Photos | December Swing Time by the Waterfront
Captured on a chilly December day in 2023, this heartwarming scene underlines the joy of family outings. In their stylish hats, coat, and jacket, a woman and her child bring an incredible warmth to the cold outdoors. Their smiles are as radiant as the water glistening behind them, showcasing a tranquil waterfront where a canoe lies idle. Their happiness evokes a sentiment we often long for in the heart of winter - warmth, love and togetherness.
BLIP-2 Description:
a woman and a child sitting on a swingChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
3024w x 4032h - (download 4k)
Usage
Dominant Color:
Location:
december canoe activities headgear pants optical leisure fence portrait footwear dagger sweater baby cap equipment rocks outdoors transportation hat jacket boat shoe knife machine coat glasses water waterfront nature sunglasses wheel lake vehicle sport rowboat accessories lori blade sports canoeing knitwear photography smile happy wesley random weapon beanie
iso
50
metering mode
5
aperture
f/2.8
focal length
16mm
latitude
37.54
longitude
-119.92
shutter speed
1/114s
camera make
Apple
camera model
date
2023-12-28T14:00:36.248000-08:00
tzoffset
-28800
tzname
GMT-0800
overall
(66.99%)
curation
(69.03%)
highlight visibility
(82.30%)
behavioral
(90.89%)
failure
(-0.07%)
harmonious color
(8.06%)
immersiveness
(0.37%)
interaction
(4.00%)
interesting subject
(60.84%)
intrusive object presence
(-7.86%)
lively color
(11.27%)
low light
(0.44%)
noise
(-0.90%)
pleasant camera tilt
(0.04%)
pleasant composition
(-14.60%)
pleasant lighting
(38.01%)
pleasant pattern
(2.61%)
pleasant perspective
(13.62%)
pleasant post processing
(4.07%)
pleasant reflection
(0.32%)
pleasant symmetry
(0.78%)
sharply focused subject
(19.31%)
tastefully blurred
(15.45%)
well chosen subject
(-12.43%)
well framed subject
(55.42%)
well timed shot
(26.59%)
all
(14.03%)
* 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,
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