Machine Generated Data
Tags
Amazon
created on 2022-01-08
Clarifai
created on 2023-10-25
negative | 99.5 | |
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filmstrip | 99.5 | |
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movie | 98.8 | |
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slide | 98.8 | |
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collage | 98.7 | |
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picture frame | 98.4 | |
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cinematography | 97.5 | |
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noisy | 97.3 | |
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art | 97.1 | |
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wear | 96.8 | |
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vintage | 96.8 | |
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margin | 96.7 | |
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sepia | 96.5 | |
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old | 96.2 | |
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retro | 96.1 | |
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dirty | 94.2 | |
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blank | 93.9 | |
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emulsion | 93.7 | |
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sepia pigment | 92.8 | |
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photograph | 92.3 | |
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Imagga
created on 2022-01-08
Google
created on 2022-01-08
Photograph | 94.3 | |
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Rectangle | 89.7 | |
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Line | 81.9 | |
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Wall | 81.5 | |
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Art | 79.9 | |
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Font | 78.1 | |
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Landmark | 77.6 | |
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Tints and shades | 77.4 | |
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Wood | 75.2 | |
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Snapshot | 74.3 | |
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Visual arts | 69.3 | |
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Room | 68.2 | |
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History | 67.9 | |
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Paper product | 67.8 | |
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Photographic film | 66.1 | |
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Square | 65.9 | |
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Stock photography | 63.7 | |
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Vintage clothing | 62.1 | |
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Arch | 62 | |
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Negative | 60.6 | |
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Color Analysis
Face analysis
Amazon

AWS Rekognition
Age | 0-4 |
Gender | Female, 100% |
Calm | 64.4% |
Angry | 19.2% |
Confused | 7% |
Sad | 4.3% |
Disgusted | 2% |
Surprised | 1.5% |
Happy | 0.8% |
Fear | 0.8% |

AWS Rekognition
Age | 4-10 |
Gender | Female, 98.9% |
Calm | 94.3% |
Sad | 1.7% |
Fear | 1.3% |
Happy | 1.2% |
Surprised | 0.6% |
Confused | 0.4% |
Angry | 0.3% |
Disgusted | 0.2% |

AWS Rekognition
Age | 26-36 |
Gender | Male, 96% |
Calm | 79.8% |
Confused | 5.4% |
Happy | 5.4% |
Sad | 3.6% |
Angry | 2.2% |
Disgusted | 1.6% |
Surprised | 1.2% |
Fear | 0.8% |

AWS Rekognition
Age | 29-39 |
Gender | Male, 95.4% |
Happy | 41.2% |
Calm | 25.2% |
Disgusted | 9.5% |
Sad | 6.9% |
Angry | 5.2% |
Confused | 5.1% |
Fear | 4.1% |
Surprised | 2.8% |

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 | 88.2% | |
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paintings art | 10.1% | |
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text visuals | 1.4% | |
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Captions
Clarifai
created by general-english-image-caption-blip on 2025-05-02
a photograph of a man in a suit and hat standing in front of a fence | -100% | |
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Google Gemini
Created by gemini-2.0-flash-lite on 2025-05-07
The image is a sepia-toned contact sheet, capturing three distinct scenes. The contact sheet suggests an older photographic process, likely from the early to mid-20th century.
First Scene: A street scene with several people. Two men in suits are talking on the sidewalk. One woman with a fur collar is looking toward the men and a bus is passing by the side of a big tree.
Second Scene: An older gentleman walking past a fence.
Third Scene: A baby lies comfortably in a carriage. The baby appears to be quite young, perhaps a few months old.
Created by gemini-2.0-flash on 2025-05-07
The image is a strip of old-fashioned photographic film, showing three separate frames or pictures. The film border is a textured, metallic brown. Each frame depicts a different scene.
Frame 1: Appears to be an outdoor street scene. A large tree trunk is positioned in the center of the frame, slightly left. To the left of the tree, there's a vintage bus or vehicle partially visible. To the right of the tree, there are several people. One person, dressed in a dark suit and hat, appears to be conversing with a woman in a coat with fur trim. There are other figures standing in the background, possibly waiting or observing.
Frame 2: This frame captures a man walking in a park-like setting. The man is wearing a cap and appears to be looking to the left. Behind him, there is a low fence and a grassy area with trees in the distance. The scene has a sense of open space and tranquility.
Frame 3: The third frame features a close-up of a baby lying in a stroller. The baby is resting on a white pillow or cushion, and their gaze is directed upwards. The stroller has a dark, possibly leather interior. This frame has a more personal and intimate feel compared to the previous two.
The overall tone of the images is warm and nostalgic, given the color and style of the film strip. The wear of the film is visible.
Text analysis
Amazon





