Machine Generated Data
Tags
Amazon
created on 2023-10-25
Art | 100 | |
| ||
Collage | 100 | |
| ||
Chart | 100 | |
| ||
Plot | 100 | |
| ||
Diagram | 100 | |
| ||
Plan | 100 | |
| ||
Water | 94.2 | |
| ||
Waterfront | 94.2 | |
| ||
Aircraft | 90.3 | |
| ||
Airplane | 90.3 | |
| ||
Transportation | 90.3 | |
| ||
Vehicle | 90.3 | |
| ||
Airplane | 76.2 | |
| ||
Yacht | 74.9 | |
| ||
Outdoors | 71.5 | |
| ||
Nature | 69.1 | |
| ||
Sea | 69.1 | |
| ||
Coast | 63.2 | |
| ||
Shoreline | 63.2 | |
| ||
Airplane | 58.5 | |
| ||
Airplane | 57.8 | |
| ||
Astronomy | 56.7 | |
| ||
Outer Space | 56.7 | |
| ||
Land | 55.5 | |
|
Clarifai
created on 2018-10-06
monochrome | 97.3 | |
| ||
collage | 96.6 | |
| ||
people | 94.9 | |
| ||
no person | 94.6 | |
| ||
medicine | 93.5 | |
| ||
water | 92.5 | |
| ||
illustration | 92 | |
| ||
window | 92 | |
| ||
dirty | 90.8 | |
| ||
picture frame | 90.3 | |
| ||
exposed | 89.2 | |
| ||
nature | 88.2 | |
| ||
sea | 87.6 | |
| ||
negative | 86.4 | |
| ||
man | 86.4 | |
| ||
science | 86.3 | |
| ||
medical | 85.9 | |
| ||
vertical | 85.9 | |
| ||
watercraft | 85.5 | |
| ||
retro | 83.8 | |
|
Imagga
created on 2018-10-06
Google
created on 2018-10-06
photograph | 95.4 | |
| ||
black and white | 93.4 | |
| ||
text | 88.4 | |
| ||
monochrome photography | 81 | |
| ||
photography | 80.7 | |
| ||
structure | 79 | |
| ||
monochrome | 68.4 | |
| ||
font | 56.9 | |
| ||
stock photography | 55.2 | |
| ||
angle | 54.9 | |
|
Color Analysis
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/38979157/283,108,104,38/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/38979157/238,70,88,54/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/38979157/181,65,143,46/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/38979157/319,80,82,28/full/0/native.jpg)
Airplane | 90.3% | |
|
Categories
Imagga
text visuals | 53.3% | |
| ||
interior objects | 36% | |
| ||
paintings art | 3.1% | |
| ||
nature landscape | 2.2% | |
| ||
food drinks | 2.1% | |
| ||
pets animals | 1.4% | |
| ||
streetview architecture | 1% | |
| ||
cars vehicles | 0.3% | |
| ||
beaches seaside | 0.2% | |
| ||
events parties | 0.2% | |
| ||
people portraits | 0.2% | |
|
Captions
Microsoft
created on 2018-10-06
a flat screen television | 56.7% | |
| ||
a flat screen tv | 56.6% | |
| ||
a screen shot of a video game | 32.2% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/38979157/116,184,11,8/full/0/native.jpg)
13
![](https://ids.lib.harvard.edu/ids/iiif/38979157/518,183,11,8/full/0/native.jpg)
15
![](https://ids.lib.harvard.edu/ids/iiif/38979157/321,183,12,8/full/0/native.jpg)
14
![](https://ids.lib.harvard.edu/ids/iiif/38979157/748,8,31,7/full/0/native.jpg)
FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979157/715,183,12,8/full/0/native.jpg)
16
![](https://ids.lib.harvard.edu/ids/iiif/38979157/631,8,38,9/full/0/native.jpg)
KODAK
![](https://ids.lib.harvard.edu/ids/iiif/38979157/917,184,13,7/full/0/native.jpg)
17
![](https://ids.lib.harvard.edu/ids/iiif/38979157/305,8,26,8/full/0/native.jpg)
PAN
![](https://ids.lib.harvard.edu/ids/iiif/38979157/194,8,84,8/full/0/native.jpg)
KODAKPLUS
![](https://ids.lib.harvard.edu/ids/iiif/38979157/809,183,21,8/full/0/native.jpg)
16A
![](https://ids.lib.harvard.edu/ids/iiif/38979157/610,182,20,8/full/0/native.jpg)
15A
![](https://ids.lib.harvard.edu/ids/iiif/38979157/194,8,175,9/full/0/native.jpg)
KODAKPLUS x PAN FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979157/686,8,45,8/full/0/native.jpg)
SAFETY
![](https://ids.lib.harvard.edu/ids/iiif/38979157/414,183,21,8/full/0/native.jpg)
14A
![](https://ids.lib.harvard.edu/ids/iiif/38979157/288,9,6,7/full/0/native.jpg)
x
![](https://ids.lib.harvard.edu/ids/iiif/38979157/210,183,22,8/full/0/native.jpg)
13A
![](https://ids.lib.harvard.edu/ids/iiif/38979157/3,183,27,11/full/0/native.jpg)
+12A
![](https://ids.lib.harvard.edu/ids/iiif/38979157/4,9,930,188/full/0/native.jpg)
KODAK SAFETY FILM
KODAK PLUS X PAN FILM
317
-> 16A
-> 15
→15A
-> 16
14 A
→ 14
-13
13A
012A
![](https://ids.lib.harvard.edu/ids/iiif/38979157/632,9,38,12/full/0/native.jpg)
KODAK
![](https://ids.lib.harvard.edu/ids/iiif/38979157/673,9,60,12/full/0/native.jpg)
SAFETY
![](https://ids.lib.harvard.edu/ids/iiif/38979157/738,9,44,12/full/0/native.jpg)
FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979157/245,9,36,11/full/0/native.jpg)
PLUS
![](https://ids.lib.harvard.edu/ids/iiif/38979157/289,9,10,11/full/0/native.jpg)
X
![](https://ids.lib.harvard.edu/ids/iiif/38979157/305,9,28,12/full/0/native.jpg)
PAN
![](https://ids.lib.harvard.edu/ids/iiif/38979157/907,183,27,12/full/0/native.jpg)
317
![](https://ids.lib.harvard.edu/ids/iiif/38979157/788,185,12,7/full/0/native.jpg)
-
![](https://ids.lib.harvard.edu/ids/iiif/38979157/796,183,15,13/full/0/native.jpg)
>
![](https://ids.lib.harvard.edu/ids/iiif/38979157/809,182,24,13/full/0/native.jpg)
16A
![](https://ids.lib.harvard.edu/ids/iiif/38979157/518,183,16,13/full/0/native.jpg)
15
![](https://ids.lib.harvard.edu/ids/iiif/38979157/591,183,22,13/full/0/native.jpg)
→
![](https://ids.lib.harvard.edu/ids/iiif/38979157/610,182,24,13/full/0/native.jpg)
15A
![](https://ids.lib.harvard.edu/ids/iiif/38979157/715,183,15,12/full/0/native.jpg)
16
![](https://ids.lib.harvard.edu/ids/iiif/38979157/415,183,16,12/full/0/native.jpg)
14
![](https://ids.lib.harvard.edu/ids/iiif/38979157/427,183,13,13/full/0/native.jpg)
A
![](https://ids.lib.harvard.edu/ids/iiif/38979157/95,182,34,15/full/0/native.jpg)
-13
![](https://ids.lib.harvard.edu/ids/iiif/38979157/200,183,33,14/full/0/native.jpg)
13A
![](https://ids.lib.harvard.edu/ids/iiif/38979157/4,184,30,13/full/0/native.jpg)
012A