Photos | Coachella 2016 Crowd Goes Wild
Mary Hayashi, Sandra Aguilar, Finn Cole, and Len Pascoe join the crowd at the 2016 Coachella music festival, their hands in the air as they dance to the sounds of the performance.
BLIP-2 Description:
a crowd of people at a concert with their hands upChronologically Adjacent
Note: You can also navigate with your arrow keys or swiping.
Metadata
Capture date:
Original Dimensions:
5760w x 3840h - (download 4k)
Usage
Dominant Color:
sandra aguilar bracelet sunday necklace cole spotlight urban rock len pascoe mobile baby stage arts hat wristwatch performing performance party art fun club glasses coachella audience life interior rekognition_c electronics finn jewelry light hayashi accessories nightclub room night recreation mary lighting phone concert crowd
iso
1600
metering mode
5
aperture
f/2.8
exposure bias
1
focal length
16mm
shutter speed
1/320s
camera make
Canon
camera model
lens model
date
2016-04-17T18:11:32.230000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(42.38%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.32%)
failure
(-0.66%)
harmonious color
(0.67%)
immersiveness
(0.24%)
interaction
(1.00%)
interesting subject
(9.53%)
intrusive object presence
(-9.42%)
lively color
(-38.57%)
low light
(99.46%)
noise
(-1.44%)
pleasant camera tilt
(-11.80%)
pleasant composition
(-63.23%)
pleasant lighting
(-56.15%)
pleasant pattern
(8.84%)
pleasant perspective
(7.00%)
pleasant post processing
(-2.28%)
pleasant reflection
(-6.41%)
pleasant symmetry
(1.17%)
sharply focused subject
(0.22%)
tastefully blurred
(-16.09%)
well chosen subject
(-7.86%)
well framed subject
(-18.54%)
well timed shot
(26.32%)
all
(-5.34%)
* 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.