Machine Generated Data
Tags
Amazon
created on 2022-06-04
Water | 99.8 | |
| ||
Waterfront | 98.6 | |
| ||
Pier | 96.9 | |
| ||
Port | 96.9 | |
| ||
Dock | 96.9 | |
| ||
Outdoors | 74.1 | |
| ||
Harbor | 73.9 | |
| ||
Building | 62.6 | |
| ||
Nature | 61.5 | |
| ||
Watercraft | 59.3 | |
| ||
Transportation | 59.3 | |
| ||
Vehicle | 59.3 | |
| ||
Vessel | 59.3 | |
| ||
Construction | 58.7 | |
|
Imagga
created on 2022-06-04
structure | 45.6 | |
| ||
bridge | 38.4 | |
| ||
building | 28.3 | |
| ||
architecture | 26.2 | |
| ||
city | 24.9 | |
| ||
steel | 24 | |
| ||
urban | 23.6 | |
| ||
steel arch bridge | 23.1 | |
| ||
industrial | 21.8 | |
| ||
factory | 20.7 | |
| ||
industry | 20.5 | |
| ||
beam | 19 | |
| ||
billboard | 18.7 | |
| ||
river | 18.7 | |
| ||
machine | 18.2 | |
| ||
power | 16.8 | |
| ||
water | 16.7 | |
| ||
old | 15.3 | |
| ||
signboard | 15.3 | |
| ||
transportation | 15.2 | |
| ||
night | 15.1 | |
| ||
plant | 15 | |
| ||
travel | 14.8 | |
| ||
construction | 14.5 | |
| ||
tower | 14.3 | |
| ||
sky | 14 | |
| ||
modern | 13.3 | |
| ||
device | 13 | |
| ||
metal | 12.9 | |
| ||
pipe | 12.6 | |
| ||
pier | 12.1 | |
| ||
light | 12 | |
| ||
landmark | 11.7 | |
| ||
engineering | 11.4 | |
| ||
transport | 11 | |
| ||
road | 10.8 | |
| ||
skyline | 10.4 | |
| ||
famous | 10.2 | |
| ||
station | 9.9 | |
| ||
rail | 9.8 | |
| ||
business | 9.7 | |
| ||
support | 9.7 | |
| ||
pollution | 9.6 | |
| ||
equipment | 9.6 | |
| ||
concrete | 9.6 | |
| ||
wheel | 9.5 | |
| ||
car | 9.4 | |
| ||
iron | 9.3 | |
| ||
inside | 9.2 | |
| ||
landscape | 8.9 | |
| ||
railroad | 8.8 | |
| ||
train | 8.8 | |
| ||
railway | 8.8 | |
| ||
steam | 8.7 | |
| ||
heavy | 8.6 | |
| ||
design | 8.4 | |
| ||
energy | 8.4 | |
| ||
town | 8.3 | |
| ||
reflection | 8.1 | |
| ||
lines | 8.1 | |
| ||
interior | 8 | |
| ||
wall | 7.9 | |
| ||
cables | 7.8 | |
| ||
ancient | 7.8 | |
| ||
production | 7.8 | |
| ||
waste | 7.8 | |
| ||
district | 7.8 | |
| ||
port | 7.7 | |
| ||
traffic | 7.6 | |
| ||
electricity | 7.6 | |
| ||
window | 7.5 | |
| ||
street | 7.4 | |
| ||
warehouse | 7.4 | |
| ||
ship | 7.3 | |
| ||
new | 7.3 | |
| ||
freight car | 7.3 | |
| ||
turbine | 7.2 | |
| ||
center | 7.2 | |
|
Google
created on 2022-06-04
Black | 89.8 | |
| ||
Rectangle | 86.9 | |
| ||
Black-and-white | 84.2 | |
| ||
Naval architecture | 78.6 | |
| ||
Monochrome photography | 75.7 | |
| ||
Snapshot | 74.3 | |
| ||
Font | 74.1 | |
| ||
Monochrome | 74.1 | |
| ||
Urban design | 73.5 | |
| ||
Symmetry | 69.7 | |
| ||
Bridge | 69.6 | |
| ||
Metal | 68.5 | |
| ||
City | 68.4 | |
| ||
Electricity | 67.5 | |
| ||
Engineering | 67.1 | |
| ||
Factory | 66.4 | |
| ||
Stock photography | 64 | |
| ||
Machine | 63.9 | |
| ||
Steel | 63 | |
| ||
Room | 60.4 | |
|
Microsoft
created on 2022-06-04
text | 96.1 | |
| ||
black and white | 96 | |
| ||
ship | 73.5 | |
| ||
several | 18.1 | |
|
Color Analysis
Categories
Imagga
paintings art | 47.9% | |
| ||
streetview architecture | 40.4% | |
| ||
interior objects | 6.7% | |
| ||
text visuals | 4.1% | |
|
Captions
Microsoft
created on 2022-06-04
an old photo of a boat | 33.7% | |
| ||
a boat sitting on top of a building | 28.3% | |
| ||
a boat filled with logs | 27.9% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20488742/48,787,51,20/full/0/native.jpg)
Main
![](https://ids.lib.harvard.edu/ids/iiif/20488742/3,128,31,20/full/0/native.jpg)
ORGAN
![](https://ids.lib.harvard.edu/ids/iiif/20488742/56,139,16,15/full/0/native.jpg)
NTS
![](https://ids.lib.harvard.edu/ids/iiif/20488742/72,142,16,15/full/0/native.jpg)
ETC
![](https://ids.lib.harvard.edu/ids/iiif/20488742/2,128,88,29/full/0/native.jpg)
ORGAN NON NTS ETC
![](https://ids.lib.harvard.edu/ids/iiif/20488742/102,790,20,20/full/0/native.jpg)
St
![](https://ids.lib.harvard.edu/ids/iiif/20488742/48,783,136,28/full/0/native.jpg)
Main St Inclinic
![](https://ids.lib.harvard.edu/ids/iiif/20488742/891,781,70,24/full/0/native.jpg)
4376
![](https://ids.lib.harvard.edu/ids/iiif/20488742/31,134,17,16/full/0/native.jpg)
NON
![](https://ids.lib.harvard.edu/ids/iiif/20488742/597,790,110,24/full/0/native.jpg)
oct.26.09
![](https://ids.lib.harvard.edu/ids/iiif/20488742/125,783,58,27/full/0/native.jpg)
Inclinic
![](https://ids.lib.harvard.edu/ids/iiif/20488742/135,167,25,15/full/0/native.jpg)
ESTATION
![](https://ids.lib.harvard.edu/ids/iiif/20488742/264,186,16,9/full/0/native.jpg)
CALD
![](https://ids.lib.harvard.edu/ids/iiif/20488742/144,154,19,13/full/0/native.jpg)
BENGE
![](https://ids.lib.harvard.edu/ids/iiif/20488742/240,182,40,12/full/0/native.jpg)
CONSULTS CALD
![](https://ids.lib.harvard.edu/ids/iiif/20488742/134,146,34,28/full/0/native.jpg)
- BENGE
![](https://ids.lib.harvard.edu/ids/iiif/20488742/138,156,4,6/full/0/native.jpg)
-
![](https://ids.lib.harvard.edu/ids/iiif/20488742/241,183,26,10/full/0/native.jpg)
CONSULTS
![](https://ids.lib.harvard.edu/ids/iiif/20488742/6,128,957,692/full/0/native.jpg)
ORGAN NOW NTS ETC.
155064
Main St Incline
Oct 26.09
4376
![](https://ids.lib.harvard.edu/ids/iiif/20488742/6,128,32,23/full/0/native.jpg)
ORGAN
![](https://ids.lib.harvard.edu/ids/iiif/20488742/31,133,23,21/full/0/native.jpg)
NOW
![](https://ids.lib.harvard.edu/ids/iiif/20488742/72,142,22,21/full/0/native.jpg)
ETC.
![](https://ids.lib.harvard.edu/ids/iiif/20488742/135,168,28,17/full/0/native.jpg)
155064
![](https://ids.lib.harvard.edu/ids/iiif/20488742/49,788,54,25/full/0/native.jpg)
Main
![](https://ids.lib.harvard.edu/ids/iiif/20488742/102,789,28,23/full/0/native.jpg)
St
![](https://ids.lib.harvard.edu/ids/iiif/20488742/57,139,21,20/full/0/native.jpg)
NTS
![](https://ids.lib.harvard.edu/ids/iiif/20488742/125,789,65,25/full/0/native.jpg)
Incline
![](https://ids.lib.harvard.edu/ids/iiif/20488742/601,793,42,20/full/0/native.jpg)
Oct
![](https://ids.lib.harvard.edu/ids/iiif/20488742/654,794,55,20/full/0/native.jpg)
26.09
![](https://ids.lib.harvard.edu/ids/iiif/20488742/901,789,62,19/full/0/native.jpg)
4376