Photos | Urban Night Club Crowd
A large crowd gathers at a night club in Los Angeles, California for a night of music and entertainment. Smoke fills the room as deejays spin on their laptops, while fans of all ages dance and enjoy the party atmosphere. Among the crowd are Blind Tom Wiggins, Roy Heffernan, Betty Autier, and Katy Brand.
BLIP-2 Description:
a large crowd of people at a club with smokeMetadata
Capture date:
Original Dimensions:
3264w x 2448h - (download 4k)
Usage
Dominant Color:
Location:
music roy katy bag disco room stage urban core computer rock art electronics crowd historic night brand party arts girl instrument concert blind tom wiggins handbag nightclub child fun life machine autier interior laptop manning entertainer heffernan musical performing club deejay recreation performance consumer betty accessories betty autier audience
iso
250
metering mode
5
aperture
f/2.2
focal length
4mm
latitude
34.05
longitude
-118.25
shutter speed
1/24s
camera make
Apple
camera model
lens model
overall
(21.50%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.43%)
failure
(-1.66%)
harmonious color
(-7.37%)
immersiveness
(0.22%)
interaction
(1.00%)
interesting subject
(-45.58%)
intrusive object presence
(-41.80%)
lively color
(-50.68%)
low light
(16.31%)
noise
(-3.83%)
pleasant camera tilt
(-13.37%)
pleasant composition
(-75.68%)
pleasant lighting
(-65.28%)
pleasant pattern
(4.10%)
pleasant perspective
(-6.13%)
pleasant post processing
(-2.06%)
pleasant reflection
(-2.72%)
pleasant symmetry
(0.44%)
sharply focused subject
(0.17%)
tastefully blurred
(-19.67%)
well chosen subject
(0.28%)
well framed subject
(-30.98%)
well timed shot
(9.87%)
all
(-12.07%)
* 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.
* 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.