Photos | Concertgoers Jam-Packed in a Tent at Coachella
Daniel Ricciardo, Zhang Zhenwang, Scott Goodman, Alexandre Ponomarenko, and 22 others enjoy the music at the 2010 Coachella music festival.
BLIP-2 Description:
a crowd of people in a tent watching a concertChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
daniel speaker room ricciardo theater zhang zhenwang laptop scott hardware recreation saturday screen teen lecture coachella wristwatch cinema pc indoors accessories bag performance auditorium glasses building footwear architecture crowd backpack monitor alexandre ponomarenko goodman concert audience music classroom interior boy cup computer speakers handbag school hall rekognition_c stage hat electronics shoe
iso
800
metering mode
5
aperture
f/4
exposure bias
1
focal length
16mm
shutter speed
1/200s
camera make
Canon
camera model
lens model
date
2010-04-17T16:40:52.320000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(47.97%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.33%)
failure
(-0.44%)
harmonious color
(0.23%)
immersiveness
(3.15%)
interaction
(1.00%)
interesting subject
(16.27%)
intrusive object presence
(-8.67%)
lively color
(-15.04%)
low light
(73.24%)
noise
(-2.32%)
pleasant camera tilt
(-11.03%)
pleasant composition
(-52.05%)
pleasant lighting
(-29.22%)
pleasant pattern
(16.87%)
pleasant perspective
(16.02%)
pleasant post processing
(3.41%)
pleasant reflection
(1.17%)
pleasant symmetry
(3.32%)
sharply focused subject
(0.44%)
tastefully blurred
(-5.37%)
well chosen subject
(-1.25%)
well framed subject
(-28.34%)
well timed shot
(14.25%)
all
(0.89%)
* 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.