Machine Generated Data
Tags
Amazon
created on 2023-10-25
Clarifai
created on 2018-10-06
Imagga
created on 2018-10-06
Google
created on 2018-10-06
photograph | 95 | |
| ||
black and white | 90.5 | |
| ||
text | 87.5 | |
| ||
photography | 78.7 | |
| ||
monochrome photography | 66.5 | |
| ||
monochrome | 66.1 | |
| ||
font | 61.3 | |
| ||
angle | 55.1 | |
| ||
stock photography | 50.8 | |
|
Microsoft
created on 2018-10-06
electronics | 81.5 | |
| ||
display | 80.9 | |
|
Color Analysis
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/38979108/123,83,27,35/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/38979108/87,88,19,33/full/0/native.jpg)
Person | 93.2% | |
|
Categories
Imagga
pets animals | 49.4% | |
| ||
text visuals | 23.1% | |
| ||
paintings art | 20.4% | |
| ||
nature landscape | 2.8% | |
| ||
streetview architecture | 2.3% | |
| ||
food drinks | 0.5% | |
| ||
interior objects | 0.5% | |
| ||
beaches seaside | 0.4% | |
| ||
people portraits | 0.3% | |
| ||
cars vehicles | 0.3% | |
| ||
macro flowers | 0.1% | |
|
Captions
Microsoft
created on 2018-10-06
a screen shot of a person | 39.7% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/38979108/542,11,38,8/full/0/native.jpg)
KODAK
![](https://ids.lib.harvard.edu/ids/iiif/38979108/136,183,7,8/full/0/native.jpg)
2
![](https://ids.lib.harvard.edu/ids/iiif/38979108/645,12,24,8/full/0/native.jpg)
PAN
![](https://ids.lib.harvard.edu/ids/iiif/38979108/589,11,30,8/full/0/native.jpg)
PLUS
![](https://ids.lib.harvard.edu/ids/iiif/38979108/677,12,31,8/full/0/native.jpg)
FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979108/232,183,18,8/full/0/native.jpg)
2A
![](https://ids.lib.harvard.edu/ids/iiif/38979108/825,183,15,7/full/0/native.jpg)
5A
![](https://ids.lib.harvard.edu/ids/iiif/38979108/932,184,6,7/full/0/native.jpg)
6
![](https://ids.lib.harvard.edu/ids/iiif/38979108/533,184,6,7/full/0/native.jpg)
4
![](https://ids.lib.harvard.edu/ids/iiif/38979108/626,185,16,7/full/0/native.jpg)
4A
![](https://ids.lib.harvard.edu/ids/iiif/38979108/433,183,16,9/full/0/native.jpg)
ЗА
![](https://ids.lib.harvard.edu/ids/iiif/38979108/338,185,7,8/full/0/native.jpg)
3
![](https://ids.lib.harvard.edu/ids/iiif/38979108/729,185,7,8/full/0/native.jpg)
5
![](https://ids.lib.harvard.edu/ids/iiif/38979108/542,11,166,10/full/0/native.jpg)
KODAK PLUS x PAN FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979108/99,9,46,8/full/0/native.jpg)
SAFETY
![](https://ids.lib.harvard.edu/ids/iiif/38979108/34,183,12,8/full/0/native.jpg)
1A
![](https://ids.lib.harvard.edu/ids/iiif/38979108/630,13,6,6/full/0/native.jpg)
x
![](https://ids.lib.harvard.edu/ids/iiif/38979108/976,12,38,8/full/0/native.jpg)
KODA
![](https://ids.lib.harvard.edu/ids/iiif/38979108/13,9,997,187/full/0/native.jpg)
KODAK SAFETYFILM
KODAK PLUS XPAN FILM
KODA
-→ 1A
2
-→ 2 A
![](https://ids.lib.harvard.edu/ids/iiif/38979108/46,9,38,13/full/0/native.jpg)
KODAK
![](https://ids.lib.harvard.edu/ids/iiif/38979108/87,9,111,14/full/0/native.jpg)
SAFETYFILM
![](https://ids.lib.harvard.edu/ids/iiif/38979108/589,12,34,11/full/0/native.jpg)
PLUS
![](https://ids.lib.harvard.edu/ids/iiif/38979108/630,13,42,10/full/0/native.jpg)
XPAN
![](https://ids.lib.harvard.edu/ids/iiif/38979108/677,13,35,11/full/0/native.jpg)
FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979108/977,13,33,13/full/0/native.jpg)
KODA
![](https://ids.lib.harvard.edu/ids/iiif/38979108/13,186,9,6/full/0/native.jpg)
-
![](https://ids.lib.harvard.edu/ids/iiif/38979108/18,183,18,12/full/0/native.jpg)
→
![](https://ids.lib.harvard.edu/ids/iiif/38979108/35,183,15,12/full/0/native.jpg)
1A
![](https://ids.lib.harvard.edu/ids/iiif/38979108/137,184,10,12/full/0/native.jpg)
2
![](https://ids.lib.harvard.edu/ids/iiif/38979108/243,183,12,12/full/0/native.jpg)
A