Photos | Coachella 2009: The Ultimate Music Festival Experience

Kunal Nayyar, Buddy Murphy, Salvatore Cinquegrana, and Wu Jing join the massive crowd of 29 people at Coachella 2009, surrounded by blue skies, clouds, trees, and plants, enjoying their vibrant outdoor recreation and concert experience.
BLIP-2 Description:
a crowd of people at a music festivalMetadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
Location:
murphy cap urban recreation part sky plant tree teen wu coachella back wristwatch kunal nayyar accessories bag baseball outdoor jewelry glasses footwear crowd jing backpack vacation concert audience party boy mobile phone salvatore cinquegrana buddy balloon bracelet cloudy tourist hat festival electronics fun shoe
iso
100
metering mode
5
aperture
f/6.3
exposure bias
-0.32999999999999996
focal length
16mm
shutter speed
1/400s
camera make
Canon
camera model
lens model
date
2009-04-19T16:20:05.140000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(39.38%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.77%)
failure
(-0.32%)
harmonious color
(2.36%)
immersiveness
(0.73%)
interaction
(1.00%)
interesting subject
(-23.74%)
intrusive object presence
(-14.11%)
lively color
(-12.99%)
low light
(20.17%)
noise
(-2.10%)
pleasant camera tilt
(-8.70%)
pleasant composition
(-77.10%)
pleasant lighting
(-37.55%)
pleasant pattern
(2.76%)
pleasant perspective
(5.23%)
pleasant post processing
(0.17%)
pleasant reflection
(3.02%)
pleasant symmetry
(0.42%)
sharply focused subject
(0.37%)
tastefully blurred
(-9.25%)
well chosen subject
(4.82%)
well framed subject
(-48.75%)
well timed shot
(5.42%)
all
(-4.31%)
* 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.