Photos | Dining with Distinguished Guests
John XXIII and Christian Sprenger join a group of 32 others for a delicious meal at a restaurant in 2008. The table is set with cutlery, glasses, and accessories, while stunning artwork hangs on the walls in the background.
BLIP-2 Description:
a group of people sitting around a table with foodChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
4368w x 2912h - (download 4k)
Usage
Dominant Color:
sprenger spoon buffet one room couch prayer urban furniture decor floor still dining weapon home lamp cafe linen court wristwatch john xxiii indoors accessories knife pub secure plate glasses building cafeteria architecture church grab food blade table dining table dinner painting cutlery cup still_secure restaurant christian meal flooring headgear altar hat art
iso
1600
metering mode
5
aperture
f/2.8
focal length
16mm
shutter speed
1/160s
camera make
Canon
camera model
lens model
date
2008-08-09T21:46:27-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(38.28%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.66%)
failure
(-0.34%)
harmonious color
(-2.39%)
immersiveness
(0.15%)
interaction
(1.00%)
interesting subject
(-0.87%)
intrusive object presence
(-9.40%)
lively color
(-36.87%)
low light
(87.06%)
noise
(-2.59%)
pleasant camera tilt
(-6.68%)
pleasant composition
(-55.47%)
pleasant lighting
(-53.17%)
pleasant pattern
(11.16%)
pleasant perspective
(8.37%)
pleasant post processing
(-1.09%)
pleasant reflection
(0.85%)
pleasant symmetry
(1.68%)
sharply focused subject
(0.59%)
tastefully blurred
(-3.96%)
well chosen subject
(-8.48%)
well framed subject
(-9.02%)
well timed shot
(13.06%)
all
(-5.36%)
* 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.