Photos | Coachella 2010: A Sea of Music Fans
David Jude Jolicoeur, Joy Bryant, and Don Was join thousands of enthusiastic festival-goers under a clear blue sky for a memorable day of music and entertainment.
BLIP-2 Description:
a large crowd of people at a music festivalChronologically Adjacent
Note: You can also navigate with your arrow keys or swiping.
Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
speech bracelet activities sunday david jude jolicoeur leisure music speaker footwear stage lamp crowd musician outdoor tennis performance sky shoe bag joy bryant don was glasses indoors coachella audience pc ball electronics jewelry performer sport group performance accessories musical instrument recreation band speakers laptop concert computer handbag
iso
400
metering mode
5
aperture
f/2.8
focal length
35mm
shutter speed
1/8000s
camera make
Canon
camera model
lens model
date
2010-04-18T16:16:40.510000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(40.50%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.49%)
failure
(-0.44%)
harmonious color
(2.89%)
immersiveness
(3.22%)
interaction
(1.00%)
interesting subject
(-7.89%)
intrusive object presence
(-10.72%)
lively color
(-3.15%)
low light
(1.15%)
noise
(-1.07%)
pleasant camera tilt
(-10.94%)
pleasant composition
(-68.31%)
pleasant lighting
(-37.77%)
pleasant pattern
(7.67%)
pleasant perspective
(6.77%)
pleasant post processing
(1.98%)
pleasant reflection
(0.28%)
pleasant symmetry
(0.76%)
sharply focused subject
(0.24%)
tastefully blurred
(-5.33%)
well chosen subject
(9.61%)
well framed subject
(-43.43%)
well timed shot
(8.40%)
all
(-2.23%)
* 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.