Photos | Sunset Supper at Hog Island Oyster Co, 2023
Shared smiles and delicious meals as friends gather for a sunny afternoon feast at Hog Island Oyster Co. [Dave B, Lori S, and others pictured.] Boasting beautiful sunset views over the fields of Marshall, California, this moment truly stands out in the Outstanding in the Field album.
BLIP-2 Description:
a group of people sitting at a table with a sunset in the backgroundChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
4032w x 3024h - (download 4k)
Usage
Dominant Color:
Location:
architecture cutlery glass wine activities headgear tableware lori s optical plant building meal outstanding food portrait mobile oyster leisure brunch ring beverage dish outdoors equipment hat dinner field furniture outdoor restaurant rural utensil sky co party land eating drinking island diner fun hog dave alcohol glasses indoors lunch supper farm tabletop picnic dining nature sunglasses electronics grass fork jewelry table accessories room couch tour countryside plate phone photography vineyard
iso
64
metering mode
5
aperture
f/1.78
focal length
7mm
latitude
38.16
longitude
-122.89
shutter speed
1/121s
camera make
Apple
camera model
date
2023-11-08T16:55:06.384000-08:00
tzoffset
-28800
tzname
GMT-0800
overall
(54.64%)
curation
(71.00%)
highlight visibility
(82.45%)
behavioral
(90.94%)
failure
(-0.07%)
harmonious color
(7.98%)
immersiveness
(0.17%)
interaction
(2.00%)
interesting subject
(47.85%)
intrusive object presence
(-8.84%)
lively color
(-0.99%)
low light
(2.98%)
noise
(-2.39%)
pleasant camera tilt
(-0.61%)
pleasant composition
(-47.95%)
pleasant lighting
(8.31%)
pleasant pattern
(3.66%)
pleasant perspective
(11.43%)
pleasant post processing
(4.15%)
pleasant reflection
(-1.93%)
pleasant symmetry
(0.56%)
sharply focused subject
(3.88%)
tastefully blurred
(2.52%)
well chosen subject
(-19.95%)
well framed subject
(19.41%)
well timed shot
(16.61%)
all
(4.80%)
* WARNING: The title and caption of this image were generated by an AI LLM (gpt-4-0613
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.