Photos | Sumo Wrestling Competition at Caesars Palace Magic Kingdom
Hayateumi Hidehito, Hokutoumi Nobuyoshi, Kong Qingdong, Hugh Dillon, and Yoshitomo Tani participate in a thrilling shoving match during the 2019 Sumo Wrestling Tournament at Caesars Palace in Las Vegas. The crowd watches in awe as the athletes showcase their strength and technique.
BLIP-2 Description:
sumo wrestling tournament at the magic kingdomMetadata
Capture date:
Original Dimensions:
4032w x 3024h - (download 4k)
Usage
Dominant Color:
Location:
pc rekognition_c recreation phone tani glasses baby mobile hugh dillon footwear nologic bag yoshitomo sumo hayateumi shoving uniform chair wrestling hokutoumi nobuyoshi sports kong hardware hidehito sign electronics shoe glove handbag contact screen speaker hat sport qingdong furniture accessories laptop monitor computer crowd
Detected Text
iso
80
metering mode
5
aperture
f/2
focal length
6mm
latitude
36.12
longitude
-115.17
shutter speed
1/60s
camera make
Apple
camera model
lens model
overall
(36.62%)
curation
(50.00%)
highlight visibility
(80.69%)
behavioral
(70.40%)
failure
(-0.49%)
harmonious color
(1.93%)
immersiveness
(0.05%)
interaction
(1.00%)
interesting subject
(13.57%)
intrusive object presence
(-15.89%)
lively color
(-3.47%)
low light
(68.85%)
noise
(-4.59%)
pleasant camera tilt
(-4.90%)
pleasant composition
(-54.25%)
pleasant lighting
(-39.45%)
pleasant pattern
(4.37%)
pleasant perspective
(12.02%)
pleasant post processing
(4.65%)
pleasant reflection
(-2.02%)
pleasant symmetry
(0.29%)
sharply focused subject
(0.24%)
tastefully blurred
(-17.02%)
well chosen subject
(-42.19%)
well framed subject
(4.15%)
well timed shot
(23.05%)
all
(-2.35%)
* 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.