Photos | Night of Loud Music and Wild Fun
Yan Zibei, Joseph Pulitzer, Aamir Rashadi Madni, and a crowd of 49 people let loose at a high-energy concert in Los Angeles. The urban lighting and deejay's performance created the perfect atmosphere for a night of recreation and entertainment.
BLIP-2 Description:
a crowd of people watching a concertChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
2448w x 3264h - (download 4k)
Usage
Dominant Color:
Location:
boy urban rock music child speaker footwear core stage crowd entertainer historic performance bag shoe party glove yan fun zibei club hall indoors audience disco life deejay rekognition_c electronics theater joseph pulitzer accessories auditorium night recreation lighting rashadi aamir concert handbag madni
iso
320
metering mode
5
aperture
f/2.2
focal length
4mm
latitude
34.05
longitude
-118.25
shutter speed
1/15s
camera make
Apple
camera model
lens model
date
2014-11-28T00:12:37.318000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(26.20%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.41%)
failure
(-1.03%)
harmonious color
(-1.85%)
immersiveness
(0.44%)
interaction
(1.00%)
interesting subject
(-32.74%)
intrusive object presence
(-6.52%)
lively color
(-13.54%)
low light
(13.50%)
noise
(-20.24%)
pleasant camera tilt
(-15.00%)
pleasant composition
(-57.91%)
pleasant lighting
(-49.44%)
pleasant pattern
(7.52%)
pleasant perspective
(-3.88%)
pleasant post processing
(0.49%)
pleasant reflection
(-9.27%)
pleasant symmetry
(0.46%)
sharply focused subject
(0.15%)
tastefully blurred
(-7.93%)
well chosen subject
(-14.11%)
well framed subject
(-37.40%)
well timed shot
(-0.86%)
all
(-8.08%)
* 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.