Human Generated Data

Title

Scene at Indian Payment, Odanah, Wisconsin

Date

c. 1866

People

Artist: Whitney & Zimmerman, American active 1860s-70s

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Gift of Professor and Mrs. John Coolidge, P1979.151

Human Generated Data

Title

Scene at Indian Payment, Odanah, Wisconsin

People

Artist: Whitney & Zimmerman, American active 1860s-70s

Date

c. 1866

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Gift of Professor and Mrs. John Coolidge, P1979.151

Machine Generated Data

Tags

Amazon
created on 2022-01-22

Person 99.3
Human 99.3
Person 99.3
Person 99.1
Person 98.8
Person 98.6
Person 97.1
Person 96.9
Person 96.8
People 88.6
Person 86.6
Person 86.1
Apparel 85.6
Clothing 85.6
Person 75.9
Person 75.6
Painting 73.8
Art 73.8
Advertisement 70.3
Poster 69.7
Face 68.5
Text 67.5
Person 64.3
Female 63.8
Person 61.7
Photography 61.3
Photo 61.3
Person 60.7
Collage 59.7
Person 56.9
Drawing 55.3
Person 52.3
Person 49.2

Clarifai
created on 2023-10-26

people 100
group 99.5
adult 98.9
many 98.2
child 95.6
man 95
soldier 92.5
wear 92.3
military 91.7
woman 90.3
war 89.5
print 86.7
group together 84.6
several 84.2
furniture 82.2
administration 81.9
leader 81.7
elderly 81.3
art 81.2
vehicle 78.7

Imagga
created on 2022-01-22

metropolitan 25
old 23
sculpture 19.7
architecture 18
person 17.7
people 17.3
statue 17.3
religion 15.2
ancient 14.7
travel 14.1
man 13.4
history 13.4
art 12.9
room 12.8
tourism 12.4
stone 12.2
monument 12.1
ruler 12.1
building 10.6
antique 10.6
iron lung 10.6
home 10.4
religious 10.3
house 10
traditional 10
city 10
landmark 9.9
vintage 9.9
temple 9.5
adult 9.4
culture 9.4
male 9.3
daily 8.8
scene 8.6
day 8.6
god 8.6
respirator 8.5
historical 8.5
historic 8.2
mother 8.2
new 8.1
family 8
soldier 7.8
sitting 7.7
holy 7.7
spiritual 7.7
clothing 7.7
two 7.6
famous 7.4
church 7.4
tradition 7.4
interior 7.1

Google
created on 2022-01-22

Human 89.4
Coat 89.3
Social group 82.8
Adaptation 79.3
Suit 76.6
Event 72.2
Crew 71.6
Vintage clothing 71.5
Classic 69.7
History 68.8
Team 68.4
Art 67.7
Room 67
Stock photography 63.3
Font 57.5
Illustration 56.1
Uniform 53.6
Paper product 53.5
Conversation 52.9
Retro style 51.7

Microsoft
created on 2022-01-22

text 97.6
clothing 95.2
person 90.1
man 86.3
old 57
room 41.5
clothes 16.1
several 10.9

Color Analysis

Face analysis

Amazon

Google

AWS Rekognition

Age 40-48
Gender Female, 100%
Angry 78.9%
Calm 17.2%
Disgusted 2.6%
Sad 0.5%
Happy 0.3%
Surprised 0.2%
Confused 0.2%
Fear 0.1%

AWS Rekognition

Age 54-62
Gender Male, 100%
Calm 98%
Sad 1.1%
Surprised 0.3%
Angry 0.2%
Disgusted 0.1%
Confused 0.1%
Fear 0.1%
Happy 0.1%

AWS Rekognition

Age 40-48
Gender Female, 99.2%
Calm 96.2%
Happy 1.7%
Sad 0.7%
Confused 0.4%
Disgusted 0.3%
Fear 0.3%
Angry 0.2%
Surprised 0.2%

AWS Rekognition

Age 23-31
Gender Female, 81.7%
Calm 99.9%
Confused 0%
Sad 0%
Disgusted 0%
Surprised 0%
Angry 0%
Fear 0%
Happy 0%

AWS Rekognition

Age 34-42
Gender Female, 96%
Calm 91%
Angry 4.9%
Disgusted 2.4%
Sad 0.5%
Happy 0.3%
Surprised 0.3%
Confused 0.3%
Fear 0.2%

AWS Rekognition

Age 48-56
Gender Male, 83.3%
Calm 59.5%
Sad 18.8%
Confused 15.4%
Angry 2.3%
Disgusted 2%
Surprised 1%
Fear 0.5%
Happy 0.4%

AWS Rekognition

Age 37-45
Gender Female, 87.3%
Sad 50.4%
Calm 24.2%
Happy 14.3%
Angry 3.5%
Disgusted 2.4%
Confused 2%
Fear 1.7%
Surprised 1.4%

AWS Rekognition

Age 23-33
Gender Male, 71.4%
Calm 95.8%
Sad 1.5%
Angry 0.8%
Fear 0.6%
Surprised 0.5%
Confused 0.5%
Happy 0.2%
Disgusted 0.2%

AWS Rekognition

Age 26-36
Gender Female, 97.8%
Calm 97.8%
Sad 0.5%
Fear 0.4%
Happy 0.3%
Angry 0.3%
Surprised 0.2%
Confused 0.2%
Disgusted 0.2%

AWS Rekognition

Age 20-28
Gender Male, 90.3%
Calm 94.6%
Fear 1.4%
Confused 1.3%
Sad 0.9%
Angry 0.7%
Surprised 0.4%
Happy 0.4%
Disgusted 0.3%

AWS Rekognition

Age 53-61
Gender Female, 64.8%
Calm 75.5%
Sad 18.9%
Fear 2.5%
Disgusted 1.3%
Angry 0.9%
Surprised 0.4%
Happy 0.2%
Confused 0.2%

AWS Rekognition

Age 37-45
Gender Male, 96%
Happy 47.1%
Calm 33.6%
Angry 11.6%
Disgusted 2.5%
Sad 2.1%
Surprised 1.4%
Fear 0.9%
Confused 0.9%

AWS Rekognition

Age 36-44
Gender Male, 98.5%
Calm 85.9%
Happy 3.9%
Confused 3%
Angry 2.2%
Surprised 2%
Disgusted 1.4%
Sad 1.2%
Fear 0.4%

AWS Rekognition

Age 41-49
Gender Male, 88.3%
Calm 58.4%
Sad 27.6%
Happy 7.9%
Confused 1.6%
Angry 1.5%
Disgusted 1.1%
Surprised 1%
Fear 0.8%

AWS Rekognition

Age 22-30
Gender Male, 78.8%
Calm 73.1%
Happy 20%
Angry 3.5%
Disgusted 0.8%
Fear 0.7%
Surprised 0.6%
Sad 0.6%
Confused 0.6%

AWS Rekognition

Age 14-22
Gender Male, 99.4%
Happy 37.6%
Angry 17.9%
Disgusted 15.1%
Sad 11%
Calm 10.3%
Confused 4.8%
Surprised 1.9%
Fear 1.5%

AWS Rekognition

Age 23-31
Gender Female, 75.9%
Calm 81.4%
Sad 6.1%
Happy 5.2%
Angry 2.9%
Confused 1.6%
Disgusted 1.1%
Fear 0.9%
Surprised 0.8%

AWS Rekognition

Age 25-35
Gender Female, 84.1%
Sad 43.4%
Angry 17.4%
Disgusted 16%
Fear 8%
Calm 7.7%
Confused 3.4%
Happy 2.8%
Surprised 1.3%

AWS Rekognition

Age 45-53
Gender Female, 55.3%
Calm 80%
Confused 6%
Sad 5.8%
Disgusted 3%
Angry 2.3%
Happy 1.3%
Surprised 1%
Fear 0.6%

AWS Rekognition

Age 29-39
Gender Male, 81.4%
Calm 99.5%
Sad 0.1%
Happy 0.1%
Disgusted 0.1%
Confused 0.1%
Surprised 0%
Fear 0%
Angry 0%

AWS Rekognition

Age 26-36
Gender Male, 87.8%
Surprised 98.7%
Calm 0.9%
Disgusted 0.1%
Angry 0.1%
Fear 0.1%
Sad 0.1%
Happy 0%
Confused 0%

AWS Rekognition

Age 30-40
Gender Female, 99.7%
Angry 59.4%
Calm 20.3%
Disgusted 6.7%
Fear 5.6%
Sad 3%
Surprised 2.5%
Happy 1.2%
Confused 1.2%

AWS Rekognition

Age 24-34
Gender Male, 87.6%
Sad 67.8%
Angry 27.2%
Calm 2.2%
Fear 1%
Disgusted 1%
Confused 0.4%
Surprised 0.2%
Happy 0.2%

AWS Rekognition

Age 23-33
Gender Male, 99.7%
Surprised 76.4%
Calm 23.1%
Disgusted 0.2%
Angry 0.1%
Sad 0.1%
Fear 0.1%
Happy 0%
Confused 0%

AWS Rekognition

Age 4-12
Gender Male, 99.2%
Sad 75.1%
Calm 13.6%
Angry 4.8%
Disgusted 2.8%
Confused 1.6%
Happy 1.3%
Surprised 0.5%
Fear 0.4%

AWS Rekognition

Age 21-29
Gender Female, 92.3%
Calm 73.9%
Sad 11.1%
Angry 6.4%
Happy 3%
Disgusted 2%
Fear 1.7%
Surprised 1%
Confused 0.9%

AWS Rekognition

Age 22-30
Gender Female, 97.4%
Calm 97%
Happy 1.4%
Surprised 0.4%
Fear 0.3%
Angry 0.3%
Disgusted 0.3%
Confused 0.2%
Sad 0.1%

AWS Rekognition

Age 34-42
Gender Male, 76.2%
Calm 51.2%
Disgusted 13.1%
Happy 10.7%
Angry 9.2%
Fear 5.1%
Surprised 4.9%
Sad 4.6%
Confused 1.2%

AWS Rekognition

Age 23-31
Gender Male, 70.4%
Happy 51.1%
Calm 24.1%
Angry 10.1%
Surprised 4.2%
Sad 3.9%
Disgusted 2.6%
Confused 2%
Fear 2%

AWS Rekognition

Age 18-24
Gender Female, 98.4%
Happy 99.8%
Surprised 0%
Calm 0%
Angry 0%
Sad 0%
Fear 0%
Disgusted 0%
Confused 0%

AWS Rekognition

Age 20-28
Gender Male, 61.9%
Sad 72.6%
Calm 13.3%
Confused 4.8%
Fear 2.7%
Angry 2.4%
Disgusted 1.9%
Happy 1.7%
Surprised 0.7%

AWS Rekognition

Age 20-28
Gender Female, 97.4%
Calm 84.9%
Sad 5.2%
Confused 3.1%
Happy 3%
Disgusted 1.4%
Angry 1.1%
Surprised 0.9%
Fear 0.4%

AWS Rekognition

Age 16-22
Gender Female, 66%
Calm 65.7%
Angry 11.1%
Happy 10.7%
Sad 6.2%
Disgusted 2.1%
Confused 1.6%
Surprised 1.6%
Fear 1%

AWS Rekognition

Age 28-38
Gender Male, 80.2%
Calm 94%
Sad 2.7%
Angry 2%
Confused 0.4%
Happy 0.4%
Fear 0.2%
Disgusted 0.2%
Surprised 0.1%

AWS Rekognition

Age 2-8
Gender Male, 95.9%
Confused 29.7%
Calm 24%
Happy 18.9%
Sad 16.1%
Angry 5.7%
Disgusted 3.1%
Surprised 1.4%
Fear 1.1%

AWS Rekognition

Age 21-29
Gender Female, 96.1%
Calm 47%
Happy 28.9%
Fear 5.7%
Surprised 5.5%
Disgusted 4.9%
Angry 3.3%
Sad 3%
Confused 1.8%

AWS Rekognition

Age 29-39
Gender Male, 99.2%
Calm 99.4%
Sad 0.2%
Angry 0.1%
Happy 0.1%
Surprised 0.1%
Disgusted 0.1%
Fear 0%
Confused 0%

AWS Rekognition

Age 24-34
Gender Male, 81.8%
Calm 97.6%
Sad 1.5%
Confused 0.3%
Disgusted 0.2%
Happy 0.1%
Angry 0.1%
Surprised 0.1%
Fear 0.1%

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Likely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very likely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Possible
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very likely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Likely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Likely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very likely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very likely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Unlikely
Blurred Very unlikely

Feature analysis

Amazon

Person 99.3%
Painting 73.8%

Categories

Imagga

paintings art 73.8%
interior objects 25%

Captions

Azure OpenAI

Created on 2024-01-26

The image displays a stereograph of a gathering of people outdoors around a simple table, where some sort of transaction appears to be taking place. The men are dressed in a variety of attire, from suits and hats to more casual, traditional clothing, suggesting a historic setting or an occasion of significance involving diverse participants. The individuals are engaged with one another, some standing while others are seated at the table. There are sacks on the ground, possibly indicating the presence of goods or items related to the event shown. The attire and the setup suggest a bygone era. The scene is set outdoors, with no distinct landmarks or buildings in sight, and the text at the bottom of the image indicates the subject as "Scene at Indian Payment, Odonah, Wis.," dating the image to a specific time and place in history related to transactions or dealings with Native American communities.

Anthropic Claude

Created on 2024-03-30

The image appears to be a stereoscopic photograph depicting a group of people, likely gathered for an occasion or event. The scene shows a large crowd of individuals, both men and women, seated and standing around two tables or desks. The people seem to be engaged in some kind of activity or discussion, though the specific nature of the event is not clear from the image alone. The photograph has a sepia-toned quality, characteristic of the era in which it was likely captured.

Meta Llama

Created on 2024-12-02

The image is a stereograph, a type of photograph that uses two images to create a 3D effect when viewed through a stereoscope. The stereograph depicts a scene of people gathered around a table, with some individuals standing and others seated. * **Scene:** * The scene appears to be set outdoors, possibly in a rural or natural setting. * There are several people present, all dressed in clothing typical of the late 19th or early 20th century. * Some of the individuals are wearing hats, while others have their heads uncovered. * The atmosphere seems to be one of gathering or meeting, with people engaged in conversation or activity. * **Table:** * The table is positioned centrally in the image, with several people standing or sitting around it. * The table appears to be made of wood and has a simple design. * There are various objects on the table, including what appears to be a basket, a box, and some papers or documents. * **People:** * The people in the image are dressed in clothing typical of the late 19th or early 20th century. * Some of the individuals are wearing hats, while others have their heads uncovered. * The people appear to be engaged in conversation or activity, with some gesturing or pointing at objects on the table. * **Background:** * The background of the image is not clearly defined, but it appears to be a natural setting, possibly a field or a forest. * There are some trees or other vegetation visible in the distance, but the details are not clear. * **Overall:** * The image suggests a sense of community and gathering, with people coming together to discuss or engage in an activity. * The use of a stereograph format adds a sense of depth and dimensionality to the image, making it feel more immersive and engaging. In summary, the image is a stereograph that depicts a scene of people gathered around a table, engaged in conversation or activity. The image suggests a sense of community and gathering, with people coming together to discuss or engage in an activity. The use of a stereograph format adds a sense of depth and dimensionality to the image, making it feel more immersive and engaging.

Text analysis

Amazon

SHORE
NORTH SHORE
Indian
NORTH
Scene
at
PAUL
SAINT PAUL
734
SAINT
SUPERIOR
Wis
LAKE SUPERIOR SCENERY
SCENERY
LAKE
WHITNEY
Scene at Indian Pavment-Qdanah Wis
WHITNEY 22
22
Pavment-Qdanah

Google

734 Scene at Indian Payment-0danah Wis. HITNEY & ZIMMEA SAINT PAU
734
Scene
at
Indian
Payment-0danah
Wis.
HITNEY
&
ZIMMEA
SAINT
PAU