Photos | E-Tech Banner at Dominique Ansel's Restaurant
A large e-tech banner hangs from the wooden flooring of Dominique Ansel's bustling cafeteria, showcasing the futuristic interior design and architecture of the building in 2008.
BLIP-2 Description:
a large banner that says e-techChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
3888w x 2592h - (download 4k)
Usage
Dominant Color:
architecture reception cafeteria jeans pants etech_portraits building food footwear open plywood make hat makes restaurant furniture author greet portraits flooring design court etech pm shoe wood bag tuesday hardware desk welcome indoors o'reilly interior 坚 electronics sign hardwood screen dominique ansel table kiosk don't accessories monitor cafe meet can't floor computer shop handbag march
Detected Text
iso
100
metering mode
5
aperture
f/2.8
focal length
24mm
shutter speed
1/100s
camera make
Canon
camera model
lens model
date
2008-03-04T14:31:09-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(34.16%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.48%)
failure
(-0.22%)
harmonious color
(1.32%)
immersiveness
(0.56%)
interaction
(1.00%)
interesting subject
(-43.12%)
intrusive object presence
(-5.18%)
lively color
(-14.93%)
low light
(6.40%)
noise
(-1.54%)
pleasant camera tilt
(-10.52%)
pleasant composition
(-50.54%)
pleasant lighting
(-34.40%)
pleasant pattern
(7.52%)
pleasant perspective
(10.24%)
pleasant post processing
(1.39%)
pleasant reflection
(-5.00%)
pleasant symmetry
(2.10%)
sharply focused subject
(0.27%)
tastefully blurred
(2.49%)
well chosen subject
(-4.61%)
well framed subject
(-24.71%)
well timed shot
(1.78%)
all
(-3.33%)
* 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.