Photos | Dining conversation Caption: Michael R and Dave B enjoy a meal at a table in Los Angeles, discussing optical equipment and catching up as old friends.
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BLIP-2 Description:
two men sitting at a tableChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
1280w x 960h - (download 4k)
Usage
Dominant Color:
Location:
architecture cutlery dining table glass bracelet michael r cafeteria beer spoon urban optical plant building pub meal portrait food bar chair mobile beverage dish equipment restaurant furniture counter ice container court coffee dessert sitting diner dave alcohol glasses indoors cream lunch tabletop dining electronics living room jewelry fork table accessories room juice couch cafe potted cocktail phone photography cup
iso
500
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
date
2015-05-22T19:30:12.245000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(43.51%)
curation
(68.46%)
highlight visibility
(5.92%)
behavioral
(90.73%)
failure
(-0.24%)
harmonious color
(1.35%)
immersiveness
(0.15%)
interaction
(1.00%)
interesting subject
(28.42%)
intrusive object presence
(-5.52%)
lively color
(-5.26%)
low light
(46.58%)
noise
(-27.86%)
pleasant camera tilt
(-4.90%)
pleasant composition
(-28.59%)
pleasant lighting
(-27.86%)
pleasant pattern
(2.93%)
pleasant perspective
(0.93%)
pleasant post processing
(0.97%)
pleasant reflection
(-1.38%)
pleasant symmetry
(0.32%)
sharply focused subject
(1.05%)
tastefully blurred
(8.03%)
well chosen subject
(-23.90%)
well framed subject
(21.58%)
well timed shot
(23.99%)
all
(0.70%)
* 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.