Photos | Busy Metropolis Street in Tokyo
A bustling street in the heart of Tokyo's Shinjuku neighborhood during rush hour, with pedestrians, bikes, and vehicles filling the road and towering skyscrapers lining the skyline.
BLIP-2 Description:
a busy city street with many people walking and riding bikesChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
Location:
architecture scooter rise neighborhood urban plant building motor metropolitan pedestrian transportation sidewalk area condo road outdoor sky tarmac city mall land street mixed-use development truck bicycle metropolis path billboards sign moped car vehicle shopping office high downtown walking town housing nishishinjuku photography advertisement shop crowd motorcycle
metering mode
5
aperture
f/2.5
focal length
6mm
shutter speed
1/1250s
camera make
CASIO COMPUTER CO.,LTD.
camera model
date
2002-01-07T23:52:55-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(44.12%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.79%)
failure
(-0.17%)
harmonious color
(-0.45%)
immersiveness
(1.20%)
interaction
(1.00%)
interesting subject
(-28.52%)
intrusive object presence
(-9.91%)
lively color
(5.79%)
low light
(2.20%)
noise
(-3.25%)
pleasant camera tilt
(-8.74%)
pleasant composition
(-67.19%)
pleasant lighting
(-3.23%)
pleasant pattern
(8.45%)
pleasant perspective
(4.39%)
pleasant post processing
(1.84%)
pleasant reflection
(-2.11%)
pleasant symmetry
(0.76%)
sharply focused subject
(0.37%)
tastefully blurred
(-2.68%)
well chosen subject
(0.81%)
well framed subject
(-39.31%)
well timed shot
(-2.08%)
all
(-0.31%)
* NOTE: This image was scaled up from its original size using an AI model called GFP-GAN (Generative Facial Prior), which is a
Generative adversartial network that can be used to repair (or upscale in this case) photos, sometimes the results are a little...
weird.
* 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.