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:
etech furniture tuesday desk open floor hardwood march hardware jeans screen greet cafe dominique ansel court make indoors wood sign bag accessories meet don't pm pants makes building cafeteria footwear architecture etech_portraits portraits food monitor author shop o'reilly kiosk interior table restaurant computer flooring handbag reception welcome 坚 design can't hat electronics plywood shoe
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.