Photos | Urban Nightlife on Stage at Caesars Palace
Evgeniya Mikhailova, Katayama Shinji, and Hitoshi Saito dazzle the crowd with their clothing and lighting at a basketball game event in Caesars Palace.
BLIP-2 Description:
a group of people standing on a stage in front of a crowdChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
4032w x 3024h - (download 4k)
Usage
Dominant Color:
Location:
architecture speech katayama urban building shinji chair speaker footwear stage er lamp hat basketball furniture outdoor empowering mi shoe bag city party bench venue fun hall business indoors audience mo life logic interior electronics pe theater evgeniya mikhailova sport accessories room modern night handbag sports lighting game towering casino sumo crowd hitoshi saito
iso
200
metering mode
5
aperture
f/1.8
focal length
4mm
latitude
36.12
longitude
-115.17
shutter speed
1/60s
camera make
Apple
camera model
date
2019-12-04T21:09:44.935000-08:00
tzoffset
-28800
tzname
GMT-0800
overall
(31.62%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.56%)
failure
(-0.85%)
harmonious color
(1.58%)
immersiveness
(0.51%)
interaction
(1.00%)
interesting subject
(-16.11%)
intrusive object presence
(-15.97%)
lively color
(-0.55%)
low light
(34.16%)
noise
(-5.83%)
pleasant camera tilt
(-8.86%)
pleasant composition
(-76.95%)
pleasant lighting
(-52.15%)
pleasant pattern
(8.35%)
pleasant perspective
(-0.49%)
pleasant post processing
(-0.31%)
pleasant reflection
(-1.41%)
pleasant symmetry
(1.05%)
sharply focused subject
(0.15%)
tastefully blurred
(-15.12%)
well chosen subject
(-8.15%)
well framed subject
(-55.13%)
well timed shot
(9.28%)
all
(-6.35%)
* 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.