Photos | Busy Market Scene in China Town
Huh Young-Sook, Siti Hasmah Mohamad Ali, and Sinta Nuriyah join the crowds of locals and tourists in a bustling market filled with colorful produce, accessories, and other goods.
BLIP-2 Description:
a group of people in a market areaChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
4368w x 2912h - (download 4k)
Usage
Dominant Color:
supermarket building food cable footwear marketplace transportation lamp hat eecue mohamad outdoor 星島 hasmah container bag shoe convenience fashion grocery hardware siti shelf glasses indoors 阿 interior shop interior 親善 vegetable electronics sign car vehicle screen huh young-sook chinaown accessories room monitor store bazaar market plate sinta nuriyah ali computer produce deli shop handbag 小姐
iso
100
metering mode
5
aperture
f/8
exposure bias
-2
focal length
24mm
shutter speed
1/50s
camera make
Canon
camera model
lens model
date
2007-01-16T13:25:45-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(21.52%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.36%)
failure
(-2.10%)
harmonious color
(-0.70%)
immersiveness
(0.42%)
interaction
(1.00%)
interesting subject
(-71.88%)
intrusive object presence
(-9.23%)
lively color
(-20.24%)
low light
(98.73%)
noise
(-9.16%)
pleasant camera tilt
(-15.95%)
pleasant composition
(-83.15%)
pleasant lighting
(-61.72%)
pleasant pattern
(5.52%)
pleasant perspective
(-2.17%)
pleasant post processing
(1.88%)
pleasant reflection
(-6.13%)
pleasant symmetry
(0.59%)
sharply focused subject
(0.10%)
tastefully blurred
(-31.45%)
well chosen subject
(5.91%)
well framed subject
(-65.77%)
well timed shot
(-5.29%)
all
(-10.91%)
* 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.