Machine Generated Data
Tags
Amazon
created on 2022-01-15
Cable | 89.1 | |
| ||
Urban | 86.4 | |
| ||
Power Lines | 85.3 | |
| ||
Road | 84.6 | |
| ||
Electric Transmission Tower | 82.8 | |
| ||
Building | 82 | |
| ||
City | 75.7 | |
| ||
Town | 75.7 | |
| ||
Transportation | 74.8 | |
| ||
Vehicle | 74.8 | |
| ||
Automobile | 74.8 | |
| ||
Car | 74.8 | |
| ||
Street | 71.8 | |
| ||
Metropolis | 65.5 | |
| ||
Person | 61.4 | |
| ||
Human | 61.4 | |
| ||
Neighborhood | 57.9 | |
|
Clarifai
created on 2023-10-26
industry | 98.9 | |
| ||
monochrome | 98.7 | |
| ||
building | 97.6 | |
| ||
expression | 97.1 | |
| ||
grinder | 96.7 | |
| ||
machine | 94.3 | |
| ||
urban | 93 | |
| ||
architecture | 92.7 | |
| ||
business | 92.5 | |
| ||
vehicle | 91.9 | |
| ||
street | 91.6 | |
| ||
transportation system | 90.1 | |
| ||
city | 89.5 | |
| ||
machinery | 89.4 | |
| ||
black and white | 89.3 | |
| ||
people | 88.2 | |
| ||
work | 87.2 | |
| ||
technology | 87.1 | |
| ||
construction | 86.9 | |
| ||
no person | 86 | |
|
Imagga
created on 2022-01-15
Google
created on 2022-01-15
Black-and-white | 85.6 | |
| ||
Style | 83.9 | |
| ||
Urban design | 82.3 | |
| ||
Line | 81.8 | |
| ||
Art | 81.8 | |
| ||
Rectangle | 79.8 | |
| ||
Adaptation | 79.3 | |
| ||
Font | 79 | |
| ||
Painting | 77.6 | |
| ||
Building | 75 | |
| ||
Monochrome | 74.9 | |
| ||
Monochrome photography | 74.9 | |
| ||
Symmetry | 70.1 | |
| ||
Drawing | 69.4 | |
| ||
Illustration | 69 | |
| ||
Visual arts | 68.1 | |
| ||
City | 68 | |
| ||
Road | 67 | |
| ||
Electricity | 67 | |
| ||
Facade | 65.1 | |
|
Microsoft
created on 2022-01-15
text | 99.7 | |
| ||
outdoor | 85.6 | |
| ||
building | 82.9 | |
| ||
black and white | 81.5 | |
| ||
drawing | 73.3 | |
| ||
skyscraper | 51.1 | |
|
Color Analysis
Feature analysis
Categories
Imagga
paintings art | 99.4% | |
|
Captions
Microsoft
created on 2022-01-15
an old photo of a building | 77.2% | |
| ||
an old photo of a large building | 72% | |
| ||
an old photo of a city | 71.9% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18817784/62,779,61,19/full/0/native.jpg)
Main
![](https://ids.lib.harvard.edu/ids/iiif/18817784/913,771,59,21/full/0/native.jpg)
4630
![](https://ids.lib.harvard.edu/ids/iiif/18817784/623,771,57,32/full/0/native.jpg)
May
![](https://ids.lib.harvard.edu/ids/iiif/18817784/62,779,228,19/full/0/native.jpg)
Main view
![](https://ids.lib.harvard.edu/ids/iiif/18817784/971,229,42,25/full/0/native.jpg)
Reming
![](https://ids.lib.harvard.edu/ids/iiif/18817784/240,783,50,12/full/0/native.jpg)
view
![](https://ids.lib.harvard.edu/ids/iiif/18817784/623,767,113,36/full/0/native.jpg)
May 4.10
![](https://ids.lib.harvard.edu/ids/iiif/18817784/685,767,50,30/full/0/native.jpg)
4.10
![](https://ids.lib.harvard.edu/ids/iiif/18817784/967,214,11,7/full/0/native.jpg)
the
![](https://ids.lib.harvard.edu/ids/iiif/18817784/946,213,33,14/full/0/native.jpg)
Bastely the
![](https://ids.lib.harvard.edu/ids/iiif/18817784/942,313,25,8/full/0/native.jpg)
MITCHCOOK
![](https://ids.lib.harvard.edu/ids/iiif/18817784/946,215,19,12/full/0/native.jpg)
Bastely
![](https://ids.lib.harvard.edu/ids/iiif/18817784/944,272,13,7/full/0/native.jpg)
MAX
![](https://ids.lib.harvard.edu/ids/iiif/18817784/943,235,18,9/full/0/native.jpg)
DAILY
![](https://ids.lib.harvard.edu/ids/iiif/18817784/944,258,15,11/full/0/native.jpg)
any
![](https://ids.lib.harvard.edu/ids/iiif/18817784/81,766,895,39/full/0/native.jpg)
*4630
Moin St.Prorrese view C
![](https://ids.lib.harvard.edu/ids/iiif/18817784/903,766,73,32/full/0/native.jpg)
*4630
![](https://ids.lib.harvard.edu/ids/iiif/18817784/81,777,47,25/full/0/native.jpg)
Moin
![](https://ids.lib.harvard.edu/ids/iiif/18817784/132,778,114,26/full/0/native.jpg)
St.Prorrese
![](https://ids.lib.harvard.edu/ids/iiif/18817784/243,785,58,20/full/0/native.jpg)
view
![](https://ids.lib.harvard.edu/ids/iiif/18817784/304,783,18,22/full/0/native.jpg)
C