Photos | Thrilling Wrestling Match Draws Massive Crowd at Caesars Palace

Fans eagerly watch as Katayama Shinji faces off against Xu Wei in a fierce wrestling match at Caesars Palace in Las Vegas. The excitement in the air is palpable as 49 enthusiastic spectators gather to witness the intense sports action.
BLIP-2 Description:
a large crowd of people watching a wrestling matchMetadata
Capture date:
Original Dimensions:
4032w x 3024h - (download 4k)
Usage
Dominant Color:
Location:
lighting game wrestling urban furniture nobuyoshi empowerin katayama shinji busig bag accessories er outdoor sport business chair building footwear basketball architecture crowd hanuman beniwal xu peio wei power speech audience sports sumo venue hokutoumi handbag logic modern stage hayateumi hidehito shoe
iso
100
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
2019-12-04T21:09:15.527000-08:00
tzoffset
-28800
tzname
GMT-0800
overall
(31.20%)
curation
(50.00%)
highlight visibility
(80.69%)
behavioral
(70.51%)
failure
(-0.59%)
harmonious color
(1.39%)
immersiveness
(0.37%)
interaction
(1.00%)
interesting subject
(-23.73%)
intrusive object presence
(-16.41%)
lively color
(2.61%)
low light
(39.45%)
noise
(-6.32%)
pleasant camera tilt
(-7.25%)
pleasant composition
(-75.15%)
pleasant lighting
(-34.06%)
pleasant pattern
(8.42%)
pleasant perspective
(3.51%)
pleasant post processing
(0.72%)
pleasant reflection
(-2.05%)
pleasant symmetry
(0.85%)
sharply focused subject
(0.22%)
tastefully blurred
(-7.68%)
well chosen subject
(-5.07%)
well framed subject
(-46.51%)
well timed shot
(12.87%)
all
(-3.84%)
* 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.