Machine Generated Data
Tags
Amazon
created on 2022-01-15
Clarifai
created on 2023-10-26
Imagga
created on 2022-01-15
Google
created on 2022-01-15
Black | 89.7 | |
| ||
Black-and-white | 82.5 | |
| ||
Chair | 80.3 | |
| ||
Comfort | 74.8 | |
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Monochrome photography | 73.4 | |
| ||
Monochrome | 73.4 | |
| ||
Room | 68.8 | |
| ||
Drawer | 68.2 | |
| ||
Cabinetry | 67.4 | |
| ||
Club chair | 66.4 | |
| ||
Classic | 65.1 | |
| ||
Table | 64.9 | |
| ||
Stock photography | 63.2 | |
| ||
Art | 61.9 | |
| ||
Sitting | 61.6 | |
| ||
Still life photography | 58.9 | |
| ||
Chest of drawers | 54.9 | |
| ||
Font | 54.5 | |
| ||
Cupboard | 53.7 | |
| ||
T-shirt | 51.9 | |
|
Microsoft
created on 2022-01-15
text | 99.9 | |
| ||
cat | 88 | |
| ||
furniture | 85.9 | |
| ||
black and white | 74 | |
|
Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18819705/318,235,67,62/full/0/native.jpg)
AWS Rekognition
Age | 38-46 |
Gender | Female, 98.8% |
Calm | 35.6% |
Happy | 34.6% |
Sad | 20.7% |
Angry | 2.5% |
Fear | 2.4% |
Surprised | 1.5% |
Confused | 1.4% |
Disgusted | 1.3% |
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18819705/193,280,342,487/full/0/native.jpg)
Cat | 87.9% | |
|
Categories
Imagga
paintings art | 96.9% | |
| ||
interior objects | 1.8% | |
|
Captions
Microsoft
created on 2022-01-15
a person sitting in a room | 47.8% | |
| ||
a person sitting in a room | 47.7% | |
| ||
a person sitting in a chair | 38.3% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18819705/684,583,73,43/full/0/native.jpg)
Better
![](https://ids.lib.harvard.edu/ids/iiif/18819705/698,602,92,64/full/0/native.jpg)
Homes
![](https://ids.lib.harvard.edu/ids/iiif/18819705/756,781,22,16/full/0/native.jpg)
Come
![](https://ids.lib.harvard.edu/ids/iiif/18819705/760,671,8,4/full/0/native.jpg)
/
![](https://ids.lib.harvard.edu/ids/iiif/18819705/680,627,14,13/full/0/native.jpg)
1
![](https://ids.lib.harvard.edu/ids/iiif/18819705/715,640,43,25/full/0/native.jpg)
-
![](https://ids.lib.harvard.edu/ids/iiif/18819705/755,775,30,32/full/0/native.jpg)
Come DO
![](https://ids.lib.harvard.edu/ids/iiif/18819705/701,652,19,16/full/0/native.jpg)
=
![](https://ids.lib.harvard.edu/ids/iiif/18819705/740,660,6,4/full/0/native.jpg)
F
![](https://ids.lib.harvard.edu/ids/iiif/18819705/759,660,12,10/full/0/native.jpg)
y
![](https://ids.lib.harvard.edu/ids/iiif/18819705/493,6,164,36/full/0/native.jpg)
57066.
![](https://ids.lib.harvard.edu/ids/iiif/18819705/741,640,13,8/full/0/native.jpg)
and
![](https://ids.lib.harvard.edu/ids/iiif/18819705/741,638,42,23/full/0/native.jpg)
and Garden
![](https://ids.lib.harvard.edu/ids/iiif/18819705/723,653,18,11/full/0/native.jpg)
I
![](https://ids.lib.harvard.edu/ids/iiif/18819705/774,789,11,11/full/0/native.jpg)
DO
![](https://ids.lib.harvard.edu/ids/iiif/18819705/675,631,48,37/full/0/native.jpg)
I II =
![](https://ids.lib.harvard.edu/ids/iiif/18819705/753,643,30,17/full/0/native.jpg)
Garden
![](https://ids.lib.harvard.edu/ids/iiif/18819705/377,16,121,17/full/0/native.jpg)
M 117--YT33
![](https://ids.lib.harvard.edu/ids/iiif/18819705/692,639,10,12/full/0/native.jpg)
II
![](https://ids.lib.harvard.edu/ids/iiif/18819705/380,16,416,647/full/0/native.jpg)
M --YT
Better
Homes
![](https://ids.lib.harvard.edu/ids/iiif/18819705/380,20,16,14/full/0/native.jpg)
M
![](https://ids.lib.harvard.edu/ids/iiif/18819705/421,16,54,21/full/0/native.jpg)
--YT
![](https://ids.lib.harvard.edu/ids/iiif/18819705/670,578,91,55/full/0/native.jpg)
Better
![](https://ids.lib.harvard.edu/ids/iiif/18819705/702,611,94,51/full/0/native.jpg)
Homes