Photos | Young Coffee Connoisseur in San Francisco - October 2023
Caught mid-sip, our youngest family member, who apparently takes after his coffee-loving parents, in a cozy San Francisco café. Candid capture of the adorable everyday moments at our family dinner table amidst an artistic ambiance. – Randoms, October 2023
BLIP-2 Description:
a baby is sitting in a chair with a cup of coffeeMetadata
Capture date:
Original Dimensions:
3024w x 4032h - (download 4k)
Usage
Dominant Color:
Location:
coffee wood restaurant child portrait cutlery glasses randoms latte espresso interior food spoon bowl saucer cafeteria plywood table building luciano pavarotti tableware porcelain october dining table pottery boy room painting dish cafe cup beverage architecture telegraph utensil meal wesley furniture frame photography accessories indoors sitting dining art hill part
iso
1250
metering mode
5
aperture
f/2.2
focal length
2mm
latitude
37.8
longitude
-122.41
shutter speed
1/30s
camera make
Apple
camera model
overall
(28.71%)
curation
(89.28%)
highlight visibility
(7.35%)
behavioral
(70.61%)
failure
(-1.20%)
harmonious color
(-5.60%)
immersiveness
(0.39%)
interaction
(8.00%)
interesting subject
(-7.37%)
intrusive object presence
(-11.60%)
lively color
(-6.70%)
low light
(17.68%)
noise
(-4.32%)
pleasant camera tilt
(-8.50%)
pleasant composition
(-47.02%)
pleasant lighting
(-42.58%)
pleasant pattern
(7.42%)
pleasant perspective
(-17.52%)
pleasant post processing
(-3.22%)
pleasant reflection
(-3.67%)
pleasant symmetry
(0.39%)
sharply focused subject
(0.59%)
tastefully blurred
(-23.30%)
well chosen subject
(-37.82%)
well framed subject
(1.62%)
well timed shot
(-0.71%)
all
(-8.05%)
* 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-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.