Photos | Nightclub Crowd

Ryan Starr, Josh O'Connor, and Heather K are among the 16 people in this lively nightclub crowd, sporting glasses, hats, and jewelry, while enjoying a night out on the town.
BLIP-2 Description:
a group of people standing in a roomMetadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
bracelet headgear necklace urban optical pub baseball portrait bar cap beverage equipment hat ryan starr k counter party eyeglasses old proper fun club alcohol shirt junglescene glasses josh audience disco life interior sunglasses heather jewelry accessories nightclub room night o'connor photography crowd
Detected Text
date
2003-02-24T18:57:19-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(21.09%)
curation
(69.29%)
highlight visibility
(5.83%)
behavioral
(70.50%)
failure
(-0.76%)
harmonious color
(-0.35%)
immersiveness
(0.10%)
interaction
(2.00%)
interesting subject
(-58.98%)
intrusive object presence
(-8.69%)
lively color
(-4.86%)
low light
(99.90%)
noise
(-26.78%)
pleasant camera tilt
(-7.07%)
pleasant composition
(-77.73%)
pleasant lighting
(-71.58%)
pleasant pattern
(2.66%)
pleasant perspective
(-11.41%)
pleasant post processing
(0.31%)
pleasant reflection
(5.23%)
pleasant symmetry
(0.05%)
sharply focused subject
(0.20%)
tastefully blurred
(1.53%)
well chosen subject
(-24.51%)
well framed subject
(-51.42%)
well timed shot
(-10.83%)
all
(-12.21%)
* 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.