Photos | Dining with Liu Guangbiao
Liu Guangbiao and his companions enjoy a meal at a restaurant in Burbank, California. The table is set with plates, cutlery, and glasses for beer and other beverages.
BLIP-2 Description:
a group of people sitting at a table with plates of foodChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
3024w x 4032h - (download 4k)
Usage
Dominant Color:
Location:
phone brunch coffee plate wood restaurant baby cutlery computer mobile dinner bread court softwar buffet interior food cafeteria liquor snack counter fork hardware drinking table pub lunch building tableware electronics dining table glass bar room breakfast dish drink downtown cafe wristwatch cup screen beverage undershirt architecture hat knife jan beer meal utensil weapon liu guangbiao furniture alcohol blade dining headgear indoors monitor burbank
iso
160
metering mode
5
aperture
f/1.8
focal length
4mm
latitude
34.18
longitude
-118.31
shutter speed
1/60s
camera make
Apple
camera model
lens model
overall
(37.55%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.63%)
failure
(-0.22%)
harmonious color
(2.87%)
immersiveness
(0.12%)
interaction
(1.00%)
interesting subject
(-33.23%)
intrusive object presence
(-11.94%)
lively color
(10.68%)
low light
(5.76%)
noise
(-1.88%)
pleasant camera tilt
(-10.59%)
pleasant composition
(-71.83%)
pleasant lighting
(-28.03%)
pleasant pattern
(12.48%)
pleasant perspective
(3.17%)
pleasant post processing
(2.54%)
pleasant reflection
(-1.90%)
pleasant symmetry
(0.27%)
sharply focused subject
(0.49%)
tastefully blurred
(-5.44%)
well chosen subject
(-27.78%)
well framed subject
(-27.93%)
well timed shot
(-5.29%)
all
(-4.16%)
* 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.