Photos | Detour Market Madness
Yumi Matsutoya leads the way as a vibrant crowd navigates through tents and banners in the heart of the city, enjoying the sunny blue skies and artful displays of accessories, hats, backpacks, shoes, and handbags.
BLIP-2 Description:
a crowd of people walking through a street with tentsChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
3504w x 2336h - (download 4k)
Usage
Dominant Color:
architecture headgear boy festiva urban building fall crand footwear des fair fairi pedestrian outdoors fine hat tent restaurant outdoor stron balloon sky bag shoe city ml art detour strong avenue negative blue glasses indoors teen metropolis banner sign backpack light accessories bazaar market handbag october yumi matsutoya shop crowd apple bis shelter
iso
400
metering mode
5
aperture
f/4.5
exposure bias
0.5
focal length
17mm
shutter speed
1/1250s
camera make
Canon
camera model
lens model
date
2006-10-07T15:37:36-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(23.19%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.76%)
failure
(-0.39%)
harmonious color
(0.99%)
immersiveness
(0.20%)
interaction
(1.00%)
interesting subject
(-60.69%)
intrusive object presence
(-42.02%)
lively color
(-9.92%)
low light
(5.59%)
noise
(-2.42%)
pleasant camera tilt
(-13.24%)
pleasant composition
(-95.61%)
pleasant lighting
(-56.64%)
pleasant pattern
(3.34%)
pleasant perspective
(-7.46%)
pleasant post processing
(3.84%)
pleasant reflection
(-2.19%)
pleasant symmetry
(0.34%)
sharply focused subject
(0.10%)
tastefully blurred
(-14.28%)
well chosen subject
(14.40%)
well framed subject
(-73.58%)
well timed shot
(3.90%)
all
(-9.50%)
* 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.