Photos | Gaming at Defcon 22
Sahin Eryilmaz and Mick Thomson take a break to play some video games on a laptop during Defcon 22 in Las Vegas.
BLIP-2 Description:
a man is playing a video game on a laptopChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
3840w x 5760h - (download 4k)
Usage
Dominant Color:
Location:
lighting machine room try furniture desk floor laptop consumer hardware screen permanendy tage rules projection tv stop pc alorms indoors accessories mick modify jewelry chair exit glasses away building now architecture necklace crowd airport harder monitor strip wach classroom audience interior table attempt mobile wites phone restaurant computer null flooring school sahin eryilmaz team start running off design defcon thomson electronics plywood wood
Detected Text
iso
3200
metering mode
5
aperture
f/2.8
focal length
35mm
shutter speed
1/40s
camera make
Canon
camera model
lens model
date
2014-08-09T12:35:42-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(20.07%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.56%)
failure
(-0.51%)
harmonious color
(0.27%)
immersiveness
(0.20%)
interaction
(1.00%)
interesting subject
(-67.58%)
intrusive object presence
(-12.38%)
lively color
(-36.62%)
low light
(15.63%)
noise
(-2.29%)
pleasant camera tilt
(-11.02%)
pleasant composition
(-87.11%)
pleasant lighting
(-58.06%)
pleasant pattern
(2.03%)
pleasant perspective
(-12.71%)
pleasant post processing
(0.62%)
pleasant reflection
(-2.75%)
pleasant symmetry
(0.17%)
sharply focused subject
(0.20%)
tastefully blurred
(-6.15%)
well chosen subject
(-11.20%)
well framed subject
(-47.49%)
well timed shot
(-0.66%)
all
(-12.77%)
* 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.