Photos | Night Walk in the Austin Metropolis
Alisa Camplin, Natalie Geisenberger, and Takeshi Yamasaki join a bustling crowd walking down a brightly lit street in the heart of Austin. The city's urban charm and vibrant night life are on full display amidst the sea of people and high-rise buildings.
BLIP-2 Description:
a crowd of people are walking down a street at nightChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
bracelet urban geisenberger footwear festival pedestrian outdoors hat luggage crowd road outdoor pet sky container city shoe bag land natalie street austin dog takeshi yamasaki glasses shorts audience metropolis alisa camplin life nature canine jewelry accessories high night heel part mammal back animal concert handbag
iso
3200
metering mode
5
aperture
f/2.8
focal length
16mm
shutter speed
1/25s
camera make
Canon
camera model
lens model
date
2009-06-13T23:26:45.180000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(27.54%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.79%)
failure
(-1.54%)
harmonious color
(-2.25%)
immersiveness
(0.42%)
interaction
(1.00%)
interesting subject
(-28.86%)
intrusive object presence
(-8.79%)
lively color
(-26.81%)
low light
(98.58%)
noise
(-7.93%)
pleasant camera tilt
(-7.34%)
pleasant composition
(-80.91%)
pleasant lighting
(-53.37%)
pleasant pattern
(5.32%)
pleasant perspective
(2.98%)
pleasant post processing
(2.80%)
pleasant reflection
(0.75%)
pleasant symmetry
(0.29%)
sharply focused subject
(0.22%)
tastefully blurred
(-32.10%)
well chosen subject
(1.42%)
well framed subject
(-55.66%)
well timed shot
(-3.90%)
all
(-9.09%)
* NOTE: Amazon Rekognition
detected a celebrity in this image using the
Celebrity Recognition API. The API isn't perfect, but it does give you the MatchConfidence which I display
next to the celebrity's name along with links _↗ to their info.
* WARNING: The title and caption of this image were generated by an AI LLM (gpt-3.5-turbo-0301
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.