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:
ceremony gong byeong-ho machine grass bridegroom sonny dress sonny_wedding wear vehicle car tie sky plant tree fashion transportation formal accessories bag evening gown outdoor roof jewelry arrangement glasses necklace flower bouquet automobile palm suit bride tuxedo handbag land flower neighborhood wedding coat
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.