Photos | Nightclub Crowd in Baseball Hats
Li Jing and 22 others hang out in an urban nightclub, sporting baseball caps and chatting amidst disco lighting and alcohol.
BLIP-2 Description:
a crowd of people standing around in a nightclubChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
urban li jing night jeans party portrait glasses old shirt footwear bag teen respect interior crowd necklace counter bassluv jewelry baseball cap pub disco junglescene lighting rednblue shoe handbag electronics nightclub boy bar room pants cup beverage baseball speaker life hat light fun club alcohol accessories photography headgear cap
Detected Text
overall
(19.73%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.59%)
failure
(-0.88%)
harmonious color
(-1.40%)
immersiveness
(0.05%)
interaction
(1.00%)
interesting subject
(-41.85%)
intrusive object presence
(-30.40%)
lively color
(-9.36%)
low light
(99.66%)
noise
(-38.60%)
pleasant camera tilt
(-9.75%)
pleasant composition
(-82.18%)
pleasant lighting
(-74.41%)
pleasant pattern
(4.59%)
pleasant perspective
(-15.10%)
pleasant post processing
(3.46%)
pleasant reflection
(3.02%)
pleasant symmetry
(0.10%)
sharply focused subject
(0.07%)
tastefully blurred
(-7.84%)
well chosen subject
(-34.45%)
well framed subject
(-51.12%)
well timed shot
(-12.12%)
all
(-13.83%)
* NOTE: Amazon Rekognition
detected a celebrity in this image using the
Celebrity Recognition API. The API isn't perfect, but it does give you the MatchConfidence which I display
next to the celebrity's name along with links _↗ to their info.
* NOTE: This image was scaled up from its original size using an AI model called GFP-GAN (Generative Facial Prior), which is a
Generative adversartial network that can be used to repair (or upscale in this case) photos, sometimes the results are a little...
weird.
* WARNING: The title and caption of this image were generated by an AI LLM (gpt-3.5-turbo-0301
from
OpenAI)
based on a
BLIP-2 image-to-text labeling, tags,
location,
people
and album metadata from the image and are
potentially inaccurate, often hilariously so. If you'd like me to adjust anything,
just reach out.