Photos | Wedding Party Poses in Front of Vintage Cars
Gong Byeong-ho and his bride, along with their wedding party, strike a pose in front of classic cars on the lush green land. The men don suits while the women don designer gowns and showcase their flower arrangements and accessories.
BLIP-2 Description:
a man and woman in formal wear standing next to a man and woman in formal wearChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
tie bride necklace formal neighborhood evening plant gown flower flower bouquet tuxedo bridegroom gong byeong-ho arrangement wedding roof transportation tree outdoor sky bag land fashion machine ceremony coat glasses wear car grass vehicle jewelry suit accessories automobile palm dress sonny sonny_wedding handbag
iso
100
metering mode
5
aperture
f/5
focal length
52mm
shutter speed
1/640s
camera make
Canon
camera model
lens model
date
2010-01-31T12:48:10.860000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(59.57%)
curation
(66.53%)
highlight visibility
(5.77%)
behavioral
(90.74%)
failure
(-0.17%)
harmonious color
(2.53%)
immersiveness
(0.44%)
interaction
(1.00%)
interesting subject
(67.53%)
intrusive object presence
(-5.42%)
lively color
(11.71%)
low light
(0.61%)
noise
(-1.61%)
pleasant camera tilt
(1.27%)
pleasant composition
(9.86%)
pleasant lighting
(0.98%)
pleasant pattern
(9.45%)
pleasant perspective
(10.68%)
pleasant post processing
(-1.71%)
pleasant reflection
(-1.75%)
pleasant symmetry
(1.37%)
sharply focused subject
(4.61%)
tastefully blurred
(13.46%)
well chosen subject
(-39.55%)
well framed subject
(57.28%)
well timed shot
(14.10%)
all
(7.96%)
* 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.