Photos | Rocking the Night Away at Coachella

Joanna Shields, Jenny Wallwork, Max Brauer, and Keiichi Hayashi join the crowd at Coachella Weekend 2 for an unforgettable concert experience under the spotlight.
BLIP-2 Description:
a crowd of people at a concert with a stage and lightsMetadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
Location:
group activities joanna shields spotlight urban rock leisure music speaker footwear stage arts hat performing crowd musician solo volleyball keiichi performance shoe bag weekend jenny art night life hall indoors coachella audience ball (ball) electronics theater performer sport light max brauer hayashi accessories auditorium musical instrument recreation band lighting wallwork day concert handbag
iso
3200
metering mode
5
aperture
f/2.8
exposure bias
-0.67
focal length
16mm
shutter speed
1/250s
camera make
Canon
camera model
lens model
date
2013-04-19T23:20:09.220000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(54.49%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.47%)
failure
(-0.81%)
harmonious color
(8.12%)
immersiveness
(2.05%)
interaction
(1.00%)
interesting subject
(6.88%)
intrusive object presence
(-5.08%)
lively color
(-15.23%)
low light
(98.88%)
noise
(-8.98%)
pleasant camera tilt
(-10.08%)
pleasant composition
(-23.79%)
pleasant lighting
(-9.32%)
pleasant pattern
(11.89%)
pleasant perspective
(5.46%)
pleasant post processing
(6.08%)
pleasant reflection
(2.47%)
pleasant symmetry
(0.66%)
sharply focused subject
(0.59%)
tastefully blurred
(-5.29%)
well chosen subject
(-10.88%)
well framed subject
(-23.38%)
well timed shot
(3.01%)
all
(3.58%)
* 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.