Photos | Election Night Viewing Party at Bobby Flay's Restaurant
Bobby Flay hosts a packed house of 28 people at his restaurant, all gathered around to watch the election results on TV.
BLIP-2 Description:
a large group of people in a room watching a tvChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
4368w x 2912h - (download 4k)
Usage
Dominant Color:
architecture bobby flay dining table cafeteria breaking urban classroom building elected fall food chair pub footwear eos election_day lamp november crowd restaurant furniture flooring design court projection bag shoe president hardware hall indoors dining audience school rack interior electronics obama screen table accessories room monitor handbag couch cafe canon lighting tv live day floor barack election computer news cnn
iso
3200
metering mode
5
aperture
f/2.8
focal length
16mm
shutter speed
1/15s
camera make
Canon
camera model
lens model
date
2008-11-04T21:24:06-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(36.50%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.60%)
failure
(-0.66%)
harmonious color
(1.05%)
immersiveness
(0.59%)
interaction
(1.00%)
interesting subject
(-50.83%)
intrusive object presence
(-14.33%)
lively color
(-44.07%)
low light
(89.16%)
noise
(-4.42%)
pleasant camera tilt
(-13.04%)
pleasant composition
(-87.21%)
pleasant lighting
(-42.48%)
pleasant pattern
(3.96%)
pleasant perspective
(0.21%)
pleasant post processing
(1.42%)
pleasant reflection
(-2.83%)
pleasant symmetry
(1.03%)
sharply focused subject
(0.12%)
tastefully blurred
(-15.04%)
well chosen subject
(9.27%)
well framed subject
(-57.28%)
well timed shot
(3.44%)
all
(-8.12%)
* 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.