Photos | Wedding Ceremony of Emmanuelle and Wickstrom
Emmanuelle Mignon and Wickstrom are all set to tie the knot in front of their loved ones as they stand on the stage amid beautiful flower arrangements and a perfect seating arrangement.
BLIP-2 Description:
a man and woman standing in front of a crowdChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
tie activities bride formal evening wickstrom_wedding plant leisure chair gown flower footwear tuxedo arrangement stage wedding microphone hat furniture dave b flooring emmanuelle mignon wood shoe bag wickstrom art fashion ceremony glasses indoors wear hardwood table suit flower arrangement accessories handbag lighting device dress floor bouquet crowd dancing electrical
iso
3200
metering mode
5
aperture
f/2.8
focal length
70mm
shutter speed
1/40s
camera make
Canon
camera model
lens model
date
2011-10-29T19:27:06.050000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(38.31%)
curation
(65.32%)
highlight visibility
(5.53%)
behavioral
(70.57%)
failure
(-0.49%)
harmonious color
(0.59%)
immersiveness
(0.05%)
interaction
(1.00%)
interesting subject
(17.82%)
intrusive object presence
(-25.02%)
lively color
(-36.38%)
low light
(84.18%)
noise
(-1.93%)
pleasant camera tilt
(-3.40%)
pleasant composition
(-81.59%)
pleasant lighting
(-42.94%)
pleasant pattern
(2.34%)
pleasant perspective
(3.78%)
pleasant post processing
(-4.44%)
pleasant reflection
(2.08%)
pleasant symmetry
(0.27%)
sharply focused subject
(0.51%)
tastefully blurred
(-26.56%)
well chosen subject
(-6.62%)
well framed subject
(-12.48%)
well timed shot
(32.15%)
all
(-5.25%)
* 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.