Photos | Group of Distinguished Guests Pose in Front of Building
Kim Dotcom, Eric Koston, Kim Dong-yeon, and Geoff Kabush stand with 28 other people in front of a beautiful building on a sunny day. The crowd is dressed in a variety of clothing and footwear, including sandals and hats, and they are surrounded by green shrubs and trees.
BLIP-2 Description:
a group of people standing in front of a buildingChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
4368w x 2912h - (download 4k)
Usage
Dominant Color:
shrub car bus pants geoff koston vehicle way footwear outdoors lamp shop apc plant kim dong-yeon today glasses walking hat kabush sky building architecture handbag college kim dotcom crowd eric wristwatch easiest school transportation sandal amercasprinteccom outdoor stop tree print bag shoe accessories
iso
100
metering mode
5
aperture
f/8
focal length
16mm
shutter speed
1/200s
camera make
Canon
camera model
lens model
date
2008-08-06T15:18:04-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(57.18%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.65%)
failure
(-0.02%)
harmonious color
(7.40%)
immersiveness
(0.61%)
interaction
(1.00%)
interesting subject
(40.43%)
intrusive object presence
(-2.27%)
lively color
(24.84%)
low light
(0.27%)
noise
(-0.44%)
pleasant camera tilt
(-4.06%)
pleasant composition
(-2.32%)
pleasant lighting
(24.49%)
pleasant pattern
(10.52%)
pleasant perspective
(24.32%)
pleasant post processing
(0.96%)
pleasant reflection
(0.20%)
pleasant symmetry
(1.37%)
sharply focused subject
(2.20%)
tastefully blurred
(5.16%)
well chosen subject
(-7.36%)
well framed subject
(23.45%)
well timed shot
(3.78%)
all
(11.38%)
* 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.