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:
dish glass activities cutlery beverage photography grass oyster dinner table outdoors alcohol restaurant food plant eating farm party fun drinking mobile dave wine leisure picnic dining diner lori s glasses vineyard tour hat sky couch land utensil furniture building architecture rural optical fork lunch field jewelry equipment outstanding phone portrait countryside tableware meal nature headgear sunglasses hog electronics ring outdoor co brunch plate tabletop room supper indoors accessories island
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.