Photos | Wedding Party Posing in Front of Palm Tree House

Chang Dae-hwan's wedding party poses for a group photo in front of a beautiful palm tree house, dressed in stunning wedding gowns and suits. The blue sky and cloudy background make for a perfect outdoor wedding ceremony.
BLIP-2 Description:
a group of people posing for a photo in front of a houseMetadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
bride formal celebration evening plant chair gown footwear tuxedo flower bridegroom eos wedding outdoors transportation tree furniture outdoor sky chang dae-hwan bag shoe land cloudy ii fashion ceremony glasses january winter mark wear car grass vehicle suit accessories flower arrangement bridesmaid handbag walking canon groom palm sonny blue sky sonny_wedding dress bouquet crowd
iso
100
metering mode
5
aperture
f/4
focal length
24mm
shutter speed
1/800s
camera make
Canon
camera model
lens model
date
2010-01-31T12:42:00.630000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(38.70%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.67%)
failure
(-0.42%)
harmonious color
(2.08%)
immersiveness
(0.73%)
interaction
(1.00%)
interesting subject
(12.38%)
intrusive object presence
(-26.22%)
lively color
(-2.16%)
low light
(0.81%)
noise
(-2.25%)
pleasant camera tilt
(-2.94%)
pleasant composition
(-61.57%)
pleasant lighting
(-39.62%)
pleasant pattern
(4.25%)
pleasant perspective
(4.09%)
pleasant post processing
(2.49%)
pleasant reflection
(2.88%)
pleasant symmetry
(0.56%)
sharply focused subject
(0.37%)
tastefully blurred
(-11.94%)
well chosen subject
(-14.73%)
well framed subject
(-29.27%)
well timed shot
(16.61%)
all
(-2.49%)
* 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.