Photos | Coachella Crowd Goes Wild for DJ's
Helen Kelesi and Kaleigh Fratkin join a sea of partygoers at Coachella, dancing to the beats of deejays and surrounded by a colorful array of clothing and accessories.
BLIP-2 Description:
a large crowd of people at a party with dj'sChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5760w x 3840h - (download 4k)
Usage
thursday headgear necklace urban vsvn music speaker footwear mobile hat wristwatch crowd entertainer performance balloon bag shoe party hardware fun fratkin club glasses friday coachella audience life interior deejay electronics jewelry screen + nightclub accessories monitor room musical instrument recreation turntable headphones night stagne kaleigh phone concert computer handbag helen kelesi
iso
3200
metering mode
5
aperture
f/3.2
exposure bias
0.32999999999999996
focal length
16mm
shutter speed
1/250s
camera make
Canon
camera model
lens model
date
2016-04-15T15:55:31.570000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(35.23%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.52%)
failure
(-0.68%)
harmonious color
(1.19%)
immersiveness
(0.27%)
interaction
(1.00%)
interesting subject
(-17.75%)
intrusive object presence
(-7.67%)
lively color
(-25.22%)
low light
(94.04%)
noise
(-5.22%)
pleasant camera tilt
(-10.50%)
pleasant composition
(-64.70%)
pleasant lighting
(-46.09%)
pleasant pattern
(4.81%)
pleasant perspective
(-0.86%)
pleasant post processing
(6.63%)
pleasant reflection
(-3.69%)
pleasant symmetry
(0.34%)
sharply focused subject
(0.34%)
tastefully blurred
(-14.00%)
well chosen subject
(1.68%)
well framed subject
(-38.89%)
well timed shot
(5.01%)
all
(-5.85%)
* 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.