Photos | Culinary Encounter in Korea

In the heart of Seoul in 2024, Guo Peiyuan along with three other men caught up in an authentic Korean restaurant. Engrossed in their delectable meals and in-depth conversation, they encapsulate the essence of urban dining culture. Time stamp: March 21, 2024.
BLIP-2 Description:
a group of men sitting at a table with foodMetadata
Capture date:
Original Dimensions:
6000w x 4000h - (download 4k)
Usage
Dominant Color:
architecture cutlery cafeteria boy spoon tableware bowl building meal food portrait child buffet ring dish dinner restaurant furniture utensil court drinking glass eating television hardware machine indoors lunch dining interior guo peiyuan electronics jewelry screen table accessories room monitor korea cafe plate tv photography cup computer consumer
iso
20000
metering mode
5
aperture
f/2.8
focal length
24mm
shutter speed
1/640s
camera make
Canon
camera model
lens model
date
2024-03-21T04:44:26.090000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(40.26%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.67%)
failure
(-0.17%)
harmonious color
(5.55%)
immersiveness
(0.05%)
interaction
(1.00%)
interesting subject
(-5.34%)
intrusive object presence
(-11.40%)
lively color
(-42.36%)
low light
(35.11%)
noise
(-1.61%)
pleasant camera tilt
(-4.49%)
pleasant composition
(-69.14%)
pleasant lighting
(-48.10%)
pleasant pattern
(1.54%)
pleasant perspective
(12.35%)
pleasant post processing
(2.57%)
pleasant reflection
(-1.40%)
pleasant symmetry
(0.22%)
sharply focused subject
(0.66%)
tastefully blurred
(-25.10%)
well chosen subject
(-37.23%)
well framed subject
(25.78%)
well timed shot
(2.47%)
all
(-7.38%)
* 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.