Photos | Wedding Bliss in Front of a Gorgeous Home
Chang Dae-hwan and Gretchen Baer celebrate their special day with 42 loved ones, surrounded by lush greenery, palm trees, and blue skies. The stylish group stuns in their formal wear, with the bride donning a stunning wedding gown and the groom wearing a dapper suit.
BLIP-2 Description:
a group of people posing for a photo in front of a houseChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
tie baer formal evening plant gown footwear tuxedo bridegroom flower wedding transportation crowd tree outdoor sky chang dae-hwan bag shoe land cloudy glove fashion ceremony glasses wear gretchen car grass vehicle suit accessories flower arrangement bridesmaid palm dress sonny sonny_wedding bouquet handbag
iso
100
metering mode
5
aperture
f/4
focal length
24mm
shutter speed
1/1000s
camera make
Canon
camera model
lens model
date
2010-01-31T12:42:37.870000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(52.54%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.66%)
failure
(-0.24%)
harmonious color
(4.93%)
immersiveness
(0.59%)
interaction
(1.00%)
interesting subject
(71.24%)
intrusive object presence
(-18.09%)
lively color
(2.34%)
low light
(0.51%)
noise
(-2.08%)
pleasant camera tilt
(-2.88%)
pleasant composition
(-22.52%)
pleasant lighting
(-25.34%)
pleasant pattern
(4.22%)
pleasant perspective
(7.04%)
pleasant post processing
(2.31%)
pleasant reflection
(1.95%)
pleasant symmetry
(0.61%)
sharply focused subject
(0.63%)
tastefully blurred
(-5.94%)
well chosen subject
(-9.26%)
well framed subject
(13.77%)
well timed shot
(22.23%)
all
(4.02%)
* 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.