Machine Generated Data
Tags
Amazon
created on 2019-06-17
Clarifai
created on 2019-06-17
Imagga
created on 2019-06-17
landscape | 37.2 | |
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mountain | 35.5 | |
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sky | 30.7 | |
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rock | 26 | |
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tree | 25.9 | |
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travel | 25.3 | |
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water | 24 | |
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trees | 24 | |
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park | 23.9 | |
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vacation | 23.7 | |
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mountains | 23.1 | |
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tourism | 23.1 | |
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scenic | 22.8 | |
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cliff | 22.1 | |
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national | 20.8 | |
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canyon | 20.1 | |
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forest | 20 | |
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outdoor | 19.9 | |
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clouds | 19.4 | |
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snow | 19 | |
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rocks | 18.8 | |
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lake | 17.4 | |
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stone | 17 | |
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outdoors | 16.4 | |
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sea | 16.4 | |
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valley | 16 | |
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geology | 15.5 | |
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scenery | 15.3 | |
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island | 14.6 | |
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erosion | 14.6 | |
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river | 14.2 | |
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winter | 13.6 | |
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black | 13.3 | |
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desert | 13.1 | |
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cold | 12.9 | |
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natural | 12.7 | |
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land | 12.6 | |
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hiking | 12.5 | |
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television | 12.5 | |
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scene | 12.1 | |
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tourist | 11.8 | |
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sunset | 11.7 | |
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summer | 11.6 | |
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cloud | 11.2 | |
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peaceful | 11 | |
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coast | 10.8 | |
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recreation | 10.8 | |
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vista | 10.7 | |
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adventure | 10.4 | |
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high | 10.4 | |
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beach | 10.3 | |
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season | 10.1 | |
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archipelago | 10.1 | |
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sand | 10 | |
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book jacket | 9.9 | |
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sun | 9.9 | |
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formation | 9.7 | |
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hike | 9.7 | |
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structure | 9.5 | |
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wilderness | 9.4 | |
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weather | 9.4 | |
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light | 9.4 | |
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ocean | 9.3 | |
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billboard | 9.3 | |
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orange | 9.2 | |
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environment | 9 | |
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horizon | 9 | |
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color | 8.9 | |
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mist | 8.7 | |
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peak | 8.7 | |
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deep | 8.6 | |
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dusk | 8.6 | |
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coastline | 8.5 | |
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ice | 8.3 | |
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calm | 8.2 | |
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tranquil | 8.1 | |
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road | 8.1 | |
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rocky | 7.7 | |
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fog | 7.7 | |
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jacket | 7.7 | |
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reflection | 7.7 | |
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panoramic | 7.7 | |
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shore | 7.5 | |
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south | 7.5 | |
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signboard | 7.5 | |
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pine | 7.3 | |
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autumn | 7 | |
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Google
created on 2019-06-17
Painting | 89.4 | |
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Art | 80.3 | |
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Stock photography | 71.4 | |
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Visual arts | 68.6 | |
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Photography | 67.8 | |
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Room | 65.7 | |
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Picture frame | 65.1 | |
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Modern art | 60.1 | |
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Landscape | 59.3 | |
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Artwork | 58.6 | |
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Illustration | 57.7 | |
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Drawing | 51.1 | |
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Microsoft
created on 2019-06-17
gallery | 99.6 | |
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room | 97.6 | |
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painting | 93.4 | |
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scene | 92.9 | |
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drawing | 76.6 | |
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photograph | 57 | |
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picture frame | 27.6 | |
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Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20414471/330,647,9,12/full/0/native.jpg)
AWS Rekognition
Age | 20-38 |
Gender | Male, 50.4% |
Calm | 50.1% |
Surprised | 49.5% |
Angry | 49.5% |
Disgusted | 49.5% |
Confused | 49.6% |
Happy | 49.5% |
Sad | 49.7% |
![](https://ids.lib.harvard.edu/ids/iiif/20414471/316,643,9,13/full/0/native.jpg)
AWS Rekognition
Age | 35-52 |
Gender | Male, 50.1% |
Sad | 49.7% |
Surprised | 49.5% |
Angry | 49.7% |
Happy | 49.5% |
Confused | 49.5% |
Disgusted | 49.6% |
Calm | 50% |
Feature analysis
Categories
Imagga
paintings art | 99.9% | |
|
Captions
Microsoft
created on 2019-06-17
an old photo of a room | 68% | |
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a black and white photo | 40.2% | |
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a black and white photo of a room | 40.1% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20414471/412,818,98,17/full/0/native.jpg)
FLORENTINS.
![](https://ids.lib.harvard.edu/ids/iiif/20414471/285,818,36,18/full/0/native.jpg)
LES
![](https://ids.lib.harvard.edu/ids/iiif/20414471/284,818,225,18/full/0/native.jpg)
LES PECHEURS FLORENTINS.
![](https://ids.lib.harvard.edu/ids/iiif/20414471/323,820,84,15/full/0/native.jpg)
PECHEURS
![](https://ids.lib.harvard.edu/ids/iiif/20414471/332,835,33,13/full/0/native.jpg)
'Could,
![](https://ids.lib.harvard.edu/ids/iiif/20414471/545,830,42,17/full/0/native.jpg)
Ter
![](https://ids.lib.harvard.edu/ids/iiif/20414471/596,845,26,11/full/0/native.jpg)
ully
![](https://ids.lib.harvard.edu/ids/iiif/20414471/186,835,33,13/full/0/native.jpg)
Cni
![](https://ids.lib.harvard.edu/ids/iiif/20414471/186,832,401,18/full/0/native.jpg)
Cni eThillte 'Could, yris 7ablour 7ugh Ter
![](https://ids.lib.harvard.edu/ids/iiif/20414471/415,837,36,10/full/0/native.jpg)
7ablour
![](https://ids.lib.harvard.edu/ids/iiif/20414471/366,836,31,13/full/0/native.jpg)
yris
![](https://ids.lib.harvard.edu/ids/iiif/20414471/281,835,48,13/full/0/native.jpg)
eThillte
![](https://ids.lib.harvard.edu/ids/iiif/20414471/501,831,42,18/full/0/native.jpg)
7ugh
![](https://ids.lib.harvard.edu/ids/iiif/20414471/545,845,47,13/full/0/native.jpg)
eewr
![](https://ids.lib.harvard.edu/ids/iiif/20414471/332,847,289,13/full/0/native.jpg)
vlow .Tirvtur (slwt eewr ully
![](https://ids.lib.harvard.edu/ids/iiif/20414471/500,848,30,9/full/0/native.jpg)
(slwt
![](https://ids.lib.harvard.edu/ids/iiif/20414471/332,850,33,8/full/0/native.jpg)
vlow
![](https://ids.lib.harvard.edu/ids/iiif/20414471/460,848,36,10/full/0/native.jpg)
.Tirvtur
![](https://ids.lib.harvard.edu/ids/iiif/20414471/220,835,21,19/full/0/native.jpg)
par
![](https://ids.lib.harvard.edu/ids/iiif/20414471/190,821,363,34/full/0/native.jpg)
RSFTORENTINS
able
G par
gT
![](https://ids.lib.harvard.edu/ids/iiif/20414471/374,821,137,25/full/0/native.jpg)
RSFTORENTINS
![](https://ids.lib.harvard.edu/ids/iiif/20414471/423,833,25,16/full/0/native.jpg)
able
![](https://ids.lib.harvard.edu/ids/iiif/20414471/190,838,12,17/full/0/native.jpg)
G
![](https://ids.lib.harvard.edu/ids/iiif/20414471/495,832,58,20/full/0/native.jpg)
gT