Photos | Coachella Crowd Goes Wild
Laura Tanguy and 18 other concertgoers lose themselves in the music under the starry night sky at the Empire Polo Club in Indio.
BLIP-2 Description:
a crowd of people standing in front of a fenceChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5760w x 3840h - (download 4k)
Usage
Dominant Color:
Location:
group activities necklace ca urban leisure music festival eos iii stage arts outdoors wristwatch hat empire performing musician states outdoor sky performance bag city party art machine night life fun club indio glasses friday coachella audience metropolis mark nature wheel united jewelry coachella valley performer laura tanguy accessories musical instrument night handbag april spring cheering band canon part back california concert crowd polo dancing
iso
6400
metering mode
5
aperture
f/3.2
focal length
16mm
shutter speed
1/200s
camera make
Canon
camera model
lens model
date
2014-04-18T21:34:47-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(49.15%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.51%)
failure
(-0.37%)
harmonious color
(0.92%)
immersiveness
(0.12%)
interaction
(1.00%)
interesting subject
(32.15%)
intrusive object presence
(-5.83%)
lively color
(-18.85%)
low light
(99.66%)
noise
(-2.78%)
pleasant camera tilt
(-4.04%)
pleasant composition
(-42.24%)
pleasant lighting
(-22.45%)
pleasant pattern
(7.10%)
pleasant perspective
(8.84%)
pleasant post processing
(1.06%)
pleasant reflection
(4.76%)
pleasant symmetry
(0.73%)
sharply focused subject
(1.20%)
tastefully blurred
(-9.34%)
well chosen subject
(-4.54%)
well framed subject
(0.83%)
well timed shot
(21.85%)
all
(1.61%)
* 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.