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
baer formal evening plant gown flower tuxedo footwear bridegroom wedding wristwatch crowd tree outdoor dae sky bag shoe land cloudy hwan fashion ceremony glasses seb la frite wear rekognition_c gretchen grass suit flower arrangement accessories bridesmaid kavya madhavan palm dress sonny sonny_wedding chang bouquet handbag
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.