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:
architecture scooter spoke neighborhood handrail urban 資 building jeremiah kjemwelry window footwear lane pedestrian lamp transportation sidewalk area walkway road outdoor k 来 intersection sedan sky tarmac city shoe balloon license land street 名 machine storefront coat parking chinatown bicycle metropolis path tire wheel rekognition_c car vehicle jewelry lantern light office town alloy 公 lot plate automobile cloudy motorcycle car wheel
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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