Machine Generated Data
Tags
Amazon
created on 2023-10-24
Clarifai
created on 2018-10-06
Imagga
created on 2018-10-06
man | 24.2 | |
| ||
people | 24 | |
| ||
person | 20.3 | |
| ||
magazine | 18.7 | |
| ||
creation | 18.5 | |
| ||
product | 18.1 | |
| ||
male | 17.7 | |
| ||
old | 15.3 | |
| ||
vintage | 14.1 | |
| ||
business | 14 | |
| ||
adult | 13.6 | |
| ||
postmark | 12.8 | |
| ||
sky | 12.7 | |
| ||
stamp | 12.6 | |
| ||
12.4 | ||
| ||
sport | 12.4 | |
| ||
portrait | 12.3 | |
| ||
letter | 11.9 | |
| ||
envelope | 11.8 | |
| ||
snow | 11.7 | |
| ||
businessman | 11.5 | |
| ||
fashion | 11.3 | |
| ||
ancient | 11.2 | |
| ||
jacket | 11.2 | |
| ||
fun | 11.2 | |
| ||
philately | 10.9 | |
| ||
lifestyle | 10.8 | |
| ||
outdoor | 10.7 | |
| ||
retro | 10.6 | |
| ||
book jacket | 10.4 | |
| ||
office | 10.4 | |
| ||
cold | 10.3 | |
| ||
art | 10.2 | |
| ||
cute | 10 | |
| ||
happy | 10 | |
| ||
circa | 9.9 | |
| ||
postage | 9.8 | |
| ||
postal | 9.8 | |
| ||
human | 9.7 | |
| ||
summer | 9.6 | |
| ||
love | 9.5 | |
| ||
work | 9.4 | |
| ||
winter | 9.4 | |
| ||
ice | 9.3 | |
| ||
attractive | 9.1 | |
| ||
aged | 9 | |
| ||
active | 9 | |
| ||
team | 9 | |
| ||
outdoors | 9 | |
| ||
clothing | 8.8 | |
| ||
drawing | 8.7 | |
| ||
happiness | 8.6 | |
| ||
professional | 8.6 | |
| ||
travel | 8.4 | |
| ||
dress | 8.1 | |
| ||
hair | 7.9 | |
| ||
address | 7.8 | |
| ||
black | 7.8 | |
| ||
face | 7.8 | |
| ||
beach | 7.8 | |
| ||
card | 7.7 | |
| ||
men | 7.7 | |
| ||
casual | 7.6 | |
| ||
leisure | 7.5 | |
| ||
manager | 7.4 | |
| ||
daily | 7.3 | |
| ||
message | 7.3 | |
| ||
suit | 7.2 | |
| ||
smile | 7.1 | |
| ||
job | 7.1 | |
| ||
architecture | 7 | |
|
Google
created on 2018-10-06
black and white | 89.6 | |
| ||
monochrome | 63.2 | |
| ||
monochrome photography | 62.9 | |
|
Microsoft
created on 2018-10-06
text | 94.7 | |
|
Color Analysis
Feature analysis
Categories
Imagga
paintings art | 99.9% | |
|
Captions
Microsoft
created on 2018-10-06
a man standing in front of a building | 32.7% | |
| ||
an old photo of a man | 32.6% | |
| ||
old photo of a man | 32.5% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/38979049/947,4425,50,84/full/0/native.jpg)
33
![](https://ids.lib.harvard.edu/ids/iiif/38979049/941,1253,50,87/full/0/native.jpg)
36
![](https://ids.lib.harvard.edu/ids/iiif/38979049/943,2286,50,87/full/0/native.jpg)
35
![](https://ids.lib.harvard.edu/ids/iiif/38979049/25,144,38,108/full/0/native.jpg)
TRI
![](https://ids.lib.harvard.edu/ids/iiif/38979049/943,3357,50,89/full/0/native.jpg)
34
![](https://ids.lib.harvard.edu/ids/iiif/38979049/36,4776,42,127/full/0/native.jpg)
PAN
![](https://ids.lib.harvard.edu/ids/iiif/38979049/23,299,44,216/full/0/native.jpg)
KODAK
![](https://ids.lib.harvard.edu/ids/iiif/38979049/40,5237,42,129/full/0/native.jpg)
DAK
![](https://ids.lib.harvard.edu/ids/iiif/38979049/31,2345,40,167/full/0/native.jpg)
FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979049/29,2345,44,514/full/0/native.jpg)
SAFETY FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979049/939,682,50,144/full/0/native.jpg)
36A
![](https://ids.lib.harvard.edu/ids/iiif/38979049/949,4918,50,133/full/0/native.jpg)
32A
![](https://ids.lib.harvard.edu/ids/iiif/38979049/29,2602,44,257/full/0/native.jpg)
SAFETY
![](https://ids.lib.harvard.edu/ids/iiif/38979049/30,4567,52,799/full/0/native.jpg)
DAK TRI x PAN FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979049/23,46,44,469/full/0/native.jpg)
KODAK TRI x
![](https://ids.lib.harvard.edu/ids/iiif/38979049/939,1746,50,133/full/0/native.jpg)
35A
![](https://ids.lib.harvard.edu/ids/iiif/38979049/38,4986,38,33/full/0/native.jpg)
x
![](https://ids.lib.harvard.edu/ids/iiif/38979049/943,2794,50,142/full/0/native.jpg)
34A
![](https://ids.lib.harvard.edu/ids/iiif/38979049/938,3874,54,137/full/0/native.jpg)
ЗЗА
![](https://ids.lib.harvard.edu/ids/iiif/38979049/24,47,988,5322/full/0/native.jpg)
DAK TRIX PAN FILM
KODAK SAFETY FILM
KODA K TRIX
→ 32A
→ 33
-33A
→ 34
→34 A
→35
→35A
-36A
-36
![](https://ids.lib.harvard.edu/ids/iiif/38979049/40,5240,41,127/full/0/native.jpg)
DAK
![](https://ids.lib.harvard.edu/ids/iiif/38979049/38,4986,38,204/full/0/native.jpg)
TRIX
![](https://ids.lib.harvard.edu/ids/iiif/38979049/38,4777,38,127/full/0/native.jpg)
PAN
![](https://ids.lib.harvard.edu/ids/iiif/38979049/33,4569,43,165/full/0/native.jpg)
FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979049/33,2967,43,199/full/0/native.jpg)
KODAK
![](https://ids.lib.harvard.edu/ids/iiif/38979049/33,2621,43,306/full/0/native.jpg)
SAFETY
![](https://ids.lib.harvard.edu/ids/iiif/38979049/24,351,41,161/full/0/native.jpg)
KODA
![](https://ids.lib.harvard.edu/ids/iiif/38979049/27,301,38,36/full/0/native.jpg)
K
![](https://ids.lib.harvard.edu/ids/iiif/38979049/942,5056,59,106/full/0/native.jpg)
→
![](https://ids.lib.harvard.edu/ids/iiif/38979049/942,4913,68,138/full/0/native.jpg)
32A
![](https://ids.lib.harvard.edu/ids/iiif/38979049/946,4424,52,82/full/0/native.jpg)
33
![](https://ids.lib.harvard.edu/ids/iiif/38979049/937,3880,66,245/full/0/native.jpg)
-33A
![](https://ids.lib.harvard.edu/ids/iiif/38979049/942,3355,54,88/full/0/native.jpg)
34
![](https://ids.lib.harvard.edu/ids/iiif/38979049/944,2793,45,43/full/0/native.jpg)
A
![](https://ids.lib.harvard.edu/ids/iiif/38979049/940,2283,61,91/full/0/native.jpg)
35
![](https://ids.lib.harvard.edu/ids/iiif/38979049/937,1746,57,134/full/0/native.jpg)
35A
![](https://ids.lib.harvard.edu/ids/iiif/38979049/928,695,70,270/full/0/native.jpg)
-36A
![](https://ids.lib.harvard.edu/ids/iiif/38979049/944,1268,50,188/full/0/native.jpg)
-36