Machine Generated Data
Tags
Amazon
created on 2019-11-19
Home Decor | 99.7 | |
| ||
Person | 94.1 | |
| ||
Human | 94.1 | |
| ||
Window | 72.3 | |
| ||
Person | 70.2 | |
| ||
Curtain | 57.4 | |
| ||
Shutter | 57.4 | |
| ||
Transportation | 56.9 | |
| ||
Vehicle | 56.9 | |
|
Clarifai
created on 2019-11-19
people | 99.8 | |
| ||
adult | 98.5 | |
| ||
group together | 97.8 | |
| ||
vehicle | 97.5 | |
| ||
monochrome | 96.4 | |
| ||
man | 95.6 | |
| ||
group | 95.3 | |
| ||
administration | 95 | |
| ||
many | 94.8 | |
| ||
transportation system | 93.3 | |
| ||
street | 93.3 | |
| ||
war | 92.2 | |
| ||
one | 91.5 | |
| ||
police | 90.2 | |
| ||
two | 89.6 | |
| ||
aircraft | 89.3 | |
| ||
no person | 89 | |
| ||
military | 88 | |
| ||
outdoors | 86.6 | |
| ||
several | 86.2 | |
|
Imagga
created on 2019-11-19
building | 40.6 | |
| ||
architecture | 34 | |
| ||
structure | 30.7 | |
| ||
city | 24.9 | |
| ||
old | 23 | |
| ||
urban | 20.1 | |
| ||
wheeled vehicle | 19 | |
| ||
business | 18.8 | |
| ||
wall | 16.6 | |
| ||
facade | 16.4 | |
| ||
office | 15.2 | |
| ||
construction | 14.5 | |
| ||
window | 14.2 | |
| ||
house | 14.2 | |
| ||
travel | 14.1 | |
| ||
modern | 13.3 | |
| ||
glass | 12.4 | |
| ||
exterior | 12 | |
| ||
billboard | 11.5 | |
| ||
metal | 11.3 | |
| ||
sky | 10.8 | |
| ||
tree | 10.8 | |
| ||
mobile home | 10.2 | |
| ||
grunge | 10.2 | |
| ||
winter | 10.2 | |
| ||
town | 10.2 | |
| ||
light | 10 | |
| ||
dirty | 9.9 | |
| ||
vintage | 9.9 | |
| ||
vehicle | 9.9 | |
| ||
conveyance | 9.8 | |
| ||
steel | 9.7 | |
| ||
door | 9.7 | |
| ||
cold | 9.5 | |
| ||
industry | 9.4 | |
| ||
street | 9.2 | |
| ||
frame | 9.2 | |
| ||
shopping cart | 9.1 | |
| ||
industrial | 9.1 | |
| ||
housing | 9.1 | |
| ||
transportation | 9 | |
| ||
concrete | 8.6 | |
| ||
snow | 8.5 | |
| ||
design | 8.4 | |
| ||
tourism | 8.2 | |
| ||
trailer | 8.2 | |
| ||
tourist | 8.2 | |
| ||
landmark | 8.1 | |
| ||
interior | 8 | |
| ||
wooden | 7.9 | |
| ||
art | 7.8 | |
| ||
antique | 7.8 | |
| ||
ancient | 7.8 | |
| ||
warehouse | 7.8 | |
| ||
windows | 7.7 | |
| ||
obsolete | 7.7 | |
| ||
lamp | 7.6 | |
| ||
roof | 7.6 | |
| ||
drawing | 7.5 | |
| ||
brick | 7.5 | |
| ||
people | 7.2 | |
| ||
aged | 7.2 | |
| ||
road | 7.2 | |
| ||
black | 7.2 | |
| ||
home | 7.2 | |
| ||
room | 7.1 | |
| ||
trees | 7.1 | |
| ||
center | 7.1 | |
| ||
male | 7.1 | |
|
Google
created on 2019-11-19
Photograph | 95.3 | |
| ||
Snapshot | 84.9 | |
| ||
Architecture | 65.5 | |
| ||
Photography | 62.4 | |
| ||
Black-and-white | 56.4 | |
| ||
Building | 50.8 | |
|
Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/12890627/299,484,20,29/full/0/native.jpg)
AWS Rekognition
Age | 26-42 |
Gender | Male, 50.4% |
Surprised | 45.2% |
Angry | 46% |
Sad | 50.3% |
Fear | 45.1% |
Happy | 45.1% |
Confused | 46.5% |
Disgusted | 45.6% |
Calm | 46.3% |
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/12890627/262,468,82,232/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/12890627/557,357,66,174/full/0/native.jpg)
Person | 94.1% | |
|
Categories
Imagga
streetview architecture | 44.1% | |
| ||
interior objects | 42.5% | |
| ||
cars vehicles | 5.1% | |
| ||
beaches seaside | 3.9% | |
| ||
text visuals | 1.7% | |
| ||
paintings art | 1.1% | |
|
Captions
Microsoft
created on 2019-11-19
a black and white photo of a person | 81.6% | |
| ||
a black and white photo of a building | 81.5% | |
| ||
a black and white photo of a street | 79.1% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/12890627/9,403,85,20/full/0/native.jpg)
MESSAGERIES
![](https://ids.lib.harvard.edu/ids/iiif/12890627/7,382,145,45/full/0/native.jpg)
MESSAGERIES TRANSPORTS EXPEDITIONS
![](https://ids.lib.harvard.edu/ids/iiif/12890627/10,381,72,16/full/0/native.jpg)
TRANSPORTS
![](https://ids.lib.harvard.edu/ids/iiif/12890627/84,387,69,16/full/0/native.jpg)
EXPEDITIONS
![](https://ids.lib.harvard.edu/ids/iiif/12890627/961,263,51,38/full/0/native.jpg)
PE
![](https://ids.lib.harvard.edu/ids/iiif/12890627/95,407,59,18/full/0/native.jpg)
MIRABEAU
![](https://ids.lib.harvard.edu/ids/iiif/12890627/412,319,89,32/full/0/native.jpg)
La
![](https://ids.lib.harvard.edu/ids/iiif/12890627/409,313,449,41/full/0/native.jpg)
La eJungle
![](https://ids.lib.harvard.edu/ids/iiif/12890627/83,425,56,11/full/0/native.jpg)
VERSALLE
![](https://ids.lib.harvard.edu/ids/iiif/12890627/9,409,144,29/full/0/native.jpg)
16 VERSALLE MIRABEAU
![](https://ids.lib.harvard.edu/ids/iiif/12890627/549,303,311,39/full/0/native.jpg)
eJungle
![](https://ids.lib.harvard.edu/ids/iiif/12890627/10,421,19,10/full/0/native.jpg)
16
![](https://ids.lib.harvard.edu/ids/iiif/12890627/11,207,1010,243/full/0/native.jpg)
127
PE
Rt
"La Jungle
TRANSPORTS EXPEDITIONS
PARIS-PROVINGE
MESSAGERIES MIRABEAU
16. AVENUEVERSAILLES
WIS
![](https://ids.lib.harvard.edu/ids/iiif/12890627/582,207,25,22/full/0/native.jpg)
127
![](https://ids.lib.harvard.edu/ids/iiif/12890627/948,261,73,52/full/0/native.jpg)
PE
![](https://ids.lib.harvard.edu/ids/iiif/12890627/256,283,45,45/full/0/native.jpg)
Rt
![](https://ids.lib.harvard.edu/ids/iiif/12890627/378,307,137,62/full/0/native.jpg)
"La
![](https://ids.lib.harvard.edu/ids/iiif/12890627/577,289,296,67/full/0/native.jpg)
Jungle
![](https://ids.lib.harvard.edu/ids/iiif/12890627/16,387,69,18/full/0/native.jpg)
TRANSPORTS
![](https://ids.lib.harvard.edu/ids/iiif/12890627/87,391,72,18/full/0/native.jpg)
EXPEDITIONS
![](https://ids.lib.harvard.edu/ids/iiif/12890627/41,401,85,15/full/0/native.jpg)
PARIS-PROVINGE
![](https://ids.lib.harvard.edu/ids/iiif/12890627/11,406,87,25/full/0/native.jpg)
MESSAGERIES
![](https://ids.lib.harvard.edu/ids/iiif/12890627/98,411,60,22/full/0/native.jpg)
MIRABEAU
![](https://ids.lib.harvard.edu/ids/iiif/12890627/13,422,26,15/full/0/native.jpg)
16.
![](https://ids.lib.harvard.edu/ids/iiif/12890627/35,423,115,21/full/0/native.jpg)
AVENUEVERSAILLES
![](https://ids.lib.harvard.edu/ids/iiif/12890627/109,439,27,11/full/0/native.jpg)
WIS