Machine Generated Data
Tags
Amazon
created on 2023-10-06
Path | 100 | |
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Sidewalk | 100 | |
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City | 100 | |
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Road | 100 | |
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Street | 100 | |
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Urban | 100 | |
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Walking | 99.9 | |
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Neighborhood | 99.7 | |
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Person | 98.2 | |
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Person | 97.2 | |
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Person | 96.2 | |
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Person | 94.2 | |
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Person | 89.4 | |
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Person | 84 | |
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Shop | 81.3 | |
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Architecture | 80.3 | |
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Building | 80.3 | |
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Car | 76.7 | |
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Transportation | 76.7 | |
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Vehicle | 76.7 | |
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Walkway | 61.7 | |
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Face | 59 | |
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Head | 59 | |
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Metropolis | 57.9 | |
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Clothing | 57 | |
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Coat | 57 | |
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Alley | 57 | |
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Outdoors | 56.8 | |
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Indoors | 56.7 | |
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Restaurant | 56.7 | |
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Pedestrian | 56.1 | |
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Deli | 55.3 | |
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Downtown | 55.2 | |
|
Clarifai
created on 2018-05-11
Imagga
created on 2023-10-06
shop | 52.9 | |
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mercantile establishment | 41.3 | |
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building | 41.2 | |
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architecture | 37.8 | |
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city | 35.8 | |
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street | 29.5 | |
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old | 27.9 | |
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place of business | 27.3 | |
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house | 25.6 | |
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town | 25.1 | |
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urban | 22.7 | |
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shoe shop | 21.9 | |
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historic | 19.3 | |
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stone | 19.2 | |
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ancient | 19 | |
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bakery | 18.3 | |
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window | 18.1 | |
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wall | 17.2 | |
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travel | 16.2 | |
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door | 15.6 | |
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road | 15.4 | |
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history | 15.2 | |
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brick | 15.1 | |
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structure | 14.2 | |
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home | 13.6 | |
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lamp | 13.4 | |
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establishment | 13.3 | |
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houses | 12.6 | |
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sky | 12.1 | |
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sidewalk | 11.7 | |
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snow | 11.6 | |
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light | 11.4 | |
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historical | 11.3 | |
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construction | 11.1 | |
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exterior | 11.1 | |
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barbershop | 11 | |
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village | 10.9 | |
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tourism | 10.7 | |
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wooden | 10.6 | |
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garage | 10.2 | |
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church | 10.2 | |
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entrance | 9.7 | |
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residential | 9.6 | |
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antique | 9.5 | |
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palace | 9.5 | |
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tourist | 9.5 | |
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buildings | 9.5 | |
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arch | 8.8 | |
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scene | 8.7 | |
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warehouse | 8.6 | |
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wood | 8.3 | |
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aged | 8.2 | |
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transportation | 8.1 | |
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religion | 8.1 | |
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plaza | 7.9 | |
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park | 7.8 | |
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empty | 7.7 | |
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windows | 7.7 | |
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medieval | 7.7 | |
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winter | 7.7 | |
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england | 7.6 | |
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sign | 7.5 | |
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row | 7.5 | |
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vintage | 7.4 | |
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tobacco shop | 7.4 | |
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design | 7.3 | |
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gate | 7.3 | |
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transport | 7.3 | |
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office | 7.3 | |
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restaurant | 7.2 | |
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glass | 7 | |
|
Google
created on 2018-05-11
town | 90.5 | |
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black and white | 89.4 | |
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infrastructure | 88.7 | |
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street | 88.5 | |
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snapshot | 81.8 | |
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neighbourhood | 78.2 | |
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monochrome photography | 78 | |
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road | 76.9 | |
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downtown | 74.8 | |
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history | 70.4 | |
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facade | 64.4 | |
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monochrome | 64.1 | |
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car | 55.5 | |
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city | 55.3 | |
|
Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/43157963/515,394,16,22/full/0/native.jpg)
AWS Rekognition
Age | 26-36 |
Gender | Male, 99.6% |
Confused | 95.1% |
Surprised | 6.5% |
Fear | 6.1% |
Sad | 2.3% |
Calm | 1.7% |
Angry | 1% |
Happy | 0.5% |
Disgusted | 0.2% |
![](https://ids.lib.harvard.edu/ids/iiif/43157963/483,440,14,15/full/0/native.jpg)
AWS Rekognition
Age | 20-28 |
Gender | Male, 97% |
Happy | 45.8% |
Sad | 36.7% |
Calm | 15.3% |
Surprised | 7.6% |
Confused | 7.3% |
Fear | 6.5% |
Disgusted | 2.5% |
Angry | 1.9% |
Feature analysis
Categories
Imagga
streetview architecture | 100% | |
|
Captions
Microsoft
created on 2018-05-11
a black sign with white letters | 92% | |
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a black sign with white letters above a storefront on a building | 91.9% | |
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a black sign with white letters above a storefront | 91.8% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/43157963/565,139,199,52/full/0/native.jpg)
DRUGS
![](https://ids.lib.harvard.edu/ids/iiif/43157963/954,387,31,18/full/0/native.jpg)
PAGE
![](https://ids.lib.harvard.edu/ids/iiif/43157963/963,430,21,18/full/0/native.jpg)
13
![](https://ids.lib.harvard.edu/ids/iiif/43157963/737,332,57,13/full/0/native.jpg)
HARDWARE
![](https://ids.lib.harvard.edu/ids/iiif/43157963/955,402,30,14/full/0/native.jpg)
SHOWS
![](https://ids.lib.harvard.edu/ids/iiif/43157963/443,323,63,25/full/0/native.jpg)
HER
![](https://ids.lib.harvard.edu/ids/iiif/43157963/580,354,35,11/full/0/native.jpg)
DENTIST
![](https://ids.lib.harvard.edu/ids/iiif/43157963/776,346,16,10/full/0/native.jpg)
NET
![](https://ids.lib.harvard.edu/ids/iiif/43157963/568,288,45,13/full/0/native.jpg)
PHYSICIAN
![](https://ids.lib.harvard.edu/ids/iiif/43157963/507,77,298,62/full/0/native.jpg)
GALLAHER'S
![](https://ids.lib.harvard.edu/ids/iiif/43157963/752,346,21,10/full/0/native.jpg)
HAIR
![](https://ids.lib.harvard.edu/ids/iiif/43157963/194,379,9,7/full/0/native.jpg)
19
![](https://ids.lib.harvard.edu/ids/iiif/43157963/956,425,13,6/full/0/native.jpg)
WITH
![](https://ids.lib.harvard.edu/ids/iiif/43157963/206,532,19,9/full/0/native.jpg)
2-29
![](https://ids.lib.harvard.edu/ids/iiif/43157963/746,346,46,10/full/0/native.jpg)
- HAIR NET
![](https://ids.lib.harvard.edu/ids/iiif/43157963/242,0,139,108/full/0/native.jpg)
TORE
![](https://ids.lib.harvard.edu/ids/iiif/43157963/395,197,149,101/full/0/native.jpg)
CALIAHER
![](https://ids.lib.harvard.edu/ids/iiif/43157963/664,363,53,16/full/0/native.jpg)
ACCEPTANCE
![](https://ids.lib.harvard.edu/ids/iiif/43157963/955,422,28,10/full/0/native.jpg)
WITH كفر
![](https://ids.lib.harvard.edu/ids/iiif/43157963/793,369,24,8/full/0/native.jpg)
NOS
![](https://ids.lib.harvard.edu/ids/iiif/43157963/751,326,27,5/full/0/native.jpg)
NUNTER
![](https://ids.lib.harvard.edu/ids/iiif/43157963/746,346,7,4/full/0/native.jpg)
-
![](https://ids.lib.harvard.edu/ids/iiif/43157963/580,340,35,13/full/0/native.jpg)
EQUILLY
![](https://ids.lib.harvard.edu/ids/iiif/43157963/776,365,41,14/full/0/native.jpg)
POST NOS
![](https://ids.lib.harvard.edu/ids/iiif/43157963/766,355,45,11/full/0/native.jpg)
I
![](https://ids.lib.harvard.edu/ids/iiif/43157963/954,414,30,13/full/0/native.jpg)
CIRCLEYL
![](https://ids.lib.harvard.edu/ids/iiif/43157963/569,279,45,12/full/0/native.jpg)
VOKERMEN2
![](https://ids.lib.harvard.edu/ids/iiif/43157963/778,371,14,6/full/0/native.jpg)
POST
![](https://ids.lib.harvard.edu/ids/iiif/43157963/971,422,12,8/full/0/native.jpg)
كفر
![](https://ids.lib.harvard.edu/ids/iiif/43157963/195,79,792,466/full/0/native.jpg)
CALLAHERS
DRUGS
PHYSICIAN
HER
HARDWARE
MAIR N
DENTIST
19
13
2-29
![](https://ids.lib.harvard.edu/ids/iiif/43157963/533,79,276,70/full/0/native.jpg)
CALLAHERS
![](https://ids.lib.harvard.edu/ids/iiif/43157963/539,133,224,85/full/0/native.jpg)
DRUGS
![](https://ids.lib.harvard.edu/ids/iiif/43157963/571,290,46,15/full/0/native.jpg)
PHYSICIAN
![](https://ids.lib.harvard.edu/ids/iiif/43157963/444,325,67,27/full/0/native.jpg)
HER
![](https://ids.lib.harvard.edu/ids/iiif/43157963/739,333,58,15/full/0/native.jpg)
HARDWARE
![](https://ids.lib.harvard.edu/ids/iiif/43157963/755,350,22,9/full/0/native.jpg)
MAIR
![](https://ids.lib.harvard.edu/ids/iiif/43157963/777,350,9,10/full/0/native.jpg)
N
![](https://ids.lib.harvard.edu/ids/iiif/43157963/583,357,36,11/full/0/native.jpg)
DENTIST
![](https://ids.lib.harvard.edu/ids/iiif/43157963/195,379,9,12/full/0/native.jpg)
19
![](https://ids.lib.harvard.edu/ids/iiif/43157963/966,431,21,20/full/0/native.jpg)
13
![](https://ids.lib.harvard.edu/ids/iiif/43157963/207,533,23,12/full/0/native.jpg)
2-29