Photos | Crowd Goes Wild for DJ's Electrifying Performance at Coachella 2012

DJ Xu Qing wows the crowd with his skills on the turntable during his set at the Coachella 2012 music festival, surrounded by fellow performers and a sea of enthusiastic fans.
BLIP-2 Description:
a dj playing music at a concert in front of a crowdMetadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
esteban urban alexander music mobile martínez transportation hat entertainer performance party yuki saito hardware machine fun club roy heffernan glasses coachella navarro life interior deejay electronics xu qing car vehicle screen accessories nightclub monitor room musical instrument recreation turntable night lighting phone concert computer crowd ludwig consumer
iso
3200
metering mode
5
aperture
f/2.8
exposure bias
2
focal length
16mm
shutter speed
1/8s
camera make
Canon
camera model
lens model
date
2012-04-12T23:30:08.120000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(27.20%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.46%)
failure
(-1.42%)
harmonious color
(-0.60%)
immersiveness
(0.34%)
interaction
(1.00%)
interesting subject
(-58.11%)
intrusive object presence
(-13.77%)
lively color
(-48.68%)
low light
(51.12%)
noise
(-6.98%)
pleasant camera tilt
(-18.95%)
pleasant composition
(-90.09%)
pleasant lighting
(-82.08%)
pleasant pattern
(1.73%)
pleasant perspective
(-9.78%)
pleasant post processing
(3.85%)
pleasant reflection
(-12.11%)
pleasant symmetry
(0.51%)
sharply focused subject
(0.07%)
tastefully blurred
(-30.79%)
well chosen subject
(2.19%)
well framed subject
(-41.72%)
well timed shot
(6.12%)
all
(-14.26%)
* 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.