Photos | Ping Pong Pros

Edward Norton, Dave B, and Jeffrey W strike a pose in front of the ping pong table during a friendly game in Royal Oak, Michigan. The group shows off their casual yet stylish clothing while enjoying some fun recreation time.
BLIP-2 Description:
a group of people posing for a photo in front of a ping pong tableMetadata
Capture date:
Original Dimensions:
5184w x 3456h - (download 4k)
Usage
Location:
architecture ping pong jeans boy pants necklace robert paddle classroom building frame portrait footwear lamp wristwatch hat furniture jacket dave b shoe groupshot pong jeffrey art shirt coat glasses indoors teen shorts school oak sign jewelry sport cancer table accessories room edward norton recreation neal f downtown ping royal photography crowd racket
Detected Text
iso
1600
metering mode
5
aperture
f/2
exposure bias
-0.67
focal length
22mm
shutter speed
1/250s
camera make
Canon
camera model
lens model
date
2014-01-29T10:23:21.330000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(36.60%)
curation
(93.17%)
highlight visibility
(7.65%)
behavioral
(70.65%)
failure
(-0.29%)
harmonious color
(-4.05%)
immersiveness
(0.24%)
interaction
(1.00%)
interesting subject
(50.63%)
intrusive object presence
(-16.28%)
lively color
(-7.60%)
low light
(6.76%)
noise
(-2.69%)
pleasant camera tilt
(-10.82%)
pleasant composition
(-34.64%)
pleasant lighting
(-48.78%)
pleasant pattern
(7.59%)
pleasant perspective
(7.76%)
pleasant post processing
(2.47%)
pleasant reflection
(-1.15%)
pleasant symmetry
(1.00%)
sharply focused subject
(0.27%)
tastefully blurred
(-15.75%)
well chosen subject
(-30.03%)
well framed subject
(25.61%)
well timed shot
(15.60%)
all
(-2.85%)
* 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.