Photos | Dining with Friends
Dave B and friends indulge in a night out at a restaurant, surrounded by stylish interior decorations, consumer electronics, and all the necessary utensils for a delightful dining experience.
BLIP-2 Description:
a group of people sitting at a table with drinksMetadata
Capture date:
Original Dimensions:
1280w x 960h - (download 4k)
Usage
Dominant Color:
Location:
urban phone bracelet ring restaurant glasses cutlery portrait baby dave mobile dinner formal court diner interior food eyeglasses spoon cafeteria liquor optical equipment counter fork jewelry table building pub lunch tableware electronics drinking glass glass bar room dish cocktail dining room cup wristwatch beverage tabletop suit architecture machine consumer meal utensil beer wear furniture alcohol accessories photography dining indoors part
iso
1000
metering mode
5
aperture
f/2.2
focal length
3mm
latitude
41.69
longitude
44.81
shutter speed
1/15s
camera make
Apple
camera model
lens model
overall
(29.08%)
curation
(65.71%)
highlight visibility
(5.71%)
behavioral
(90.77%)
failure
(-1.27%)
harmonious color
(-4.53%)
immersiveness
(0.07%)
interaction
(1.00%)
interesting subject
(12.76%)
intrusive object presence
(-3.88%)
lively color
(-13.29%)
low light
(52.78%)
noise
(-37.65%)
pleasant camera tilt
(-3.38%)
pleasant composition
(-40.89%)
pleasant lighting
(-45.51%)
pleasant pattern
(5.37%)
pleasant perspective
(-13.44%)
pleasant post processing
(-1.42%)
pleasant reflection
(0.65%)
pleasant symmetry
(0.12%)
sharply focused subject
(0.44%)
tastefully blurred
(-10.64%)
well chosen subject
(-49.66%)
well framed subject
(-11.55%)
well timed shot
(-5.50%)
all
(-8.32%)
* 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 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.