Photos | Urban Solitude: A Pause in Metropolis
Captured on December 10, 2023, within the bustling heart of Fort Mason, a solitary vehicle takes a moment's respite. Tucked away from the endless city movement, this photo showcases the synchrony of nature and machinery with plant life quietly thriving amidst urban infrastructure. Despite the bustling neighborhood, apartments, and high-rises, a quiet testament to the beauty of stillness in an otherwise hectic metropolis unfolds.
BLIP-2 Description:
a car parked on the side of the roadChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
6000w x 4000h - (download 4k)
Usage
Dominant Color:
tarmac apartment housing path machine mason car wheel wheel city urban calzones intersection drinks vehicle car bumper coupe license plant smoothies high transportation lane downtown area sidewalk pizza window spy tire outdoor street sedan road plate go building slice architecture beer food shop spoke canopy automobile sports pasta awning office alley rise metropolis condo wine land town fort neighborhood alloy
iso
100
metering mode
5
aperture
f/5
focal length
24mm
shutter speed
1/250s
camera make
Canon
camera model
lens model
date
2023-12-10T13:50:20.570000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(50.00%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.48%)
failure
(-0.10%)
harmonious color
(3.18%)
immersiveness
(6.69%)
interaction
(1.00%)
interesting subject
(-30.64%)
intrusive object presence
(-5.15%)
lively color
(0.22%)
low light
(1.03%)
noise
(-0.20%)
pleasant camera tilt
(-1.51%)
pleasant composition
(-16.44%)
pleasant lighting
(18.49%)
pleasant pattern
(10.50%)
pleasant perspective
(32.69%)
pleasant post processing
(-2.07%)
pleasant reflection
(-1.25%)
pleasant symmetry
(6.42%)
sharply focused subject
(1.34%)
tastefully blurred
(1.52%)
well chosen subject
(-0.73%)
well framed subject
(-14.32%)
well timed shot
(-4.92%)
all
(8.10%)
* WARNING: The title and caption of this image were generated by an AI LLM (gpt-4-0613
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.