Photos | Culinary Delights in Chinatown: A Family Affair
Rosie Duffield and little Wesley share a special meal in a bustling Chinatown cafe, filled with the rich aroma of food and coffee. Amid the animated chatter and clatter of cutlery, they create memories over delicious bites. (November 2023)
BLIP-2 Description:
a woman and child sitting at a table with foodMetadata
Capture date:
Original Dimensions:
6000w x 4000h - (download 4k)
Usage
Dominant Color:
phone wood coffee jeans ring restaurant baby cutlery glasses transportation mobile rosie duffield footwear body part yau court interior food spoon cafeteria saucer equipment optical chan fork jewelry car jug drinking table tableware shoe electronics pottery stroller michaela shaker glass room pants plant cafe cup vehicle beverage machine hat sunglasses utensil meal bottle wesley furniture accessories dining headgear indoors cap chinatown
iso
100
metering mode
5
aperture
f/4.5
focal length
24mm
shutter speed
1/125s
camera make
Canon
camera model
lens model
overall
(46.44%)
curation
(68.26%)
highlight visibility
(5.90%)
behavioral
(90.87%)
failure
(-0.34%)
harmonious color
(2.66%)
immersiveness
(0.12%)
interaction
(1.00%)
interesting subject
(1.50%)
intrusive object presence
(-19.97%)
lively color
(-12.79%)
low light
(19.04%)
noise
(-4.76%)
pleasant camera tilt
(-4.98%)
pleasant composition
(-75.34%)
pleasant lighting
(-26.39%)
pleasant pattern
(2.81%)
pleasant perspective
(-3.03%)
pleasant post processing
(2.89%)
pleasant reflection
(-3.07%)
pleasant symmetry
(0.44%)
sharply focused subject
(3.30%)
tastefully blurred
(24.27%)
well chosen subject
(-37.30%)
well framed subject
(29.08%)
well timed shot
(5.74%)
all
(-4.71%)
* 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.