Photos | Dining Out in LA
Michael R and Dave B enjoy each other's company over lunch at a local restaurant in Los Angeles. The elegant furniture and dim lighting create a cozy and intimate atmosphere at the dining table.
BLIP-2 Description:
two men sitting at a tableChronologically Adjacent
Note: You can also navigate with your arrow keys or swiping.
Metadata
Capture date:
Original Dimensions:
1280w x 960h - (download 4k)
Usage
Dominant Color:
Location:
diner restaurant accessories architecture bread food table cutlery plant beer cafe tabletop cocktail cafeteria drinking couch fork baby alcohol interior spoon furniture indoors glass dining room court building photography tableware container michael r portrait cup dave dining table utensil plate meal potted juice pub dish jewelry beverage bracelet optical equipment glasses lunch
iso
640
metering mode
5
aperture
f/2.2
focal length
3mm
latitude
34.05
longitude
-118.26
shutter speed
1/15s
camera make
Apple
camera model
lens model
overall
(26.81%)
curation
(68.29%)
highlight visibility
(5.91%)
behavioral
(90.71%)
failure
(-0.61%)
harmonious color
(-0.59%)
immersiveness
(0.15%)
interaction
(1.00%)
interesting subject
(-39.72%)
intrusive object presence
(-7.06%)
lively color
(-7.12%)
low light
(42.72%)
noise
(-29.96%)
pleasant camera tilt
(-7.93%)
pleasant composition
(-59.03%)
pleasant lighting
(-46.88%)
pleasant pattern
(5.15%)
pleasant perspective
(-12.25%)
pleasant post processing
(-0.90%)
pleasant reflection
(-4.31%)
pleasant symmetry
(0.20%)
sharply focused subject
(0.32%)
tastefully blurred
(-2.84%)
well chosen subject
(-36.04%)
well framed subject
(-38.92%)
well timed shot
(-9.60%)
all
(-9.43%)
* NOTE: This image was scaled up from its original size using an AI model called GFP-GAN (Generative Facial Prior), which is a
Generative adversartial network that can be used to repair (or upscale in this case) photos, sometimes the results are a little...
weird.
* WARNING: The title and caption of this image were generated with AI (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.