Photos | Wrestling Match at Caesars Palace
A crowd of 32 people gather inside Caesars Palace to watch a wrestling match in Las Vegas. The lighting and urban atmosphere add 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:
3024w x 4032h - (download 4k)
Usage
Location:
architecture activities formal pants urban convention leisure building portrait chair speaker footwear stage hat crowd graduation furniture jacket shopping mall city bag shoe wrestling hardware qin haiyang club coat indoors audience metropolis interior wear electronics theater screen arena sport suit accessories room monitor blazer lighting center tv photography casino concert computer sumo shop handbag dancing
iso
320
metering mode
5
aperture
f/1.8
focal length
4mm
latitude
36.12
longitude
-115.17
shutter speed
1/40s
camera make
Apple
camera model
date
2019-12-04T21:04:04.037000-08:00
tzoffset
-28800
tzname
GMT-0800
overall
(27.93%)
curation
(50.00%)
highlight visibility
(80.69%)
behavioral
(70.61%)
failure
(-2.51%)
harmonious color
(1.22%)
immersiveness
(0.39%)
interaction
(1.00%)
interesting subject
(-36.28%)
intrusive object presence
(-7.18%)
lively color
(-4.00%)
low light
(82.62%)
noise
(-8.84%)
pleasant camera tilt
(-8.52%)
pleasant composition
(-65.23%)
pleasant lighting
(-49.90%)
pleasant pattern
(14.33%)
pleasant perspective
(-10.24%)
pleasant post processing
(0.90%)
pleasant reflection
(-2.24%)
pleasant symmetry
(0.42%)
sharply focused subject
(0.37%)
tastefully blurred
(-26.46%)
well chosen subject
(-46.36%)
well framed subject
(-40.99%)
well timed shot
(-12.59%)
all
(-9.64%)
* 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.