Photos | Wedding Party
Gong Byeong-ho, Guo Yan, Gretchen Baer, and Stefano Bandecchi are all smiles as they pose for a photo in front of the beautiful wedding venue on a cloudy day in 2010. The group is dressed in their finest formal wear for the special occasion.
BLIP-2 Description:
a group of people posing for a photo in front of a houseChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
tie baer bride formal sonny l gong ho evening plant guo yan gown footwear flower tuxedo bridegroom wedding transportation hat crowd tree outdoor sky bag shoe stefano bandecchi land cloudy fashion ceremony coat glasses wear rekognition_c gretchen car grass vehicle suit accessories flower arrangement bridesmaid groom byeong palm dress sonny sonny_wedding bouquet handbag
iso
100
metering mode
5
aperture
f/4
focal length
30mm
shutter speed
1/1000s
camera make
Canon
camera model
lens model
date
2010-01-31T12:44:21.310000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(39.82%)
curation
(66.33%)
highlight visibility
(5.60%)
behavioral
(70.68%)
failure
(-0.44%)
harmonious color
(0.37%)
immersiveness
(0.29%)
interaction
(1.00%)
interesting subject
(25.98%)
intrusive object presence
(-26.83%)
lively color
(-2.10%)
low light
(0.68%)
noise
(-3.20%)
pleasant camera tilt
(-5.20%)
pleasant composition
(-57.28%)
pleasant lighting
(-29.61%)
pleasant pattern
(4.76%)
pleasant perspective
(4.72%)
pleasant post processing
(-0.45%)
pleasant reflection
(2.06%)
pleasant symmetry
(0.39%)
sharply focused subject
(0.56%)
tastefully blurred
(-7.43%)
well chosen subject
(-7.86%)
well framed subject
(-13.16%)
well timed shot
(16.80%)
all
(-1.32%)
* 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.