Photos | Wedding Party in the Garden
Chang Dae-hwan, Kavya Madhavan, Gretchen Baer, and Seb la Frite pose for a photo at Sonny's wedding ceremony on a cloudy day, surrounded by palm trees and lush greenery. The group's formal wear and wedding attire stand out against the blue sky and grassy land in the background.
BLIP-2 Description:
a group of people posing for a photo in the yardChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
gretchen ceremony grass bridesmaid bridegroom seb la frite sonny dress sonny_wedding wear sky plant tree fashion wristwatch formal bag accessories evening gown hwan outdoor kavya madhavan glasses footwear bouquet crowd dae palm suit flower arrangement tuxedo chang handbag rekognition_c baer cloudy land flower wedding shoe
iso
100
metering mode
5
aperture
f/4
focal length
24mm
shutter speed
1/800s
camera make
Canon
camera model
lens model
date
2010-01-31T12:42:28.090000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(49.19%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.65%)
failure
(-0.34%)
harmonious color
(3.13%)
immersiveness
(0.68%)
interaction
(1.00%)
interesting subject
(58.25%)
intrusive object presence
(-26.56%)
lively color
(-6.29%)
low light
(0.93%)
noise
(-2.49%)
pleasant camera tilt
(-1.46%)
pleasant composition
(-28.76%)
pleasant lighting
(-38.16%)
pleasant pattern
(3.54%)
pleasant perspective
(10.07%)
pleasant post processing
(2.93%)
pleasant reflection
(-0.19%)
pleasant symmetry
(0.78%)
sharply focused subject
(0.56%)
tastefully blurred
(-7.21%)
well chosen subject
(-3.68%)
well framed subject
(10.41%)
well timed shot
(26.81%)
all
(2.28%)
* 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.