Machine Generated Data
Tags
Amazon
created on 2022-06-18
White Board | 91.2 | |
| ||
Monitor | 67.1 | |
| ||
Electronics | 67.1 | |
| ||
Screen | 67.1 | |
| ||
Display | 67.1 | |
| ||
Text | 62.8 | |
| ||
Silver | 55.7 | |
|
Clarifai
created on 2023-10-29
Imagga
created on 2022-06-18
Google
created on 2022-06-18
Rectangle | 86.9 | |
| ||
Font | 81.9 | |
| ||
Monochrome photography | 69.8 | |
| ||
Circle | 67.1 | |
| ||
Monochrome | 65.5 | |
| ||
Event | 63.9 | |
| ||
Symmetry | 63.8 | |
| ||
Still life photography | 63.4 | |
| ||
Visual arts | 63.4 | |
| ||
Transparency | 62.3 | |
| ||
Fashion accessory | 60.2 | |
| ||
Pattern | 58.6 | |
| ||
Screenshot | 57.8 | |
| ||
Room | 57 | |
| ||
Metal | 56.2 | |
| ||
Display device | 54.9 | |
| ||
Art | 51.2 | |
|
Color Analysis
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20864227/0,0,760,1012/full/0/native.jpg)
Monitor | 67.1% | |
|
Categories
Imagga
paintings art | 98.9% | |
|
Captions
Microsoft
created on 2022-06-18
a flat screen tv sitting on top of a television | 40.1% | |
| ||
a flat screen television | 40% | |
| ||
a flat screen tv | 39.9% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20864227/694,327,29,56/full/0/native.jpg)
981
![](https://ids.lib.harvard.edu/ids/iiif/20864227/495,948,50,27/full/0/native.jpg)
140
![](https://ids.lib.harvard.edu/ids/iiif/20864227/694,239,28,44/full/0/native.jpg)
511
![](https://ids.lib.harvard.edu/ids/iiif/20864227/696,662,31,61/full/0/native.jpg)
195
![](https://ids.lib.harvard.edu/ids/iiif/20864227/52,951,32,23/full/0/native.jpg)
14!
![](https://ids.lib.harvard.edu/ids/iiif/20864227/696,567,31,156/full/0/native.jpg)
195 608
![](https://ids.lib.harvard.edu/ids/iiif/20864227/696,567,31,78/full/0/native.jpg)
608
![](https://ids.lib.harvard.edu/ids/iiif/20864227/495,940,214,36/full/0/native.jpg)
140 06-25-67
![](https://ids.lib.harvard.edu/ids/iiif/20864227/700,860,25,47/full/0/native.jpg)
٦/٦
![](https://ids.lib.harvard.edu/ids/iiif/20864227/274,948,61,23/full/0/native.jpg)
573
![](https://ids.lib.harvard.edu/ids/iiif/20864227/581,943,128,31/full/0/native.jpg)
06-25-67
![](https://ids.lib.harvard.edu/ids/iiif/20864227/486,20,75,15/full/0/native.jpg)
KACOX
![](https://ids.lib.harvard.edu/ids/iiif/20864227/272,18,180,20/full/0/native.jpg)
MJI7-YT37A*
![](https://ids.lib.harvard.edu/ids/iiif/20864227/277,20,451,953/full/0/native.jpg)
HACOX
2.VEELA-Lirw
119
$09 bi
7/1
↑
5.13
![](https://ids.lib.harvard.edu/ids/iiif/20864227/338,23,21,19/full/0/native.jpg)
-
![](https://ids.lib.harvard.edu/ids/iiif/20864227/701,568,27,24/full/0/native.jpg)
$
![](https://ids.lib.harvard.edu/ids/iiif/20864227/701,597,27,49/full/0/native.jpg)
09
![](https://ids.lib.harvard.edu/ids/iiif/20864227/702,692,27,34/full/0/native.jpg)
bi
![](https://ids.lib.harvard.edu/ids/iiif/20864227/700,858,26,59/full/0/native.jpg)
7/1
![](https://ids.lib.harvard.edu/ids/iiif/20864227/433,951,32,21/full/0/native.jpg)
↑
![](https://ids.lib.harvard.edu/ids/iiif/20864227/486,20,79,20/full/0/native.jpg)
HACOX
![](https://ids.lib.harvard.edu/ids/iiif/20864227/358,23,99,19/full/0/native.jpg)
2.VEELA
![](https://ids.lib.harvard.edu/ids/iiif/20864227/278,23,52,19/full/0/native.jpg)
Lirw
![](https://ids.lib.harvard.edu/ids/iiif/20864227/698,240,25,46/full/0/native.jpg)
119
![](https://ids.lib.harvard.edu/ids/iiif/20864227/279,950,63,23/full/0/native.jpg)
5.13