Photos | Cruising through Tokyo's Urban Metropolis

A sleek red car makes its way down a busy city street lined with towering buildings and colorful billboards, capturing the essence of Tokyo's bustling urban landscape.
BLIP-2 Description:
a red car driving down a city street with tall buildings in the backgroundMetadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
Location:
architecture spoke neighborhood urban coupe building fence transportation area road outdoor akihabara freeway intersection high rise sky tarmac city bag license land street japan machine metropolis tire cityscape wheel billboards sign rekognition_c car vehicle accessories office trip downtown town alloy sports plate automobile nishishinjuku advertisement handbag
metering mode
5
aperture
f/2.5
focal length
6mm
shutter speed
1/1000s
camera make
CASIO COMPUTER CO.,LTD.
camera model
date
2002-01-07T00:01:16-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(35.06%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.65%)
failure
(-0.22%)
harmonious color
(-2.41%)
immersiveness
(1.61%)
interaction
(1.00%)
interesting subject
(-57.71%)
intrusive object presence
(-10.13%)
lively color
(-13.05%)
low light
(2.61%)
noise
(-1.46%)
pleasant camera tilt
(-10.99%)
pleasant composition
(-73.73%)
pleasant lighting
(-55.18%)
pleasant pattern
(4.79%)
pleasant perspective
(7.78%)
pleasant post processing
(2.99%)
pleasant reflection
(-4.42%)
pleasant symmetry
(1.03%)
sharply focused subject
(0.17%)
tastefully blurred
(-2.45%)
well chosen subject
(3.65%)
well framed subject
(-31.69%)
well timed shot
(0.32%)
all
(-6.79%)
* 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.