Machine Generated Data
Tags
Amazon
created on 2022-01-22
Human | 98.3 | |
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Person | 98.3 | |
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Path | 95.8 | |
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Person | 95.4 | |
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Person | 93.8 | |
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Person | 93.2 | |
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Plant | 92 | |
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Grass | 92 | |
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Person | 91.9 | |
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Tarmac | 89.6 | |
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Asphalt | 89.6 | |
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Person | 88.8 | |
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Nature | 88.3 | |
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Outdoors | 87.1 | |
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Person | 86.6 | |
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Person | 85.2 | |
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Person | 84.6 | |
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Road | 84.5 | |
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Person | 83.2 | |
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Vegetation | 82.3 | |
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Shorts | 77.4 | |
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Clothing | 77.4 | |
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Apparel | 77.4 | |
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Sidewalk | 74.7 | |
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Pavement | 74.7 | |
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Tree | 70.7 | |
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Land | 69.1 | |
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Woodland | 69.1 | |
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Forest | 69.1 | |
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Pedestrian | 68.2 | |
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Person | 68 | |
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Person | 66.9 | |
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Yard | 64.1 | |
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Building | 63.8 | |
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Urban | 63.8 | |
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Street | 63.8 | |
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City | 63.8 | |
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Town | 63.8 | |
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Park | 59.8 | |
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Lawn | 59.8 | |
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Person | 57.4 | |
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Clarifai
created on 2023-10-26
people | 99.9 | |
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group together | 99.2 | |
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many | 98.9 | |
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group | 98.8 | |
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street | 98.4 | |
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monochrome | 97.7 | |
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adult | 96.6 | |
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man | 94.4 | |
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vehicle | 93.5 | |
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war | 93.2 | |
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crowd | 92.7 | |
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transportation system | 90.2 | |
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no person | 88.3 | |
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military | 87.2 | |
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black and white | 86.7 | |
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home | 86.1 | |
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soldier | 85.9 | |
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child | 85 | |
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road | 84.2 | |
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woman | 83.6 | |
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Imagga
created on 2022-01-22
patio | 79.6 | |
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area | 59.3 | |
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structure | 50.6 | |
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snow | 27.7 | |
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shopping cart | 25.8 | |
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handcart | 20.1 | |
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building | 20 | |
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architecture | 18.1 | |
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landscape | 16.4 | |
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wheeled vehicle | 15.8 | |
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travel | 15.5 | |
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sky | 15.3 | |
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outdoor | 15.3 | |
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chair | 15.2 | |
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summer | 14.8 | |
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trees | 14.2 | |
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winter | 13.6 | |
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house | 13.4 | |
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park | 13.2 | |
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sun | 12.9 | |
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construction | 12.8 | |
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water | 12.7 | |
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city | 12.5 | |
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vacation | 12.3 | |
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seat | 12.2 | |
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holiday | 12.2 | |
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day | 11 | |
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tree | 10.8 | |
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tourism | 10.7 | |
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container | 10.3 | |
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weather | 10.1 | |
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wood | 10 | |
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outdoors | 9.8 | |
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old | 9.8 | |
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urban | 9.6 | |
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home | 9.6 | |
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scene | 9.5 | |
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street | 9.2 | |
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sand | 9.2 | |
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fountain | 9.1 | |
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beach | 9.1 | |
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night | 8.9 | |
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sunny | 8.6 | |
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sea | 8.6 | |
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relaxation | 8.4 | |
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new | 8.1 | |
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grass | 7.9 | |
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umbrella | 7.8 | |
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cold | 7.7 | |
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resort | 7.7 | |
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modern | 7.7 | |
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industry | 7.7 | |
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residential | 7.7 | |
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path | 7.6 | |
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brick | 7.5 | |
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leisure | 7.5 | |
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exterior | 7.4 | |
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furniture | 7.3 | |
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transport | 7.3 | |
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tourist | 7.3 | |
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road | 7.2 | |
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black | 7.2 | |
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transportation | 7.2 | |
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history | 7.2 | |
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work | 7.2 | |
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blackboard | 7.1 | |
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table | 7 | |
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scenic | 7 | |
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glass | 7 | |
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Google
created on 2022-01-22
Black-and-white | 85.5 | |
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Plant | 85.1 | |
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Tree | 85 | |
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Rectangle | 82.9 | |
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Adaptation | 79.3 | |
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Tints and shades | 77.4 | |
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Monochrome photography | 75.6 | |
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Monochrome | 75.3 | |
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Font | 73.4 | |
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Landscape | 69.7 | |
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Room | 66.5 | |
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Road | 65.8 | |
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Motor vehicle | 63.7 | |
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Photographic paper | 62.1 | |
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Art | 61.4 | |
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History | 61.3 | |
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Street | 61.2 | |
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Visual arts | 59.8 | |
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Square | 57.3 | |
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Paper product | 56.8 | |
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Microsoft
created on 2022-01-22
outdoor | 99.5 | |
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text | 97.5 | |
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tree | 84 | |
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black and white | 80.8 | |
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old | 42.6 | |
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Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18824451/583,387,11,14/full/0/native.jpg)
AWS Rekognition
Age | 18-26 |
Gender | Female, 78.6% |
Happy | 29.5% |
Fear | 26.5% |
Sad | 20.9% |
Calm | 11.4% |
Confused | 4.4% |
Surprised | 3.3% |
Angry | 2.7% |
Disgusted | 1.3% |
![](https://ids.lib.harvard.edu/ids/iiif/18824451/512,408,9,12/full/0/native.jpg)
AWS Rekognition
Age | 22-30 |
Gender | Male, 99.1% |
Sad | 72.4% |
Calm | 11.1% |
Angry | 8.1% |
Happy | 2.1% |
Confused | 2.1% |
Fear | 1.8% |
Surprised | 1.5% |
Disgusted | 0.8% |
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18824451/561,390,52,144/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18824451/523,374,34,125/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18824451/868,321,15,46/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18824451/212,401,47,183/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18824451/835,328,15,47/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18824451/845,313,19,59/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18824451/621,357,20,66/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18824451/465,425,30,104/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18824451/491,409,47,135/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18824451/733,334,21,66/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18824451/708,347,19,65/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18824451/814,323,17,58/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18824451/679,346,21,71/full/0/native.jpg)
Person | 98.3% | |
|
Categories
Imagga
nature landscape | 89.9% | |
| ||
streetview architecture | 6.7% | |
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beaches seaside | 1.1% | |
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Captions
Microsoft
created on 2022-01-22
an old photo of a street | 90.6% | |
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an old photo of a city street | 88.6% | |
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old photo of a street | 86.6% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18824451/568,345,29,12/full/0/native.jpg)
OUR
![](https://ids.lib.harvard.edu/ids/iiif/18824451/731,294,20,8/full/0/native.jpg)
MAY
![](https://ids.lib.harvard.edu/ids/iiif/18824451/731,294,44,8/full/0/native.jpg)
MAY THE
![](https://ids.lib.harvard.edu/ids/iiif/18824451/393,405,104,21/full/0/native.jpg)
DEMOCRACY
![](https://ids.lib.harvard.edu/ids/iiif/18824451/556,355,51,13/full/0/native.jpg)
IDEALS
![](https://ids.lib.harvard.edu/ids/iiif/18824451/756,294,19,8/full/0/native.jpg)
THE
![](https://ids.lib.harvard.edu/ids/iiif/18824451/204,368,20,20/full/0/native.jpg)
13
![](https://ids.lib.harvard.edu/ids/iiif/18824451/726,316,29,5/full/0/native.jpg)
ELECTION
![](https://ids.lib.harvard.edu/ids/iiif/18824451/212,360,7,8/full/0/native.jpg)
S
![](https://ids.lib.harvard.edu/ids/iiif/18824451/399,367,94,23/full/0/native.jpg)
AMERICA
![](https://ids.lib.harvard.edu/ids/iiif/18824451/682,323,15,6/full/0/native.jpg)
LTY
![](https://ids.lib.harvard.edu/ids/iiif/18824451/197,344,35,12/full/0/native.jpg)
BRADE
![](https://ids.lib.harvard.edu/ids/iiif/18824451/663,323,33,7/full/0/native.jpg)
LOVE LTY
![](https://ids.lib.harvard.edu/ids/iiif/18824451/603,317,37,10/full/0/native.jpg)
COUPANS
![](https://ids.lib.harvard.edu/ids/iiif/18824451/663,325,17,5/full/0/native.jpg)
LOVE
![](https://ids.lib.harvard.edu/ids/iiif/18824451/989,442,18,169/full/0/native.jpg)
KODAKSVELA
![](https://ids.lib.harvard.edu/ids/iiif/18824451/732,305,23,7/full/0/native.jpg)
TOSMAN
![](https://ids.lib.harvard.edu/ids/iiif/18824451/697,333,34,7/full/0/native.jpg)
HARRETT
![](https://ids.lib.harvard.edu/ids/iiif/18824451/199,346,812,266/full/0/native.jpg)
OUR
IDEALS
BRADE
AMERICA
DEMOCRACY
YT37A8 MAGO
![](https://ids.lib.harvard.edu/ids/iiif/18824451/571,347,30,15/full/0/native.jpg)
OUR
![](https://ids.lib.harvard.edu/ids/iiif/18824451/565,357,46,16/full/0/native.jpg)
IDEALS
![](https://ids.lib.harvard.edu/ids/iiif/18824451/199,346,37,15/full/0/native.jpg)
BRADE
![](https://ids.lib.harvard.edu/ids/iiif/18824451/395,368,106,27/full/0/native.jpg)
AMERICA
![](https://ids.lib.harvard.edu/ids/iiif/18824451/392,406,110,25/full/0/native.jpg)
DEMOCRACY
![](https://ids.lib.harvard.edu/ids/iiif/18824451/989,444,23,86/full/0/native.jpg)
YT37A8
![](https://ids.lib.harvard.edu/ids/iiif/18824451/990,558,21,54/full/0/native.jpg)
MAGO