Photos | Nancy's Cozy Bedroom
Nancy Spungen's bedroom in San Francisco featuring her comfy bed, decorative rug, and colorful art pieces. A TV and indoor plant add extra coziness to the room, while the sliding door provides access to a view of the city.
BLIP-2 Description:
a bedroom with a bed and a tv in itChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
3024w x 4032h - (download 4k)
Usage
Dominant Color:
Location:
architecture civic tool door interior room pillow plant building nancy spungen housewares bedroom furniture rug house pet flooring design container art dog toilet hardware indoors interior canine electronics dorm living room screen sink room sink faucet monitor bed sliding corner housing home center decor mammal dressing animal floor bathroom bedding computer painting
iso
200
metering mode
5
aperture
f/1.6
focal length
5mm
latitude
37.78
longitude
-122.42
shutter speed
1/42s
camera make
Apple
camera model
date
2020-11-27T20:43:24.549000-08:00
tzoffset
-28800
tzname
GMT-0800
overall
(20.50%)
curation
(50.00%)
highlight visibility
(2.45%)
behavioral
(70.47%)
failure
(-0.39%)
harmonious color
(1.50%)
immersiveness
(1.81%)
interaction
(1.00%)
interesting subject
(-69.78%)
intrusive object presence
(-9.91%)
lively color
(-9.84%)
low light
(2.81%)
noise
(-3.98%)
pleasant camera tilt
(-20.84%)
pleasant composition
(-76.56%)
pleasant lighting
(-39.33%)
pleasant pattern
(3.81%)
pleasant perspective
(-15.67%)
pleasant post processing
(2.67%)
pleasant reflection
(-12.71%)
pleasant symmetry
(0.51%)
sharply focused subject
(0.12%)
tastefully blurred
(-1.61%)
well chosen subject
(-4.86%)
well framed subject
(-48.75%)
well timed shot
(5.15%)
all
(-8.72%)
* 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.