Photos | Lunch with Friends

Robin Schulz, David Anders, and Francisco C joined four other friends for a meal at a cafeteria in Los Angeles. The table was filled with a variety of delicious food and tableware while they enjoyed each other's company.
BLIP-2 Description:
a group of people standing around a table with foodMetadata
Capture date:
Original Dimensions:
2448w x 3264h - (download 4k)
Usage
Location:
architecture cafeteria tableware bowl building meal food chair mobile footwear brunch buffet dish plywood wristwatch restaurant furniture anders utensil court charles v bag shoe wood francisco eating vincent desk glasses indoors lunch tabletop dining district electronics bread jewelry todd table accessories room david plate phone robin schulz cup handbag
iso
100
metering mode
5
aperture
f/2.2
focal length
4mm
latitude
34.05
longitude
-118.26
shutter speed
1/30s
camera make
Apple
camera model
lens model
date
2015-08-06T15:51:54.371000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(30.57%)
curation
(92.23%)
highlight visibility
(7.58%)
behavioral
(70.62%)
failure
(-0.32%)
harmonious color
(-0.57%)
immersiveness
(0.15%)
interaction
(1.00%)
interesting subject
(-27.73%)
intrusive object presence
(-10.89%)
lively color
(1.69%)
low light
(11.16%)
noise
(-1.88%)
pleasant camera tilt
(-8.01%)
pleasant composition
(-60.50%)
pleasant lighting
(-39.21%)
pleasant pattern
(3.78%)
pleasant perspective
(-12.45%)
pleasant post processing
(3.07%)
pleasant reflection
(0.25%)
pleasant symmetry
(0.12%)
sharply focused subject
(0.42%)
tastefully blurred
(-4.53%)
well chosen subject
(-29.69%)
well framed subject
(-27.51%)
well timed shot
(-1.97%)
all
(-6.63%)
* 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.