Photos | Urban Transportation Scene
A bustling street filled with cars, motorcycles, and people in an urban metropolis on a sunny day in 2003. License plates, helmets, and alloy wheels can be spotted among the vehicles, while buildings and lampposts line the sidewalk and tarmac path.
BLIP-2 Description:
a street with cars and motorcycles on itChronologically Adjacent
Note: You can also navigate with your arrow keys or swiping.
Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
architecture tony spoke neighborhood urban coupe building lane transportation sidewalk photos/for_dside-defiant-twotokes-tony road outdoor intersection sedan sky tarmac city pole land street twotokes old machine junglescene dside metropolis path helmet tire wheel rekognition_c car vehicle light office utility alloy sports automobile license plate lamppost defiant motorcycle
Detected Text
date
2003-01-25T02:02:33-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(22.80%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.56%)
failure
(-1.00%)
harmonious color
(-3.17%)
immersiveness
(1.78%)
interaction
(1.00%)
interesting subject
(-78.03%)
intrusive object presence
(-16.48%)
lively color
(-13.83%)
low light
(13.04%)
noise
(-6.93%)
pleasant camera tilt
(-14.21%)
pleasant composition
(-80.96%)
pleasant lighting
(-50.63%)
pleasant pattern
(4.64%)
pleasant perspective
(-15.63%)
pleasant post processing
(0.45%)
pleasant reflection
(-5.77%)
pleasant symmetry
(0.49%)
sharply focused subject
(0.10%)
tastefully blurred
(-5.19%)
well chosen subject
(0.89%)
well framed subject
(-56.05%)
well timed shot
(0.20%)
all
(-10.20%)
* 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.