Photos | Wedding Dinner with Flower Arrangements
Snorri Helgason, Aaron A, Dustin B, Melissa, and Mandy B sit at a beautifully decorated dining table surrounded by flower arrangements during a wedding reception in Hawaii.
BLIP-2 Description:
a group of people sitting around a tableMetadata
Capture date:
Original Dimensions:
4368w x 2912h - (download 4k)
Usage
Dominant Color:
accessories restaurant architecture waiting room land plant table cutlery shoe food march ml formal flower suit handbag teylor wear bride wedding helgason couch dress canon fork evening necklace interior banquet decor teylor d spoon knife furniture indoors flower arrangement linen glass chair room mandy spring tablecloth court building apple bowen arrangement blade fashion snorri weapon dichiara reception celebration tie footwear meal eos art rekognition_c home bag outdoor gown hawaii dustin jewelry bracelet dining bouquet
iso
100
metering mode
5
aperture
f/2.8
focal length
16mm
shutter speed
1/30s
camera make
Canon
camera model
lens model
overall
(41.58%)
curation
(68.64%)
highlight visibility
(5.78%)
behavioral
(70.70%)
failure
(-0.20%)
harmonious color
(4.74%)
immersiveness
(0.17%)
interaction
(1.00%)
interesting subject
(8.18%)
intrusive object presence
(-29.64%)
lively color
(-5.28%)
low light
(13.28%)
noise
(-1.56%)
pleasant camera tilt
(-8.53%)
pleasant composition
(-75.39%)
pleasant lighting
(-34.13%)
pleasant pattern
(4.27%)
pleasant perspective
(3.65%)
pleasant post processing
(5.79%)
pleasant reflection
(0.47%)
pleasant symmetry
(0.54%)
sharply focused subject
(1.03%)
tastefully blurred
(-1.18%)
well chosen subject
(-29.76%)
well framed subject
(-17.66%)
well timed shot
(6.65%)
all
(-4.08%)
* 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 with AI (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.