Photos | Wedding Reception at a Hawaiian Resort
Giuliano Stroe and Mark B join 24 other guests for an elegant wedding reception in Hawaii. The table is beautifully decorated with linen, flower arrangements, and cutlery. A tree with a flower bouquet adds to the interior room's decor.
BLIP-2 Description:
a group of people sitting around a tableChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
4368w x 2912h - (download 4k)
Usage
Dominant Color:
r fork room furniture dress lenny decor dining weapon wear home tie fun waiting room plant tree linen hawaii court formal indoors bag accessories giuliano stroe knife chair banquet building bouquet architecture crowd food rose suit blade table mobile cutlery bride cup phone restaurant flower arrangement handbag reception hall tablecloth flower electronics wedding
iso
100
metering mode
5
aperture
f/2.8
focal length
16mm
shutter speed
1/25s
camera make
Canon
camera model
lens model
date
2008-03-15T20:14:15-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(45.95%)
curation
(65.87%)
highlight visibility
(5.57%)
behavioral
(70.62%)
failure
(-0.29%)
harmonious color
(4.02%)
immersiveness
(0.63%)
interaction
(1.00%)
interesting subject
(26.68%)
intrusive object presence
(-9.69%)
lively color
(5.13%)
low light
(4.86%)
noise
(-3.37%)
pleasant camera tilt
(-3.45%)
pleasant composition
(-65.43%)
pleasant lighting
(-19.53%)
pleasant pattern
(4.57%)
pleasant perspective
(5.56%)
pleasant post processing
(2.79%)
pleasant reflection
(1.85%)
pleasant symmetry
(0.56%)
sharply focused subject
(2.12%)
tastefully blurred
(10.66%)
well chosen subject
(-30.00%)
well framed subject
(-14.66%)
well timed shot
(14.59%)
all
(-0.41%)
* 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.