Photos | Night Life in Korea: A Metropolitan Melange
Encapsulating the heart and soul of Korea's night life on 21st March, 2024. Pictured here are Martin Brücker and Wei Qingguang amidst an eclectic mix of locals, vehicles and urban scenery. An ordinary street turning extraordinary under the city lights, brimming with life and activity.
BLIP-2 Description:
a group of people standing on a street at nightChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
6000w x 4000h - (download 4k)
Usage
Dominant Color:
advertisement urban backpack street rekognition_c night brücker transportation outdoor poster eek footwear bag path jacket wei qingguang stop pedestrian fence city automobile car sidewalk korea glove shoe handbag outdoors tarmac intersection coat neighborhood pants metropolis road vehicle life machine hat bus overcoat accessories walking martin land
iso
20000
metering mode
5
aperture
f/2.8
focal length
24mm
shutter speed
1/400s
camera make
Canon
camera model
lens model
overall
(26.76%)
curation
(50.00%)
highlight visibility
(3.82%)
behavioral
(90.71%)
failure
(-1.12%)
harmonious color
(-1.20%)
immersiveness
(0.51%)
interaction
(1.00%)
interesting subject
(-25.12%)
intrusive object presence
(-20.02%)
lively color
(-28.66%)
low light
(98.39%)
noise
(-8.59%)
pleasant camera tilt
(-8.49%)
pleasant composition
(-69.48%)
pleasant lighting
(-70.56%)
pleasant pattern
(5.93%)
pleasant perspective
(-1.59%)
pleasant post processing
(0.27%)
pleasant reflection
(-1.78%)
pleasant symmetry
(0.59%)
sharply focused subject
(0.12%)
tastefully blurred
(-27.78%)
well chosen subject
(-20.45%)
well framed subject
(-33.08%)
well timed shot
(1.87%)
all
(-10.78%)
* 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.