Photos | Dining with Friends

Yulia Merkulova and two friends enjoy a delicious meal at a local restaurant in Los Angeles. The plywood table and trendy interior design make for an enjoyable dining experience.
BLIP-2 Description:
three people standing around a table with foodMetadata
Capture date:
Original Dimensions:
5760w x 3840h - (download 4k)
Usage
Dominant Color:
Location:
yulia merkulova les document room buffet la furniture desk decor dining tabletop home fun cratenu leah cafe linen leah_artisntal_la glass artisntal court indoors semolina accessories bag beverage calif jewelry chair neal d'anglud cafeteria building architecture artisanal food party manufacturing table mobile phone alcohol restaurant angeles meal handbag bracelet box factory tablecloth interior design electronics plywood wood
iso
3200
metering mode
5
aperture
f/2.8
focal length
16mm
shutter speed
1/60s
camera make
Canon
camera model
lens model
date
2014-10-11T15:22:57.910000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(40.43%)
curation
(65.91%)
highlight visibility
(5.57%)
behavioral
(70.55%)
failure
(-0.20%)
harmonious color
(-0.88%)
immersiveness
(0.27%)
interaction
(1.00%)
interesting subject
(15.67%)
intrusive object presence
(-18.65%)
lively color
(-12.83%)
low light
(3.86%)
noise
(-0.95%)
pleasant camera tilt
(-8.65%)
pleasant composition
(-32.30%)
pleasant lighting
(-17.04%)
pleasant pattern
(13.79%)
pleasant perspective
(11.54%)
pleasant post processing
(-1.62%)
pleasant reflection
(-3.40%)
pleasant symmetry
(2.12%)
sharply focused subject
(0.56%)
tastefully blurred
(-18.09%)
well chosen subject
(-12.16%)
well framed subject
(13.90%)
well timed shot
(15.94%)
all
(1.09%)
* 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.