Machine Generated Data
Tags
Amazon
created on 2019-11-19
Clarifai
created on 2019-11-19
Imagga
created on 2019-11-19
groom | 40.9 | |
| ||
city | 33.3 | |
| ||
architecture | 30.9 | |
| ||
building | 24.6 | |
| ||
travel | 20.4 | |
| ||
urban | 19.2 | |
| ||
tourism | 19 | |
| ||
statue | 18.9 | |
| ||
structure | 18.2 | |
| ||
landmark | 18.1 | |
| ||
barrier | 17.2 | |
| ||
monument | 16.8 | |
| ||
tourist | 15.8 | |
| ||
historic | 15.6 | |
| ||
famous | 14.9 | |
| ||
step | 14.7 | |
| ||
bridge | 14.4 | |
| ||
history | 14.3 | |
| ||
old | 13.9 | |
| ||
dress | 13.6 | |
| ||
support | 13.1 | |
| ||
person | 13 | |
| ||
church | 12.9 | |
| ||
obstruction | 12.9 | |
| ||
people | 12.8 | |
| ||
man | 12.8 | |
| ||
sky | 12.8 | |
| ||
palace | 12.2 | |
| ||
culture | 11.1 | |
| ||
love | 11 | |
| ||
street | 11 | |
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traditional | 10.8 | |
| ||
light | 10.8 | |
| ||
religion | 10.8 | |
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sculpture | 10.7 | |
| ||
night | 10.7 | |
| ||
bride | 10.6 | |
| ||
cityscape | 10.4 | |
| ||
device | 10.1 | |
| ||
wedding | 10.1 | |
| ||
marble | 9.8 | |
| ||
stone | 9.5 | |
| ||
scene | 9.5 | |
| ||
ancient | 9.5 | |
| ||
historical | 9.4 | |
| ||
adult | 9.1 | |
| ||
park | 9.1 | |
| ||
shadow | 9 | |
| ||
tower | 9 | |
| ||
new | 8.9 | |
| ||
romantic | 8.9 | |
| ||
black | 8.7 | |
| ||
portrait | 8.4 | |
| ||
modern | 8.4 | |
| ||
design | 7.9 | |
| ||
art | 7.9 | |
| ||
house | 7.8 | |
| ||
column | 7.5 | |
| ||
religious | 7.5 | |
| ||
outdoors | 7.5 | |
| ||
town | 7.4 | |
| ||
vacation | 7.4 | |
| ||
business | 7.3 | |
| ||
male | 7.3 | |
| ||
river | 7.1 | |
| ||
happiness | 7.1 | |
|
Google
created on 2019-11-19
Photograph | 95.6 | |
| ||
Snapshot | 82.5 | |
| ||
Photography | 72.5 | |
| ||
Black-and-white | 68.3 | |
| ||
Stock photography | 64 | |
|
Microsoft
created on 2019-11-19
black and white | 95.5 | |
| ||
man | 93.5 | |
| ||
person | 93.1 | |
| ||
text | 91.1 | |
| ||
clothing | 88.2 | |
| ||
monochrome | 86.2 | |
| ||
street | 86 | |
|
Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/14240892/337,377,48,63/full/0/native.jpg)
AWS Rekognition
Age | 36-54 |
Gender | Male, 54.5% |
Sad | 50.6% |
Confused | 45.1% |
Fear | 45.1% |
Angry | 45.1% |
Disgusted | 45% |
Surprised | 45.1% |
Calm | 48.9% |
Happy | 45.1% |
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/14240892/217,341,250,641/full/0/native.jpg)
Person | 98.9% | |
|
Categories
Imagga
events parties | 96.9% | |
| ||
streetview architecture | 1.6% | |
| ||
people portraits | 1% | |
|
Captions
Microsoft
created on 2019-11-19
a black and white photo of a man | 68.3% | |
| ||
a man standing in a room | 68.2% | |
| ||
a man standing in front of a building | 67.7% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/14240892/18,496,83,20/full/0/native.jpg)
STORES
![](https://ids.lib.harvard.edu/ids/iiif/14240892/25,474,66,22/full/0/native.jpg)
LOFTS
![](https://ids.lib.harvard.edu/ids/iiif/14240892/50,456,50,18/full/0/native.jpg)
Buildings
![](https://ids.lib.harvard.edu/ids/iiif/14240892/16,455,84,18/full/0/native.jpg)
Bliss Buildings
![](https://ids.lib.harvard.edu/ids/iiif/14240892/16,457,33,14/full/0/native.jpg)
Bliss
![](https://ids.lib.harvard.edu/ids/iiif/14240892/14,552,86,19/full/0/native.jpg)
BASTINECO
![](https://ids.lib.harvard.edu/ids/iiif/14240892/58,540,33,9/full/0/native.jpg)
STEAM
![](https://ids.lib.harvard.edu/ids/iiif/14240892/68,522,42,9/full/0/native.jpg)
CAACITY
![](https://ids.lib.harvard.edu/ids/iiif/14240892/32,537,61,11/full/0/native.jpg)
LVE STEAM
![](https://ids.lib.harvard.edu/ids/iiif/14240892/91,572,21,9/full/0/native.jpg)
2820
![](https://ids.lib.harvard.edu/ids/iiif/14240892/32,538,26,11/full/0/native.jpg)
LVE
![](https://ids.lib.harvard.edu/ids/iiif/14240892/10,456,193,213/full/0/native.jpg)
Bliss Buildings
LOFTS
STORES
HEAVY PLOOR CARACITY
GT SERVICE
BASTINE&CO
2 .19ST AL4-7520
AGENT
wwww
![](https://ids.lib.harvard.edu/ids/iiif/14240892/17,457,38,23/full/0/native.jpg)
Bliss
![](https://ids.lib.harvard.edu/ids/iiif/14240892/52,456,50,24/full/0/native.jpg)
Buildings
![](https://ids.lib.harvard.edu/ids/iiif/14240892/31,477,64,25/full/0/native.jpg)
LOFTS
![](https://ids.lib.harvard.edu/ids/iiif/14240892/21,497,86,28/full/0/native.jpg)
STORES
![](https://ids.lib.harvard.edu/ids/iiif/14240892/13,525,31,15/full/0/native.jpg)
HEAVY
![](https://ids.lib.harvard.edu/ids/iiif/14240892/42,524,32,15/full/0/native.jpg)
PLOOR
![](https://ids.lib.harvard.edu/ids/iiif/14240892/71,523,43,16/full/0/native.jpg)
CARACITY
![](https://ids.lib.harvard.edu/ids/iiif/14240892/28,532,33,14/full/0/native.jpg)
GT
![](https://ids.lib.harvard.edu/ids/iiif/14240892/59,532,39,15/full/0/native.jpg)
SERVICE
![](https://ids.lib.harvard.edu/ids/iiif/14240892/10,553,108,28/full/0/native.jpg)
BASTINE&CO
![](https://ids.lib.harvard.edu/ids/iiif/14240892/12,575,19,15/full/0/native.jpg)
2
![](https://ids.lib.harvard.edu/ids/iiif/14240892/29,574,36,15/full/0/native.jpg)
.19ST
![](https://ids.lib.harvard.edu/ids/iiif/14240892/63,574,55,14/full/0/native.jpg)
AL4-7520
![](https://ids.lib.harvard.edu/ids/iiif/14240892/33,586,27,14/full/0/native.jpg)
AGENT
![](https://ids.lib.harvard.edu/ids/iiif/14240892/162,656,41,13/full/0/native.jpg)
wwww