Photos | A Fierce Match at Caesars Palace

A crowd of 45 people gather in an urban interior room to watch Willy Fritsch and Hayateumi Hidehito battle it out in a wrestling match, with dynamic lighting adding an exciting atmosphere to the event.
BLIP-2 Description:
a crowd of people watching a wrestling matchMetadata
Capture date:
Original Dimensions:
3024w x 4032h - (download 4k)
Usage
Dominant Color:
Location:
lighting speaker room city urban furniture theater floor hardware screen child tv indoors bag accessories willy fritsch outdoor chair night micinace glasses building footwear architecture crowd club hidehito monitor hayateumi arena concert audience sports interior table sumo boy restaurant venue computer flooring life handbag hall logic casino difforant electronics shoe
iso
400
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
2019-12-04T21:04:12.645000-08:00
tzoffset
-28800
tzname
GMT-0800
overall
(31.84%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.56%)
failure
(-0.61%)
harmonious color
(2.46%)
immersiveness
(0.59%)
interaction
(1.00%)
interesting subject
(-35.03%)
intrusive object presence
(-6.88%)
lively color
(-1.56%)
low light
(20.63%)
noise
(-6.79%)
pleasant camera tilt
(-13.05%)
pleasant composition
(-73.14%)
pleasant lighting
(-38.01%)
pleasant pattern
(13.96%)
pleasant perspective
(-13.70%)
pleasant post processing
(0.55%)
pleasant reflection
(-2.22%)
pleasant symmetry
(0.49%)
sharply focused subject
(0.12%)
tastefully blurred
(-5.64%)
well chosen subject
(-11.54%)
well framed subject
(-60.21%)
well timed shot
(-7.49%)
all
(-7.22%)
* 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.