Photos | A Convivial Gathering in Seoul
Yang Yongliang and friends come together for a delightful meal amidst the bustling Seoul cityscape. This snapshot from March 2024 captures their shared joy at the dining table, infused with the vibrant energy of urban life. Each plate tells a story, creating a tapestry of conversation, friendship, and gastronomical delights.
BLIP-2 Description:
a group of people sitting at a table with plates of foodChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
4284w x 5712h - (download 4k)
Usage
Dominant Color:
urban phone brunch wood plate restaurant child glasses randoms mobile window court march interior food bowl cafeteria gu table building lunch songpa tableware electronics boy room breakfast dish wristwatch tabletop architecture meal utensil yang yongliang furniture accessories dining indoors bangi dong
iso
200
metering mode
5
aperture
f/1.78
focal length
7mm
latitude
37.52
longitude
127.11
shutter speed
1/120s
camera make
Apple
camera model
overall
(33.74%)
curation
(75.00%)
highlight visibility
(5.73%)
behavioral
(70.57%)
failure
(-0.32%)
harmonious color
(1.37%)
immersiveness
(0.24%)
interaction
(2.00%)
interesting subject
(-17.09%)
intrusive object presence
(-12.28%)
lively color
(-5.57%)
low light
(5.79%)
noise
(-3.91%)
pleasant camera tilt
(-11.24%)
pleasant composition
(-60.55%)
pleasant lighting
(-36.30%)
pleasant pattern
(10.82%)
pleasant perspective
(-4.31%)
pleasant post processing
(2.17%)
pleasant reflection
(-3.28%)
pleasant symmetry
(0.27%)
sharply focused subject
(0.51%)
tastefully blurred
(-15.00%)
well chosen subject
(-33.96%)
well framed subject
(-22.13%)
well timed shot
(-2.35%)
all
(-6.04%)
* 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-4-0613
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.