Photos | The Dazzling Life of Chinatown

An eclectic urban spectacle, this November 2023 snapshot captures the energetic nightlife of Chinatown. Neon signs flicker against the enchanting architectural backdrop while locals and visitors intermingle amidst cars, walkways, and urban alleyways. Hats, backpacks, and warm coats create a tapestry of city life, creating a scene that's vibrantly alive and thoroughly captivating. This is a moment in the urban kaleidoscope of the city's life, illustrating the captivating interplay of people, architecture, and the bustling rhythm of metropolitan life.
BLIP-2 Description:
a building with a neon signMetadata
Capture date:
Original Dimensions:
4000w x 6000h - (download 4k)
Usage
Dominant Color:
architecture ci pants neighborhood urban building pedestrian outdoors transportation sidewalk hat luggage walkway lamp area restaurant road outdoor sky container city bag balloon tarmac land street machine coat indoors chinatown metropolis path sign backpack vehicle car alley lantern downtown walking canopy town cafe automobile symbol shelter
iso
100
metering mode
5
aperture
f/3.2
focal length
24mm
shutter speed
1/125s
camera make
Canon
camera model
lens model
date
2023-11-26T16:14:40.360000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(45.53%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.90%)
failure
(-0.27%)
harmonious color
(4.62%)
immersiveness
(3.34%)
interaction
(1.00%)
interesting subject
(-33.64%)
intrusive object presence
(-22.05%)
lively color
(7.15%)
low light
(6.03%)
noise
(-0.61%)
pleasant camera tilt
(-6.38%)
pleasant composition
(-61.28%)
pleasant lighting
(-3.43%)
pleasant pattern
(8.18%)
pleasant perspective
(9.81%)
pleasant post processing
(3.85%)
pleasant reflection
(2.84%)
pleasant symmetry
(3.00%)
sharply focused subject
(1.07%)
tastefully blurred
(11.00%)
well chosen subject
(-6.14%)
well framed subject
(-16.42%)
well timed shot
(-0.55%)
all
(1.78%)
* 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.