Machine Generated Data
Tags
Amazon
created on 2022-06-04
Railway | 99.8 | |
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Train Track | 99.8 | |
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Rail | 99.8 | |
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Transportation | 99.8 | |
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Staircase | 67.6 | |
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Theme Park | 63.7 | |
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Amusement Park | 63.7 | |
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Imagga
created on 2022-06-04
track | 100 | |
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railway | 48.1 | |
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train | 44.4 | |
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railroad | 44.3 | |
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transportation | 43.1 | |
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travel | 36.7 | |
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rail | 35.4 | |
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road | 27.1 | |
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station | 25.3 | |
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way | 24.6 | |
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journey | 24.5 | |
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steel | 23.9 | |
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tie | 23.1 | |
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transport | 21.9 | |
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speed | 19.3 | |
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perspective | 18.9 | |
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industry | 18 | |
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landscape | 17.9 | |
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tracks | 17.7 | |
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building | 17.6 | |
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urban | 16.6 | |
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sky | 16.6 | |
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rails | 15.8 | |
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architecture | 15.6 | |
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traffic | 15.2 | |
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trip | 15.1 | |
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city | 15 | |
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tourism | 14 | |
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line | 13.7 | |
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brace | 13.7 | |
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direction | 13.3 | |
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fast | 13.1 | |
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iron | 13.1 | |
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metal | 12.9 | |
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bridge | 12.9 | |
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transit | 12.8 | |
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vehicle | 12.3 | |
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outdoors | 12 | |
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industrial | 11.8 | |
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device | 11.7 | |
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outdoor | 11.5 | |
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tunnel | 11.3 | |
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old | 11.2 | |
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grass | 11.1 | |
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light | 10.7 | |
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mountain | 10.7 | |
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rural | 10.6 | |
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strengthener | 10.3 | |
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commute | 9.9 | |
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motion | 9.4 | |
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car | 9.4 | |
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modern | 9.1 | |
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landmark | 9 | |
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river | 8.9 | |
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gravel | 8.9 | |
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highway | 8.7 | |
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structure | 8.6 | |
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path | 8.5 | |
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horizon | 8.1 | |
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step | 8.1 | |
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support | 7.9 | |
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locomotive | 7.9 | |
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subway | 7.9 | |
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platform | 7.9 | |
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far | 7.9 | |
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cars | 7.8 | |
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tree | 7.7 | |
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cityscape | 7.6 | |
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wood | 7.5 | |
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destination | 7.5 | |
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evening | 7.5 | |
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long | 7.4 | |
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business | 7.3 | |
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tourist | 7.3 | |
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lines | 7.2 | |
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night | 7.1 | |
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summer | 7.1 | |
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Google
created on 2022-06-04
Photograph | 94.2 | |
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Black | 89.5 | |
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Track | 89 | |
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Mode of transport | 86 | |
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Railway | 85.8 | |
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Black-and-white | 84.1 | |
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Style | 83.8 | |
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Line | 81.7 | |
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Sky | 78.6 | |
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Parallel | 78 | |
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Symmetry | 75.6 | |
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Monochrome | 74.7 | |
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Monochrome photography | 74.3 | |
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Roof | 72.9 | |
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Metal | 71.3 | |
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Road | 71 | |
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City | 68.5 | |
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Bridge | 68.2 | |
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Handrail | 66.2 | |
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Stock photography | 64.7 | |
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Microsoft
created on 2022-06-04
black and white | 94.1 | |
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black | 76.2 | |
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train | 74.3 | |
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white | 68.7 | |
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vehicle | 54.4 | |
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Color Analysis
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20489286/75,306,871,498/full/0/native.jpg)
Staircase | 67.6% | |
|
Categories
Imagga
nature landscape | 50.6% | |
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cars vehicles | 34.4% | |
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streetview architecture | 5.4% | |
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sunrises sunsets | 3.3% | |
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paintings art | 3.2% | |
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beaches seaside | 1.8% | |
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Captions
Microsoft
created on 2022-06-04
an old photo of a bridge | 47.5% | |
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Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20489286/164,239,38,11/full/0/native.jpg)
COAL
![](https://ids.lib.harvard.edu/ids/iiif/20489286/152,230,59,9/full/0/native.jpg)
METROPOLITAN
![](https://ids.lib.harvard.edu/ids/iiif/20489286/30,791,66,18/full/0/native.jpg)
Forest
![](https://ids.lib.harvard.edu/ids/iiif/20489286/156,248,49,11/full/0/native.jpg)
COMPANY
![](https://ids.lib.harvard.edu/ids/iiif/20489286/283,795,40,13/full/0/native.jpg)
ouer
![](https://ids.lib.harvard.edu/ids/iiif/20489286/908,793,51,19/full/0/native.jpg)
2467
![](https://ids.lib.harvard.edu/ids/iiif/20489286/283,788,130,24/full/0/native.jpg)
ouer arborwa
![](https://ids.lib.harvard.edu/ids/iiif/20489286/657,797,66,17/full/0/native.jpg)
Sep.30
![](https://ids.lib.harvard.edu/ids/iiif/20489286/657,797,100,17/full/0/native.jpg)
Sep.30 .09
![](https://ids.lib.harvard.edu/ids/iiif/20489286/729,800,28,15/full/0/native.jpg)
.09
![](https://ids.lib.harvard.edu/ids/iiif/20489286/328,788,84,23/full/0/native.jpg)
arborwa
![](https://ids.lib.harvard.edu/ids/iiif/20489286/32,230,728,588/full/0/native.jpg)
Forest
METROPOLITAN
COAL
COMPANY
ouer arb
sep. 30.09
![](https://ids.lib.harvard.edu/ids/iiif/20489286/32,794,66,18/full/0/native.jpg)
Forest
![](https://ids.lib.harvard.edu/ids/iiif/20489286/154,230,61,15/full/0/native.jpg)
METROPOLITAN
![](https://ids.lib.harvard.edu/ids/iiif/20489286/165,240,41,15/full/0/native.jpg)
COAL
![](https://ids.lib.harvard.edu/ids/iiif/20489286/159,248,51,14/full/0/native.jpg)
COMPANY
![](https://ids.lib.harvard.edu/ids/iiif/20489286/285,797,44,14/full/0/native.jpg)
ouer
![](https://ids.lib.harvard.edu/ids/iiif/20489286/331,797,32,14/full/0/native.jpg)
arb
![](https://ids.lib.harvard.edu/ids/iiif/20489286/659,800,36,17/full/0/native.jpg)
sep
![](https://ids.lib.harvard.edu/ids/iiif/20489286/693,800,11,17/full/0/native.jpg)
.
![](https://ids.lib.harvard.edu/ids/iiif/20489286/698,800,62,17/full/0/native.jpg)
30.09