Photos | Urban Romance: Night Serenity in Downtown Sonoma

Dave B and a companion stand before a church, the nightlife of downtown Sonoma reflected in the urban scene behind them. The arch of the church and the city's architecture are highlighted by the perfect balance of nature and machine, making the captured moment emblematic of the lively city-life. The glow from the street lamps bathes the path beneath their feet, lending a warmth to the cool November night in 2023.
BLIP-2 Description:
a man and woman standing in front of a church at nightMetadata
Capture date:
Original Dimensions:
6000w x 4000h - (download 4k)
Usage
Dominant Color:
architecture scooter tool pants spoke crypt handrail arch urban plant sonoma building wall window footwear flare outdoors transportation hat cobblestone walkway romantic road jacket tarmac city bag shoe street machine dave hall coat bicycle tire path shrub nature wheel car vehicle alley sport light accessories night downtown cycling darkness walking alloy lighting kissing stroller photography handbag tunnel motorcycle
iso
25600
metering mode
5
aperture
f/2.8
focal length
24mm
shutter speed
1/250s
camera make
Canon
camera model
lens model
date
2023-11-25T17:38:29.960000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(41.04%)
curation
(65.00%)
highlight visibility
(5.65%)
behavioral
(90.76%)
failure
(-1.17%)
harmonious color
(3.92%)
immersiveness
(1.32%)
interaction
(1.00%)
interesting subject
(-9.81%)
intrusive object presence
(-9.45%)
lively color
(-41.41%)
low light
(99.85%)
noise
(-5.44%)
pleasant camera tilt
(-1.35%)
pleasant composition
(-38.23%)
pleasant lighting
(-45.46%)
pleasant pattern
(4.35%)
pleasant perspective
(5.29%)
pleasant post processing
(-3.29%)
pleasant reflection
(0.13%)
pleasant symmetry
(3.00%)
sharply focused subject
(0.66%)
tastefully blurred
(-10.35%)
well chosen subject
(-5.49%)
well framed subject
(13.09%)
well timed shot
(12.87%)
all
(-3.36%)
* 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.