Photos | Dining at the Restaurant
Gzuz, Justin M, and Kevin H enjoy a meal with friends and family at a restaurant in 2017. The table is set with tableware, utensils, and drinking glasses as the group gathers around to share a meal together.
BLIP-2 Description:
a group of people sitting around a table eating foodChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
4032w x 3024h - (download 4k)
Usage
Dominant Color:
justin buffet room drinking urban furniture eating container dining bread dining room wear fun glass court wristwatch gzuz formal indoors accessories bag beverage lunch jewelry pub dish plate glasses footwear cafeteria building architecture food kevin h counter utensil suit party table bar interior dinner cup alcohol restaurant meal handbag bracelet tableware shoe
iso
80
metering mode
5
aperture
f/1.8
focal length
4mm
shutter speed
1/6s
camera make
Apple
camera model
lens model
date
2017-12-15T20:09:26.051000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(23.95%)
curation
(70.65%)
highlight visibility
(5.93%)
behavioral
(70.65%)
failure
(-0.93%)
harmonious color
(-3.78%)
immersiveness
(0.20%)
interaction
(4.00%)
interesting subject
(-32.74%)
intrusive object presence
(-20.92%)
lively color
(0.74%)
low light
(23.93%)
noise
(-4.39%)
pleasant camera tilt
(-7.51%)
pleasant composition
(-78.71%)
pleasant lighting
(-52.10%)
pleasant pattern
(4.93%)
pleasant perspective
(-22.95%)
pleasant post processing
(-4.53%)
pleasant reflection
(-1.47%)
pleasant symmetry
(0.07%)
sharply focused subject
(0.34%)
tastefully blurred
(-16.58%)
well chosen subject
(-32.74%)
well framed subject
(-62.01%)
well timed shot
(-12.77%)
all
(-12.33%)
* 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.