Photos | Nighttime Crowd at Austin Restaurant
Priyanka Vadra joins 28 other people outside a storefront restaurant on a bustling street in Austin. The night sky and city buildings provide a stunning backdrop as the group socializes and waits for a table.
BLIP-2 Description:
a crowd of people standing outside a restaurant at nightChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
architecture beer jeans sexas spoke pants necklace urban building window footwear pedestrian transportation sidewalk wristwatch walkway priyanka vadra cards road outdoor sky shoe bag city land street cruffy's austin cigarettes machine storefront bicycle metropolis path helmet wheel vehicle jewelry sport accessories cycling handbag sour atm phone shil crowd motorcycle sodas
iso
1600
metering mode
5
aperture
f/2.8
focal length
16mm
shutter speed
1/40s
camera make
Canon
camera model
lens model
date
2009-06-13T22:54:35.470000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(24.72%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.67%)
failure
(-0.95%)
harmonious color
(-0.22%)
immersiveness
(0.51%)
interaction
(1.00%)
interesting subject
(-73.63%)
intrusive object presence
(-7.13%)
lively color
(-20.59%)
low light
(99.56%)
noise
(-11.82%)
pleasant camera tilt
(-10.51%)
pleasant composition
(-87.11%)
pleasant lighting
(-63.09%)
pleasant pattern
(3.42%)
pleasant perspective
(-4.05%)
pleasant post processing
(0.78%)
pleasant reflection
(-0.83%)
pleasant symmetry
(0.15%)
sharply focused subject
(0.07%)
tastefully blurred
(-15.36%)
well chosen subject
(5.17%)
well framed subject
(-67.48%)
well timed shot
(-1.58%)
all
(-10.64%)
* 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.