Photos | Wrestling Match Draws Huge Crowd at Caesars Palace
Hayateumi Hidehito and Jim James face off as a packed house watches on at Caesars Palace in Las Vegas. The bright lighting adds to the excitement of the event.
BLIP-2 Description:
a crowd of people watching a wrestling matchChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
4032w x 3024h - (download 4k)
Usage
Dominant Color:
Location:
speech jim urban building chair speaker footwear loy er hat basketball solo furniture outdoor empowering volleyball contact performance shoe bag james venue hardware camera coat business audience mo logic electronics performer screen sport suit accessories modern monitor recreation handbag pelthopower sports lighting hayateumi hidehito busile game computer sumo crowd volleyball game
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
2019-12-04T21:09:38.533000-08:00
tzoffset
-28800
tzname
GMT-0800
overall
(30.79%)
curation
(50.00%)
highlight visibility
(80.69%)
behavioral
(70.48%)
failure
(-0.39%)
harmonious color
(0.85%)
immersiveness
(0.17%)
interaction
(1.00%)
interesting subject
(-24.82%)
intrusive object presence
(-8.13%)
lively color
(-8.08%)
low light
(39.11%)
noise
(-2.88%)
pleasant camera tilt
(-6.71%)
pleasant composition
(-80.96%)
pleasant lighting
(-50.10%)
pleasant pattern
(5.40%)
pleasant perspective
(4.05%)
pleasant post processing
(1.35%)
pleasant reflection
(-0.07%)
pleasant symmetry
(0.46%)
sharply focused subject
(0.17%)
tastefully blurred
(-12.99%)
well chosen subject
(-4.87%)
well framed subject
(-48.12%)
well timed shot
(20.96%)
all
(-5.49%)
* 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.