Photos | Sunset Serenity at Marshall

Dave B and Lori S, a charismatic duo, bask in the golden sunset of November 8, 2023. Clad comfortably in their jackets, sweaters, and accessories, they pose together amidst the lush grass and breathtaking sunset on the coast of Marshall, California. Their smiling faces reflect the pure joy and contentment of a beautiful day spent at the Hog Island Oyster Co. Comfort, style, and nature perfectly converge in this captivating portrait, capturing a timeless moment of happiness and tranquility.
BLIP-2 Description:
a man and woman are posing for a photo at sunsetMetadata
Capture date:
Original Dimensions:
4284w x 5712h - (download 4k)
Usage
Dominant Color:
Location:
scenery jacket knitwear cap grass outdoors furniture eyeglasses dave lori s coast sky happy sea sweatshirt hoodie wristwatch accessories bag equipment photography outdoor sun chair sunglasses optical beach glasses selfie sunrise co water hugging oyster portrait sweater outstanding hog handbag sunset land island hat shoreline smile scarf nature field coat
iso
100
metering mode
5
aperture
f/1.78
focal length
7mm
latitude
38.16
longitude
-122.89
shutter speed
1/149s
camera make
Apple
camera model
date
2023-11-08T16:55:36.703000-08:00
tzoffset
-28800
tzname
GMT-0800
overall
(72.56%)
curation
(68.87%)
highlight visibility
(5.95%)
behavioral
(90.91%)
failure
(-0.10%)
harmonious color
(10.35%)
immersiveness
(0.37%)
interaction
(4.00%)
interesting subject
(76.32%)
intrusive object presence
(-3.00%)
lively color
(8.12%)
low light
(3.74%)
noise
(-1.34%)
pleasant camera tilt
(1.72%)
pleasant composition
(26.59%)
pleasant lighting
(21.01%)
pleasant pattern
(2.88%)
pleasant perspective
(4.77%)
pleasant post processing
(8.47%)
pleasant reflection
(-6.48%)
pleasant symmetry
(0.51%)
sharply focused subject
(24.05%)
tastefully blurred
(24.00%)
well chosen subject
(31.30%)
well framed subject
(69.73%)
well timed shot
(49.17%)
all
(19.03%)
* 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.