Photos | Shibuya Metropolis at Night
The bustling city street of Shibuya, Tokyo at night illuminates with flashing billboards and bright city lights, creating a captivating urban experience for locals and tourists alike.
BLIP-2 Description:
a city street at night with many people and buildingsChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
Location:
shibuya urban building metropolitan outdoors transportation area road outdoor sky tarmac city traffic mall street japan scoreboard hardware hm metropolis bus life nature rekognition_c billboards sign electronics vehicle screen light shopping monitor night trip downtown lighting nishishinjuku advertisement computer shop crowd
Detected Text
flash fired
true
metering mode
5
aperture
f/2.5
focal length
6mm
shutter speed
1/30s
camera make
CASIO COMPUTER CO.,LTD.
camera model
date
2002-01-07T06:02:45-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(25.95%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.48%)
failure
(-2.12%)
harmonious color
(-4.20%)
immersiveness
(0.42%)
interaction
(1.00%)
interesting subject
(-46.58%)
intrusive object presence
(-3.64%)
lively color
(-14.26%)
low light
(99.90%)
noise
(-30.79%)
pleasant camera tilt
(-13.12%)
pleasant composition
(-68.21%)
pleasant lighting
(-65.43%)
pleasant pattern
(10.60%)
pleasant perspective
(-8.91%)
pleasant post processing
(2.24%)
pleasant reflection
(-2.64%)
pleasant symmetry
(0.90%)
sharply focused subject
(0.22%)
tastefully blurred
(-19.45%)
well chosen subject
(-2.43%)
well framed subject
(-44.07%)
well timed shot
(-4.85%)
all
(-9.98%)
* 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.