Photos | Dining at the Defcon 10 Restaurant
Dave B and a group of eight other people sit at a table, perusing the menu and enjoying a meal at the Defcon 10 restaurant. The room features a potted plant, three chairs, and a tablecloth over the dining table.
BLIP-2 Description:
a group of people sitting at a table with a menuChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
architecture pen dining table tie glass cafeteria jeans cutlery necklace formal urban plant building meal defcon food chair publication footwear portrait flower baby beverage dish fruit wristwatch living dinner restaurant furniture shoe sitting diner dave desk alcohol junglescene indoors glasses tabletop lunch dining book wear jewelry table room accessories flower arrangement pear couch cafe potted photography cup bouquet produce tablecloth
Detected Text
date
2002-08-29T14:47:30-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(28.59%)
curation
(65.42%)
highlight visibility
(5.69%)
behavioral
(90.72%)
failure
(-0.39%)
harmonious color
(-1.53%)
immersiveness
(0.10%)
interaction
(1.00%)
interesting subject
(2.34%)
intrusive object presence
(-39.75%)
lively color
(-9.17%)
low light
(98.49%)
noise
(-13.87%)
pleasant camera tilt
(-9.84%)
pleasant composition
(-79.00%)
pleasant lighting
(-58.30%)
pleasant pattern
(3.64%)
pleasant perspective
(-8.18%)
pleasant post processing
(2.26%)
pleasant reflection
(1.01%)
pleasant symmetry
(0.17%)
sharply focused subject
(0.20%)
tastefully blurred
(-3.34%)
well chosen subject
(-30.18%)
well framed subject
(-25.54%)
well timed shot
(-0.10%)
all
(-9.99%)
* 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.