Photos | Laptop Luncheon at Defcon 22
Alex Chow and Taku Yamazoe join a crowd of computer enthusiasts for a meal and some serious coding at Defcon 22 in Las Vegas.
BLIP-2 Description:
a group of people sitting at a table with laptopsChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5760w x 3840h - (download 4k)
Usage
Dominant Color:
Location:
architecture summer cafeteria chow boy flag classroom building meal defcon food mobile speaker iii eos keyboard buffet travel kai plywood hat crowd restaurant furniture flooring court wood bag manufacturing taku yamazoe hardware machine desk glasses indoors factory teen pc school alex off mark cord electronics rekognition_c screen table accessories room monitor strip trip august couch canon lighting laptop workshop phone cup floor computer handbag consumer
iso
3200
metering mode
5
aperture
f/2.8
focal length
27mm
shutter speed
1/20s
camera make
Canon
camera model
lens model
date
2014-08-09T13:58:22-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(41.72%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.44%)
failure
(-0.24%)
harmonious color
(3.58%)
immersiveness
(0.24%)
interaction
(1.00%)
interesting subject
(-35.06%)
intrusive object presence
(-2.83%)
lively color
(-38.67%)
low light
(82.76%)
noise
(-2.49%)
pleasant camera tilt
(-5.98%)
pleasant composition
(-78.86%)
pleasant lighting
(-38.06%)
pleasant pattern
(5.32%)
pleasant perspective
(4.23%)
pleasant post processing
(4.46%)
pleasant reflection
(2.03%)
pleasant symmetry
(0.37%)
sharply focused subject
(0.29%)
tastefully blurred
(-16.55%)
well chosen subject
(-1.72%)
well framed subject
(-42.33%)
well timed shot
(3.14%)
all
(-5.80%)
* 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.