
Electricity | 66.7 | |
| ||
Tree | 65.3 | |
| ||
Car | 65.2 | |
| ||
Stock photography | 64.3 | |
| ||
Building | 63.4 | |
|
Microsoft
created on 2022-01-09
text | 99.1 | |
| ||
outdoor | 99 | |
| ||
vehicle | 91.4 | |
| ||
land vehicle | 87.2 | |
| ||
person | 80.4 | |
| ||
street | 75.5 | |
| ||
black and white | 69.2 | |
| ||
car | 65.7 | |
|
Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18791052/535,303,31,38/full/0/native.jpg)
AWS Rekognition
Age | 34-42 |
Gender | Male, 100% |
Calm | 93.7% |
Angry | 5.8% |
Confused | 0.2% |
Happy | 0.1% |
Sad | 0.1% |
Surprised | 0.1% |
Disgusted | 0% |
Fear | 0% |
![](https://ids.lib.harvard.edu/ids/iiif/18791052/527,289,46,54/full/0/native.jpg)
Google Vision
Surprise | Very unlikely |
Anger | Very unlikely |
Sorrow | Very unlikely |
Joy | Unlikely |
Headwear | Very likely |
Blurred | Very unlikely |
Feature analysis
Categories
Imagga
streetview architecture | 47.5% | |
| ||
nature landscape | 29.6% | |
| ||
cars vehicles | 9.1% | |
| ||
paintings art | 8% | |
| ||
beaches seaside | 5% | |
|
Captions
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18791052/715,255,38,49/full/0/native.jpg)
64
![](https://ids.lib.harvard.edu/ids/iiif/18791052/700,441,50,9/full/0/native.jpg)
UNLEADED
![](https://ids.lib.harvard.edu/ids/iiif/18791052/759,254,9,24/full/0/native.jpg)
9
![](https://ids.lib.harvard.edu/ids/iiif/18791052/302,321,29,8/full/0/native.jpg)
FOREIGN
![](https://ids.lib.harvard.edu/ids/iiif/18791052/641,194,225,49/full/0/native.jpg)
TEXACO
![](https://ids.lib.harvard.edu/ids/iiif/18791052/180,261,63,21/full/0/native.jpg)
CONDITIONER
![](https://ids.lib.harvard.edu/ids/iiif/18791052/969,399,20,10/full/0/native.jpg)
CH
![](https://ids.lib.harvard.edu/ids/iiif/18791052/300,330,12,8/full/0/native.jpg)
CAR
![](https://ids.lib.harvard.edu/ids/iiif/18791052/934,540,16,9/full/0/native.jpg)
and
![](https://ids.lib.harvard.edu/ids/iiif/18791052/784,267,32,9/full/0/native.jpg)
SUPER
![](https://ids.lib.harvard.edu/ids/iiif/18791052/499,292,20,9/full/0/native.jpg)
ION
![](https://ids.lib.harvard.edu/ids/iiif/18791052/927,462,67,14/full/0/native.jpg)
PREMIUM
![](https://ids.lib.harvard.edu/ids/iiif/18791052/933,538,62,18/full/0/native.jpg)
and detergent
![](https://ids.lib.harvard.edu/ids/iiif/18791052/944,549,41,14/full/0/native.jpg)
additives
![](https://ids.lib.harvard.edu/ids/iiif/18791052/784,264,84,13/full/0/native.jpg)
SUPER SERVICE
![](https://ids.lib.harvard.edu/ids/iiif/18791052/824,264,44,11/full/0/native.jpg)
SERVICE
![](https://ids.lib.harvard.edu/ids/iiif/18791052/298,308,36,11/full/0/native.jpg)
AMERICAN
![](https://ids.lib.harvard.edu/ids/iiif/18791052/949,538,46,18/full/0/native.jpg)
detergent
![](https://ids.lib.harvard.edu/ids/iiif/18791052/309,282,40,11/full/0/native.jpg)
AUTO
![](https://ids.lib.harvard.edu/ids/iiif/18791052/940,530,46,13/full/0/native.jpg)
protective
![](https://ids.lib.harvard.edu/ids/iiif/18791052/976,374,15,19/full/0/native.jpg)
S
![](https://ids.lib.harvard.edu/ids/iiif/18791052/298,346,40,14/full/0/native.jpg)
REGISTERED
![](https://ids.lib.harvard.edu/ids/iiif/18791052/725,396,44,11/full/0/native.jpg)
UNLEAD
![](https://ids.lib.harvard.edu/ids/iiif/18791052/391,297,8,8/full/0/native.jpg)
M
![](https://ids.lib.harvard.edu/ids/iiif/18791052/304,289,51,13/full/0/native.jpg)
IREPAIRS
![](https://ids.lib.harvard.edu/ids/iiif/18791052/783,274,66,17/full/0/native.jpg)
581-9353
![](https://ids.lib.harvard.edu/ids/iiif/18791052/688,396,24,8/full/0/native.jpg)
Lead-fre
![](https://ids.lib.harvard.edu/ids/iiif/18791052/470,277,10,4/full/0/native.jpg)
AND
![](https://ids.lib.harvard.edu/ids/iiif/18791052/162,261,81,22/full/0/native.jpg)
AIR CONDITIONER
![](https://ids.lib.harvard.edu/ids/iiif/18791052/300,329,37,8/full/0/native.jpg)
CAR REFAIRS
![](https://ids.lib.harvard.edu/ids/iiif/18791052/941,513,48,13/full/0/native.jpg)
Wish protective
![](https://ids.lib.harvard.edu/ids/iiif/18791052/326,358,6,4/full/0/native.jpg)
-
![](https://ids.lib.harvard.edu/ids/iiif/18791052/932,520,60,11/full/0/native.jpg)
and detergent added
![](https://ids.lib.harvard.edu/ids/iiif/18791052/317,357,6,4/full/0/native.jpg)
E
![](https://ids.lib.harvard.edu/ids/iiif/18791052/310,357,13,4/full/0/native.jpg)
E .
![](https://ids.lib.harvard.edu/ids/iiif/18791052/310,357,5,4/full/0/native.jpg)
.
![](https://ids.lib.harvard.edu/ids/iiif/18791052/162,265,17,16/full/0/native.jpg)
AIR
![](https://ids.lib.harvard.edu/ids/iiif/18791052/941,513,18,11/full/0/native.jpg)
Wish
![](https://ids.lib.harvard.edu/ids/iiif/18791052/313,329,23,8/full/0/native.jpg)
REFAIRS
![](https://ids.lib.harvard.edu/ids/iiif/18791052/935,493,59,25/full/0/native.jpg)
Chief
![](https://ids.lib.harvard.edu/ids/iiif/18791052/402,278,20,5/full/0/native.jpg)
MARINE
![](https://ids.lib.harvard.edu/ids/iiif/18791052/402,275,91,8/full/0/native.jpg)
MARINE - HAI amount AND SAIN
![](https://ids.lib.harvard.edu/ids/iiif/18791052/972,524,20,6/full/0/native.jpg)
added
![](https://ids.lib.harvard.edu/ids/iiif/18791052/918,364,27,8/full/0/native.jpg)
OZOR
![](https://ids.lib.harvard.edu/ids/iiif/18791052/978,422,14,5/full/0/native.jpg)
W
![](https://ids.lib.harvard.edu/ids/iiif/18791052/693,403,19,5/full/0/native.jpg)
Texacc
![](https://ids.lib.harvard.edu/ids/iiif/18791052/969,427,25,9/full/0/native.jpg)
address
![](https://ids.lib.harvard.edu/ids/iiif/18791052/918,386,27,8/full/0/native.jpg)
...
![](https://ids.lib.harvard.edu/ids/iiif/18791052/775,269,5,6/full/0/native.jpg)
5
![](https://ids.lib.harvard.edu/ids/iiif/18791052/482,275,12,6/full/0/native.jpg)
SAIN
![](https://ids.lib.harvard.edu/ids/iiif/18791052/273,286,11,8/full/0/native.jpg)
Solar
![](https://ids.lib.harvard.edu/ids/iiif/18791052/273,284,29,10/full/0/native.jpg)
Solar Appete
![](https://ids.lib.harvard.edu/ids/iiif/18791052/283,284,19,9/full/0/native.jpg)
Appete
![](https://ids.lib.harvard.edu/ids/iiif/18791052/435,278,9,4/full/0/native.jpg)
HAI
![](https://ids.lib.harvard.edu/ids/iiif/18791052/405,305,15,5/full/0/native.jpg)
MUTCA
![](https://ids.lib.harvard.edu/ids/iiif/18791052/446,276,21,5/full/0/native.jpg)
amount
![](https://ids.lib.harvard.edu/ids/iiif/18791052/172,301,19,8/full/0/native.jpg)
ever
![](https://ids.lib.harvard.edu/ids/iiif/18791052/716,202,109,38/full/0/native.jpg)
XA
![](https://ids.lib.harvard.edu/ids/iiif/18791052/834,198,35,36/full/0/native.jpg)
CO
![](https://ids.lib.harvard.edu/ids/iiif/18791052/786,269,35,12/full/0/native.jpg)
SUPER
![](https://ids.lib.harvard.edu/ids/iiif/18791052/282,283,28,17/full/0/native.jpg)
Ayes
![](https://ids.lib.harvard.edu/ids/iiif/18791052/501,293,24,14/full/0/native.jpg)
ION
![](https://ids.lib.harvard.edu/ids/iiif/18791052/301,309,38,14/full/0/native.jpg)
AMERICAN
![](https://ids.lib.harvard.edu/ids/iiif/18791052/301,331,17,12/full/0/native.jpg)
CAR
![](https://ids.lib.harvard.edu/ids/iiif/18791052/315,329,26,14/full/0/native.jpg)
REFARS
![](https://ids.lib.harvard.edu/ids/iiif/18791052/297,348,46,17/full/0/native.jpg)
DASTER
![](https://ids.lib.harvard.edu/ids/iiif/18791052/346,346,37,16/full/0/native.jpg)
I!
![](https://ids.lib.harvard.edu/ids/iiif/18791052/975,399,22,16/full/0/native.jpg)
CH
![](https://ids.lib.harvard.edu/ids/iiif/18791052/700,440,57,16/full/0/native.jpg)
UNLEADED
![](https://ids.lib.harvard.edu/ids/iiif/18791052/935,523,13,10/full/0/native.jpg)
wnd
![](https://ids.lib.harvard.edu/ids/iiif/18791052/944,532,47,17/full/0/native.jpg)
protective
![](https://ids.lib.harvard.edu/ids/iiif/18791052/589,380,33,8/full/0/native.jpg)
|
![](https://ids.lib.harvard.edu/ids/iiif/18791052/281,198,718,363/full/0/native.jpg)
tergent
^TE XA CO
649
SUPER SERVICE
581-9353
Ayes AUTOS
REPAIRS
OP
ION
AMERICAN
FOREIGN
CAR REFARS
DASTER I!
UNLEADI
CH
UNLEADED
PREMIUM
Wih.oroterto
wnd detergentadd
protective
and
|三
![](https://ids.lib.harvard.edu/ids/iiif/18791052/963,543,36,18/full/0/native.jpg)
tergent
![](https://ids.lib.harvard.edu/ids/iiif/18791052/633,209,72,37/full/0/native.jpg)
^TE
![](https://ids.lib.harvard.edu/ids/iiif/18791052/704,252,67,60/full/0/native.jpg)
649
![](https://ids.lib.harvard.edu/ids/iiif/18791052/827,266,46,15/full/0/native.jpg)
SERVICE
![](https://ids.lib.harvard.edu/ids/iiif/18791052/786,274,68,21/full/0/native.jpg)
581-9353
![](https://ids.lib.harvard.edu/ids/iiif/18791052/310,284,50,18/full/0/native.jpg)
AUTOS
![](https://ids.lib.harvard.edu/ids/iiif/18791052/306,293,50,13/full/0/native.jpg)
REPAIRS
![](https://ids.lib.harvard.edu/ids/iiif/18791052/541,285,25,17/full/0/native.jpg)
OP
![](https://ids.lib.harvard.edu/ids/iiif/18791052/304,320,32,14/full/0/native.jpg)
FOREIGN
![](https://ids.lib.harvard.edu/ids/iiif/18791052/727,397,52,17/full/0/native.jpg)
UNLEADI
![](https://ids.lib.harvard.edu/ids/iiif/18791052/931,462,68,18/full/0/native.jpg)
PREMIUM
![](https://ids.lib.harvard.edu/ids/iiif/18791052/945,515,50,13/full/0/native.jpg)
Wih.oroterto
![](https://ids.lib.harvard.edu/ids/iiif/18791052/946,522,53,14/full/0/native.jpg)
detergentadd
![](https://ids.lib.harvard.edu/ids/iiif/18791052/933,541,21,15/full/0/native.jpg)
and
![](https://ids.lib.harvard.edu/ids/iiif/18791052/589,401,33,27/full/0/native.jpg)
三