Machine Generated Data
Tags
Amazon
created on 2023-01-11
Person | 97.6 | |
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Missile | 95.9 | |
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Weapon | 95.9 | |
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Ammunition | 95.9 | |
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Spire | 95.5 | |
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Tower | 95.5 | |
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Building | 95.5 | |
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Architecture | 95.5 | |
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Road | 94.9 | |
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Person | 93.5 | |
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Person | 92.8 | |
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Machine | 90 | |
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Wheel | 90 | |
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Vehicle | 88.3 | |
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Transportation | 88.3 | |
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Aircraft | 88.3 | |
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Airplane | 88.3 | |
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Wheel | 87 | |
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Path | 86.9 | |
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Wheel | 86.3 | |
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Wheel | 86 | |
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Car | 84.9 | |
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Wheel | 82.5 | |
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Wheel | 81.9 | |
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Hat | 81 | |
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Clothing | 81 | |
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War | 79.5 | |
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Car | 78.3 | |
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Person | 74.5 | |
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City | 71.2 | |
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Urban | 71.2 | |
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Metropolis | 71.2 | |
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Shoe | 69.5 | |
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Footwear | 69.5 | |
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Head | 66.8 | |
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Face | 66.7 | |
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Person | 61.8 | |
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Shoe | 56 | |
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Warplane | 55.9 | |
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Bomber | 55.9 | |
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Rocket | 55.3 | |
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Cobblestone | 55.1 | |
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Clarifai
created on 2023-10-13
Imagga
created on 2023-01-11
missile | 100 | |
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weapon | 100 | |
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rocket | 100 | |
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instrument | 85.9 | |
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device | 62.1 | |
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conveyance | 60 | |
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plane | 46.4 | |
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aircraft | 46.2 | |
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airplane | 44.4 | |
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transport | 34.7 | |
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transportation | 32.3 | |
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flight | 30.7 | |
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fly | 28.9 | |
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war | 28.7 | |
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cannon | 28.7 | |
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air | 27.6 | |
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sky | 27.4 | |
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military | 27 | |
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jet | 26.5 | |
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aviation | 26.4 | |
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gun | 25 | |
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engine | 23.1 | |
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travel | 21.1 | |
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flying | 20.8 | |
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airport | 20.6 | |
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wing | 20.1 | |
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propeller | 19.1 | |
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power | 18.5 | |
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cargo | 18.4 | |
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vehicle | 17.1 | |
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industry | 16.2 | |
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cockpit | 14.8 | |
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old | 14.6 | |
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army | 14.6 | |
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technology | 14.1 | |
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speed | 13.7 | |
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pilot | 13.7 | |
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landing | 12.8 | |
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business | 12.8 | |
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force | 12.7 | |
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clouds | 12.7 | |
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tank | 11.9 | |
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runway | 11.8 | |
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airline | 11.8 | |
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airliner | 11.8 | |
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wings | 11.5 | |
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oil | 11.2 | |
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freight | 10.8 | |
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fighter | 10.7 | |
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delivery | 10.7 | |
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metal | 10.5 | |
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historic | 10.1 | |
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danger | 10 | |
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vintage | 9.9 | |
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tourism | 9.9 | |
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barrel | 9.8 | |
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world | 9.7 | |
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steel | 9.7 | |
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torpedo | 9.7 | |
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fuel | 9.6 | |
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cloud | 9.5 | |
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industrial | 9.1 | |
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history | 8.9 | |
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departure | 8.9 | |
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gas | 8.7 | |
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heavy | 8.6 | |
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wheel | 8.5 | |
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energy | 8.4 | |
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road | 8.1 | |
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airfield | 8 | |
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fuselage | 7.9 | |
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battle | 7.8 | |
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conflict | 7.8 | |
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attack | 7.8 | |
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museum | 7.8 | |
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truck | 7.8 | |
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supply | 7.7 | |
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artillery | 7.7 | |
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tail | 7.7 | |
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tower | 7.2 | |
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grass | 7.1 | |
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armament | 7.1 | |
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Google
created on 2023-01-11
Sky | 94.8 | |
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Aircraft | 89.5 | |
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Vehicle | 87.1 | |
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Wheel | 87.1 | |
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Missile | 85.5 | |
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Aerospace manufacturer | 83.8 | |
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Aviation | 83.7 | |
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Military aircraft | 77.1 | |
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Tire | 76.8 | |
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Airplane | 75.8 | |
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Air travel | 74.4 | |
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Monochrome photography | 73.4 | |
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Monochrome | 72.5 | |
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Fighter aircraft | 69 | |
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Aerospace engineering | 68.3 | |
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Jet aircraft | 68 | |
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Fin | 65.8 | |
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Rocket | 64.9 | |
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Ground attack aircraft | 63.8 | |
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Flight | 61.8 | |
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Color Analysis
Face analysis
Amazon
Microsoft
![](https://ids.lib.harvard.edu/ids/iiif/495971830/1774,676,77,113/full/0/native.jpg)
AWS Rekognition
Age | 49-57 |
Gender | Male, 99.6% |
Calm | 90.6% |
Surprised | 6.9% |
Fear | 6.3% |
Angry | 3.3% |
Sad | 2.3% |
Confused | 1.7% |
Happy | 0.8% |
Disgusted | 0.8% |
![](https://ids.lib.harvard.edu/ids/iiif/495971830/1800,702,69,69/full/0/native.jpg)
Microsoft Cognitive Services
Age | 47 |
Gender | Male |
Feature analysis
Categories
Imagga
cars vehicles | 100% | |
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Captions
Microsoft
created on 2023-01-11
a vintage photo of a plane | 75.5% | |
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a vintage photo of an old airplane | 72.9% | |
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a vintage photo of an airplane | 72.8% | |
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Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2381,714,75,32/full/0/native.jpg)
БОРЦУ
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2201,724,176,48/full/0/native.jpg)
МУЖЕСТВЕННОМУ
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2170,723,64,33/full/0/native.jpg)
CAABA
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2197,708,308,64/full/0/native.jpg)
МУЖЕСТВЕННОМУ БОРЦУ ЗА
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2493,679,34,26/full/0/native.jpg)
HA
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2465,711,33,20/full/0/native.jpg)
ЗА
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2165,679,368,76/full/0/native.jpg)
CAABA BEANKOMY COBETCKOMY HA
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2345,684,145,44/full/0/native.jpg)
COBETCKOMY
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2236,708,107,36/full/0/native.jpg)
BEANKOMY
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2173,680,357,104/full/0/native.jpg)
СЛАВА ВЕЛИКОМУ СОВЕТСКОМУ НА
МУЖЕСТВЕННОМУ БОРЦУ ЗА
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2350,685,141,48/full/0/native.jpg)
СОВЕТСКОМУ
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2497,680,30,30/full/0/native.jpg)
НА
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2173,724,61,35/full/0/native.jpg)
СЛАВА
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2239,707,107,43/full/0/native.jpg)
ВЕЛИКОМУ
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2204,725,175,52/full/0/native.jpg)
МУЖЕСТВЕННОМУ
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2385,715,74,37/full/0/native.jpg)
БОРЦУ
![](https://ids.lib.harvard.edu/ids/iiif/495971830/2469,710,26,30/full/0/native.jpg)
ЗА