Machine Generated Data
Tags
Amazon
created on 2019-06-06
Advertisement | 98.1 | |
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Person | 96.4 | |
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Human | 96.4 | |
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Person | 95.3 | |
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Interior Design | 89.3 | |
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Indoors | 89.3 | |
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Paper | 88.6 | |
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Brochure | 88.6 | |
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Flyer | 88.6 | |
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Building | 83.9 | |
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Collage | 83.5 | |
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Outdoors | 69.1 | |
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Text | 67.8 | |
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Vehicle | 65.5 | |
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Transportation | 65.5 | |
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Airplane | 65.5 | |
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Aircraft | 65.5 | |
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Urban | 64.9 | |
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Nature | 64.3 | |
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Poster | 56 | |
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Office Building | 55.8 | |
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Tower | 55.8 | |
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Architecture | 55.8 | |
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Billboard | 55.6 | |
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Clarifai
created on 2019-06-06
illustration | 97.8 | |
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people | 97.6 | |
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architecture | 95.2 | |
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no person | 95.1 | |
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94.7 | ||
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city | 93.7 | |
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art | 92.4 | |
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man | 91.6 | |
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group | 90.8 | |
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business | 90.7 | |
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picture frame | 90.1 | |
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bill | 89.6 | |
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layout | 89.4 | |
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many | 88.1 | |
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monochrome | 87.5 | |
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adult | 87.2 | |
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building | 86.9 | |
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house | 85 | |
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card | 84.8 | |
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town | 84 | |
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Imagga
created on 2019-06-06
billboard | 55.8 | |
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signboard | 44.6 | |
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structure | 42.4 | |
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business | 22.5 | |
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building | 22.4 | |
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architecture | 21.9 | |
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money | 20.4 | |
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construction | 18 | |
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design | 16.3 | |
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finance | 16 | |
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city | 15.8 | |
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web site | 15.1 | |
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plan | 15.1 | |
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paper | 14.9 | |
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equipment | 14.9 | |
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urban | 14.8 | |
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drawing | 14.4 | |
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currency | 14.4 | |
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office | 14.3 | |
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bill | 14.3 | |
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technology | 14.1 | |
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financial | 13.4 | |
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modern | 13.3 | |
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sketch | 13.2 | |
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project | 12.5 | |
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sky | 12.1 | |
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bank | 12.1 | |
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dollar | 12.1 | |
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banking | 11.9 | |
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cash | 11.9 | |
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wire | 11.4 | |
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house | 10.9 | |
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3d | 10.8 | |
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tower | 10.7 | |
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architect | 10.6 | |
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engineering | 10.5 | |
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home | 10.4 | |
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window | 10.4 | |
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grunge | 10.2 | |
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dishwasher | 10.1 | |
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frame | 10 | |
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interior | 9.7 | |
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engineer | 9.6 | |
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chart | 9.6 | |
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hand | 9.1 | |
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designer | 8.7 | |
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architectural | 8.6 | |
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line | 8.6 | |
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skyline | 8.5 | |
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space | 8.5 | |
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power | 8.4 | |
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old | 8.4 | |
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device | 8.4 | |
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texture | 8.3 | |
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note | 8.3 | |
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vintage | 8.3 | |
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investment | 8.2 | |
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monitor | 8.2 | |
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square | 8.1 | |
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digital | 8.1 | |
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copy | 8 | |
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work | 7.8 | |
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empty | 7.7 | |
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industry | 7.7 | |
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apartment | 7.7 | |
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profit | 7.6 | |
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pencil | 7.6 | |
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bridge | 7.6 | |
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buy | 7.5 | |
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three dimensional | 7.5 | |
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evening | 7.5 | |
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electronic equipment | 7.5 | |
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savings | 7.5 | |
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floor | 7.4 | |
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retro | 7.4 | |
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street | 7.4 | |
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white goods | 7.3 | |
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computer | 7.3 | |
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dirty | 7.2 | |
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wealth | 7.2 | |
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night | 7.1 | |
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market | 7.1 | |
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Google
created on 2019-06-06
Photograph | 95.4 | |
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Text | 91.2 | |
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Snapshot | 83.6 | |
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Photographic paper | 80.2 | |
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Architecture | 76.3 | |
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Art | 74.8 | |
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Design | 72 | |
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Room | 71.4 | |
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Collection | 68.1 | |
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Adaptation | 67 | |
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Visual arts | 66.9 | |
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History | 64.5 | |
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Photography | 62.4 | |
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Paper | 61.1 | |
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Stock photography | 59.4 | |
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Illustration | 57.7 | |
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Urban design | 56.1 | |
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Paper product | 55.7 | |
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Interior design | 54.3 | |
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Parallel | 52.4 | |
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Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/43314859/315,265,10,16/full/0/native.jpg)
AWS Rekognition
Age | 14-23 |
Gender | Female, 50.4% |
Calm | 49.6% |
Happy | 49.5% |
Sad | 50.1% |
Angry | 49.6% |
Confused | 49.7% |
Disgusted | 49.5% |
Surprised | 49.5% |
Feature analysis
Categories
Imagga
paintings art | 43.2% | |
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text visuals | 30% | |
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streetview architecture | 25.8% | |
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Captions
Microsoft
created on 2019-06-06
a display in a store | 63.1% | |
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a store display case | 56.2% | |
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a portrait of a store | 56.1% | |
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Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/43314859/483,66,55,15/full/0/native.jpg)
Housing:
![](https://ids.lib.harvard.edu/ids/iiif/43314859/543,493,74,17/full/0/native.jpg)
LONDON
![](https://ids.lib.harvard.edu/ids/iiif/43314859/426,65,55,15/full/0/native.jpg)
Improved
![](https://ids.lib.harvard.edu/ids/iiif/43314859/426,64,165,15/full/0/native.jpg)
Improved Housing: London,
![](https://ids.lib.harvard.edu/ids/iiif/43314859/543,67,48,14/full/0/native.jpg)
London,
![](https://ids.lib.harvard.edu/ids/iiif/43314859/419,491,198,17/full/0/native.jpg)
CAMDEN YOWN LONDON
![](https://ids.lib.harvard.edu/ids/iiif/43314859/780,558,97,19/full/0/native.jpg)
-AVATORY-
![](https://ids.lib.harvard.edu/ids/iiif/43314859/419,493,106,15/full/0/native.jpg)
CAMDEN YOWN
![](https://ids.lib.harvard.edu/ids/iiif/43314859/142,295,62,16/full/0/native.jpg)
EADIN&
![](https://ids.lib.harvard.edu/ids/iiif/43314859/141,294,119,17/full/0/native.jpg)
EADIN& LOOM
![](https://ids.lib.harvard.edu/ids/iiif/43314859/214,562,15,13/full/0/native.jpg)
of
![](https://ids.lib.harvard.edu/ids/iiif/43314859/473,431,67,17/full/0/native.jpg)
SMOXIN&
![](https://ids.lib.harvard.edu/ids/iiif/43314859/170,560,40,16/full/0/native.jpg)
Vitw
![](https://ids.lib.harvard.edu/ids/iiif/43314859/208,293,53,17/full/0/native.jpg)
LOOM
![](https://ids.lib.harvard.edu/ids/iiif/43314859/747,293,61,16/full/0/native.jpg)
- DINING
![](https://ids.lib.harvard.edu/ids/iiif/43314859/423,473,94,19/full/0/native.jpg)
.POWHon
![](https://ids.lib.harvard.edu/ids/iiif/43314859/91,559,216,17/full/0/native.jpg)
.LAUNDRY - Vitw of WOEXHOUAL
![](https://ids.lib.harvard.edu/ids/iiif/43314859/747,293,126,16/full/0/native.jpg)
- DINING ROOM-
![](https://ids.lib.harvard.edu/ids/iiif/43314859/423,473,170,20/full/0/native.jpg)
.POWHon IOUSE
![](https://ids.lib.harvard.edu/ids/iiif/43314859/91,561,74,15/full/0/native.jpg)
.LAUNDRY -
![](https://ids.lib.harvard.edu/ids/iiif/43314859/817,293,56,16/full/0/native.jpg)
ROOM-
![](https://ids.lib.harvard.edu/ids/iiif/43314859/234,561,73,17/full/0/native.jpg)
WOEXHOUAL
![](https://ids.lib.harvard.edu/ids/iiif/43314859/523,476,70,18/full/0/native.jpg)
IOUSE
![](https://ids.lib.harvard.edu/ids/iiif/43314859/884,46,67,17/full/0/native.jpg)
HV2/7,
![](https://ids.lib.harvard.edu/ids/iiif/43314859/948,46,10,14/full/0/native.jpg)
3
![](https://ids.lib.harvard.edu/ids/iiif/43314859/432,70,51,15/full/0/native.jpg)
Improved
![](https://ids.lib.harvard.edu/ids/iiif/43314859/487,71,47,15/full/0/native.jpg)
Housing
![](https://ids.lib.harvard.edu/ids/iiif/43314859/480,434,53,17/full/0/native.jpg)
MOXIN
![](https://ids.lib.harvard.edu/ids/iiif/43314859/426,478,95,24/full/0/native.jpg)
ROWtON
![](https://ids.lib.harvard.edu/ids/iiif/43314859/525,477,69,25/full/0/native.jpg)
HOU$E
![](https://ids.lib.harvard.edu/ids/iiif/43314859/95,564,56,18/full/0/native.jpg)
LAUHDR
![](https://ids.lib.harvard.edu/ids/iiif/43314859/234,565,64,18/full/0/native.jpg)
WoRxHoUp
![](https://ids.lib.harvard.edu/ids/iiif/43314859/781,562,89,22/full/0/native.jpg)
-AVAYORY
![](https://ids.lib.harvard.edu/ids/iiif/43314859/95,46,863,538/full/0/native.jpg)
HV2/7, 3
Improved Housing
London,
DINING R0OM-
MOXIN
ROWtON HOU$E
CAMDEN TOWN ONDON
LAUHDR
Vitw of WoRxHoUp
-AVAYORY
![](https://ids.lib.harvard.edu/ids/iiif/43314859/548,71,44,16/full/0/native.jpg)
London,
![](https://ids.lib.harvard.edu/ids/iiif/43314859/761,297,50,17/full/0/native.jpg)
DINING
![](https://ids.lib.harvard.edu/ids/iiif/43314859/821,296,60,18/full/0/native.jpg)
R0OM-
![](https://ids.lib.harvard.edu/ids/iiif/43314859/422,495,64,20/full/0/native.jpg)
CAMDEN
![](https://ids.lib.harvard.edu/ids/iiif/43314859/486,496,38,20/full/0/native.jpg)
TOWN
![](https://ids.lib.harvard.edu/ids/iiif/43314859/532,495,82,22/full/0/native.jpg)
ONDON
![](https://ids.lib.harvard.edu/ids/iiif/43314859/176,564,36,17/full/0/native.jpg)
Vitw
![](https://ids.lib.harvard.edu/ids/iiif/43314859/217,567,14,14/full/0/native.jpg)
of