Machine Generated Data
Tags
Amazon
created on 2022-12-02
Shorts | 100 | |
| ||
Clothing | 100 | |
| ||
Back | 100 | |
| ||
Body Part | 100 | |
| ||
Person | 99.3 | |
| ||
Woman | 99.3 | |
| ||
Adult | 99.3 | |
| ||
Female | 99.3 | |
| ||
Finger | 98.7 | |
| ||
Hand | 98.7 | |
| ||
Shoe | 93.9 | |
| ||
Footwear | 93.9 | |
| ||
Floor | 93.3 | |
| ||
Flooring | 89.2 | |
| ||
Face | 89.2 | |
| ||
Head | 89.2 | |
| ||
Shoe | 89 | |
| ||
Portrait | 79.9 | |
| ||
Photography | 79.9 | |
| ||
Dress | 75.5 | |
| ||
Fashion | 75.4 | |
| ||
Undershirt | 70.1 | |
| ||
Skirt | 57.2 | |
| ||
Underwear | 56.9 | |
| ||
Sandal | 56.9 | |
| ||
Pants | 56.9 | |
| ||
Tattoo | 56.5 | |
| ||
Skin | 56.5 | |
| ||
Smile | 56.5 | |
| ||
Happy | 56.5 | |
| ||
Swimwear | 56.4 | |
| ||
Blouse | 55.5 | |
| ||
Stomach | 55.4 | |
| ||
Knee | 55.3 | |
| ||
Navel | 55.2 | |
|
Clarifai
created on 2023-10-13
Imagga
created on 2022-12-02
Google
created on 2022-12-02
Flash photography | 88.5 | |
| ||
Black-and-white | 84 | |
| ||
Style | 83.8 | |
| ||
Thigh | 80.2 | |
| ||
Knee | 79.6 | |
| ||
Door | 77.3 | |
| ||
Tints and shades | 77.3 | |
| ||
Waist | 75.5 | |
| ||
Art model | 74.7 | |
| ||
Human leg | 74.1 | |
| ||
Monochrome photography | 73.9 | |
| ||
Fashion design | 72.6 | |
| ||
Rectangle | 72.3 | |
| ||
Monochrome | 72.1 | |
| ||
Symmetry | 71.6 | |
| ||
Darkness | 66.6 | |
| ||
Elbow | 66.5 | |
| ||
Room | 63 | |
| ||
Stock photography | 62.1 | |
| ||
Fashion model | 61 | |
|
Microsoft
created on 2022-12-02
clothing | 97.3 | |
| ||
footwear | 94.7 | |
| ||
woman | 94.5 | |
| ||
black and white | 92.7 | |
| ||
white | 87.7 | |
| ||
person | 86.9 | |
| ||
fashion | 85.4 | |
| ||
black | 77.5 | |
| ||
human face | 71.3 | |
| ||
girl | 66.8 | |
| ||
text | 64.5 | |
| ||
high heels | 53.9 | |
|
Color Analysis
Face analysis
Amazon
Microsoft
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1361,511,122,158/full/0/native.jpg)
AWS Rekognition
Age | 21-29 |
Gender | Female, 99.9% |
Calm | 99.1% |
Surprised | 6.3% |
Fear | 5.9% |
Sad | 2.3% |
Confused | 0.2% |
Angry | 0.1% |
Disgusted | 0% |
Happy | 0% |
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1357,530,128,128/full/0/native.jpg)
Microsoft Cognitive Services
Age | 31 |
Gender | Female |
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1328,471,187,217/full/0/native.jpg)
Google Vision
Surprise | Very unlikely |
Anger | Very unlikely |
Sorrow | Very unlikely |
Joy | Very unlikely |
Headwear | Very unlikely |
Blurred | Very unlikely |
Feature analysis
Categories
Imagga
interior objects | 34.6% | |
| ||
paintings art | 27.1% | |
| ||
streetview architecture | 20.3% | |
| ||
events parties | 12.3% | |
| ||
food drinks | 2.8% | |
| ||
text visuals | 1.5% | |
|
Captions
Microsoft
created on 2022-12-02
a woman standing in front of a mirror posing for the camera | 79.1% | |
| ||
a woman standing in front of a door | 79% | |
| ||
a woman standing in front of a mirror | 76.9% | |
|
Text analysis
![](https://ids.lib.harvard.edu/ids/iiif/495803507/865,37,1608,1966/full/0/native.jpg)
ONONONO
ONONONO
ONONONG
ONONONO
ONOKONO
ONOKOHO
OHONONO
QHONONO
ONOHONG
OKONONO
NOWOWONO
00
32
ONONONO
CHORONO
ONONONG
SHOMOKO
CHONONO
ONONONO
OHOMONG
ONORONG
}
OHONONO
0.0.0.0
ококо о
OKOMONO
OMOHONO
OHOMONO
OHOKOHO
OMOMOKO
OSONONO
OXOXOXO
OHONONO
HOYO
OHONONO
OHOHOHO
CHOKONO
ÖKONOHO
ONONOHO
OHOHOHO
DHOYONO
ONO
OHOHOR
OKORON
000
ONOHOXO
OHOXOS
OXOHONG
0000
ОHOKONO
ONDHONG
OKOMOHO
CHOHOHO
OROKOKO
OHOKONO
0000
MOHONG
ONONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/865,40,79,16/full/0/native.jpg)
ONONONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/874,280,77,18/full/0/native.jpg)
ONONONG
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1018,42,79,17/full/0/native.jpg)
ONOKONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1020,129,78,19/full/0/native.jpg)
ONOKOHO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1021,195,78,15/full/0/native.jpg)
OHONONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1020,281,78,16/full/0/native.jpg)
QHONONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1021,341,77,19/full/0/native.jpg)
ONOHONG
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1021,426,77,16/full/0/native.jpg)
OKONONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1010,483,85,17/full/0/native.jpg)
NOWOWONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1018,625,32,12/full/0/native.jpg)
00
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1006,1953,71,49/full/0/native.jpg)
32
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1171,132,79,15/full/0/native.jpg)
CHORONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1174,282,77,16/full/0/native.jpg)
SHOMOKO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1170,342,77,17/full/0/native.jpg)
CHONONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1167,565,71,18/full/0/native.jpg)
OHOMONG
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1173,707,71,14/full/0/native.jpg)
ONORONG
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1217,1691,40,49/full/0/native.jpg)
}
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1317,129,80,18/full/0/native.jpg)
0.0.0.0
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1312,190,53,22/full/0/native.jpg)
ококо
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1381,190,9,22/full/0/native.jpg)
о
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1312,279,80,16/full/0/native.jpg)
OKOMONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1314,343,78,15/full/0/native.jpg)
OMOHONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1313,425,78,17/full/0/native.jpg)
OHOMONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1469,39,80,15/full/0/native.jpg)
OHOKOHO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1469,128,78,19/full/0/native.jpg)
OMOMOKO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1466,190,78,19/full/0/native.jpg)
OSONONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1465,278,80,17/full/0/native.jpg)
OXOXOXO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1463,425,44,15/full/0/native.jpg)
HOYO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1618,193,79,14/full/0/native.jpg)
OHOHOHO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1616,278,78,17/full/0/native.jpg)
CHOKONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1615,338,78,19/full/0/native.jpg)
ÖKONOHO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1611,422,79,18/full/0/native.jpg)
ONONOHO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1609,625,77,16/full/0/native.jpg)
DHOYONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1771,129,36,17/full/0/native.jpg)
ONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1756,569,64,15/full/0/native.jpg)
OHOHOR
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1754,627,63,15/full/0/native.jpg)
OKORON
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1771,710,56,13/full/0/native.jpg)
000
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1944,559,78,16/full/0/native.jpg)
ONOHOXO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1958,620,63,17/full/0/native.jpg)
OHOXOS
![](https://ids.lib.harvard.edu/ids/iiif/495803507/1938,758,76,17/full/0/native.jpg)
OXOHONG
![](https://ids.lib.harvard.edu/ids/iiif/495803507/2094,561,79,15/full/0/native.jpg)
0000
![](https://ids.lib.harvard.edu/ids/iiif/495803507/2092,619,80,15/full/0/native.jpg)
ОHOKONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/2079,896,77,16/full/0/native.jpg)
ONDHONG
![](https://ids.lib.harvard.edu/ids/iiif/495803507/2246,558,79,16/full/0/native.jpg)
OKOMOHO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/2244,619,78,14/full/0/native.jpg)
CHOHOHO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/2229,974,70,16/full/0/native.jpg)
OROKOKO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/2393,564,80,19/full/0/native.jpg)
OHOKONO
![](https://ids.lib.harvard.edu/ids/iiif/495803507/2382,906,67,14/full/0/native.jpg)
MOHONG
![](https://ids.lib.harvard.edu/ids/iiif/495803507/2389,1042,51,13/full/0/native.jpg)
ONONO