Photos | Live Performance by Too Short and Snoop Dogg at Coachella 2012
A captivating moment on stage with Too Short and Snoop Dogg as they light up the crowd at Coachella 2012. The male performer commands attention with the microphone while the audience cheers in excitement.
BLIP-2 Description:
a man on stage with a microphone and a crowd watchingChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
bracelet spotlight urban rock mobile speaker footwear keyboard eos stage arts eecue performing performance shoe art ii glasses indoors too short audience coachella snoop life helmet mark electronics theater dogg jewelry light accessories musical instrument night recreation april spring canon lighting phone concert crowd piano
iso
3200
metering mode
5
aperture
f/2.8
exposure bias
2
focal length
16mm
shutter speed
1/400s
camera make
Canon
camera model
lens model
date
2012-04-15T23:15:14.270000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(36.25%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.44%)
failure
(-1.17%)
harmonious color
(1.48%)
immersiveness
(0.63%)
interaction
(1.00%)
interesting subject
(-34.25%)
intrusive object presence
(-8.79%)
lively color
(-32.10%)
low light
(99.80%)
noise
(-4.35%)
pleasant camera tilt
(-12.59%)
pleasant composition
(-81.79%)
pleasant lighting
(-67.29%)
pleasant pattern
(3.08%)
pleasant perspective
(7.95%)
pleasant post processing
(4.79%)
pleasant reflection
(-2.13%)
pleasant symmetry
(0.68%)
sharply focused subject
(0.05%)
tastefully blurred
(-15.28%)
well chosen subject
(10.76%)
well framed subject
(-45.09%)
well timed shot
(4.82%)
all
(-8.24%)
* 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.