Photos | Jamming Under the Tent
Sahin Eryilmaz and his band rock the crowd during their performance at Coachella 2012 Weekend 2. The lights, drums, guitars and speakers created an electrifying atmosphere at the concert.
BLIP-2 Description:
a band playing in a tent with a crowd watchingChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
bracelet spotlight urban sahin eryilmaz rock music speaker footwear stage arts musical instrument microphone performing volleyball entertainer performance shoe weekend art night life club hall friday coachella indoors ball audience (ball) cord electronics theater jewelry sport light accessories auditorium musical instrument recreation speakers lighting device guitar concert crowd drum electrical
iso
6400
metering mode
5
aperture
f/2.8
focal length
21mm
shutter speed
1/200s
camera make
Canon
camera model
lens model
date
2012-04-20T22:32:26.780000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(42.36%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.30%)
failure
(-2.12%)
harmonious color
(4.10%)
immersiveness
(1.71%)
interaction
(1.00%)
interesting subject
(8.41%)
intrusive object presence
(-11.04%)
lively color
(-53.03%)
low light
(97.46%)
noise
(-4.64%)
pleasant camera tilt
(-6.63%)
pleasant composition
(-60.74%)
pleasant lighting
(-38.28%)
pleasant pattern
(12.23%)
pleasant perspective
(11.65%)
pleasant post processing
(-3.65%)
pleasant reflection
(5.22%)
pleasant symmetry
(3.96%)
sharply focused subject
(0.22%)
tastefully blurred
(-31.88%)
well chosen subject
(1.00%)
well framed subject
(-26.27%)
well timed shot
(14.33%)
all
(-3.41%)
* 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,
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