Photos | Group Performance in Robes at Coachella Concert

Boris KoDisc Jockeyoe and a group of 13 people in robes perform on stage at Coachella during the Saturday night concert. The crowd is captured in the spotlight, showcasing the urban clothing and footwear styles of the attendees.
BLIP-2 Description:
a group of people in robes on stageMetadata
Capture date:
Original Dimensions:
5760w x 3840h - (download 4k)
Usage
Dominant Color:
Location:
group activities spotlight urban rock leisure music boris kodisc jockeyoe footwear stage hat wristwatch theatre performing arts musician saturday performance shoe art glove glasses indoors coachella life interior electronics theater performer light accessories musical room instrument night recreation band lighting concert crowd dancing dance pose
iso
3200
metering mode
5
aperture
f/2.8
focal length
16mm
shutter speed
1/1250s
camera make
Canon
camera model
lens model
date
2014-04-12T22:48:54.460000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(54.64%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.43%)
failure
(-0.29%)
harmonious color
(13.02%)
immersiveness
(0.12%)
interaction
(1.00%)
interesting subject
(32.96%)
intrusive object presence
(-22.22%)
lively color
(-16.70%)
low light
(99.46%)
noise
(-2.42%)
pleasant camera tilt
(-7.38%)
pleasant composition
(-68.95%)
pleasant lighting
(-13.64%)
pleasant pattern
(3.42%)
pleasant perspective
(7.69%)
pleasant post processing
(3.02%)
pleasant reflection
(-3.98%)
pleasant symmetry
(0.76%)
sharply focused subject
(0.34%)
tastefully blurred
(-10.24%)
well chosen subject
(-10.50%)
well framed subject
(-22.03%)
well timed shot
(32.86%)
all
(1.93%)
* 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.