Photos | Vibrant Lantern Lit Streets of Urban Chinatown
This photograph, taken on November 26, 2023, captures a dynamic city scene with a large building adorned with charming red and white lanterns in Chinatown. Featured prominently is Jeremiah J strolling amongst bustling urban life, forward-looking architecture, and vibrant streetlights. The array of vehicles, including e-scooters and cars, adds a modern edge to this vivid illustration of city life.
BLIP-2 Description:
a large building with red and white lanternsChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
4000w x 6000h - (download 4k)
Usage
Dominant Color:
tarmac kjemwelry path machine walkway car wheel wheel city urban chinatown intersection vehicle car license lamp sky bicycle transportation storefront lane area handrail sidewalk tire window sedan parking outdoor street jewelry road plate lantern building footwear architecture 名 spoke automobile k office light 公 metropolis coat 来 lot 資 pedestrian scooter balloon rekognition_c cloudy land town jeremiah motorcycle neighborhood alloy shoe
iso
160
metering mode
5
aperture
f/3.2
focal length
24mm
shutter speed
1/250s
camera make
Canon
camera model
lens model
date
2023-11-26T16:24:24.700000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(43.16%)
curation
(65.00%)
highlight visibility
(5.50%)
behavioral
(70.63%)
failure
(-0.22%)
harmonious color
(4.13%)
immersiveness
(3.49%)
interaction
(1.00%)
interesting subject
(-54.30%)
intrusive object presence
(-5.44%)
lively color
(-10.38%)
low light
(9.08%)
noise
(-0.51%)
pleasant camera tilt
(-6.87%)
pleasant composition
(-56.10%)
pleasant lighting
(-14.16%)
pleasant pattern
(10.94%)
pleasant perspective
(14.70%)
pleasant post processing
(5.60%)
pleasant reflection
(2.93%)
pleasant symmetry
(1.17%)
sharply focused subject
(0.34%)
tastefully blurred
(3.06%)
well chosen subject
(1.94%)
well framed subject
(-37.89%)
well timed shot
(2.37%)
all
(0.97%)
* 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,
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