Photos | A View of the 2008 White Knight Two Crowd
Kevin McCarthy and Gary Schwartz among the 58 people gathered in the large hangar for the debut of the White Knight Two airplane.
BLIP-2 Description:
a large crowd of people in a large hangarChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
4368w x 2912h - (download 4k)
Usage
Dominant Color:
architecture cafeteria classroom building food chair speaker footwear knight airplane lamp transportation hat outdoors crowd restaurant furniture kevin mccarthy two flooring court manufacturing bag shoe sandal aircraft hardware white hall glasses indoors factory audience airport school electronics theater backpack vehicle screen accessories room monitor auditorium high heel schwartz gary terminal floor concert computer handbag white_knight_two shelter
iso
1600
metering mode
5
aperture
f/2.8
focal length
16mm
shutter speed
1/400s
camera make
Canon
camera model
lens model
date
2008-07-28T08:11:58-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(26.64%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.47%)
failure
(-0.54%)
harmonious color
(0.19%)
immersiveness
(0.34%)
interaction
(1.00%)
interesting subject
(-46.17%)
intrusive object presence
(-11.65%)
lively color
(-13.02%)
low light
(67.53%)
noise
(-2.49%)
pleasant camera tilt
(-10.55%)
pleasant composition
(-83.30%)
pleasant lighting
(-39.36%)
pleasant pattern
(9.62%)
pleasant perspective
(6.00%)
pleasant post processing
(0.27%)
pleasant reflection
(-0.06%)
pleasant symmetry
(0.54%)
sharply focused subject
(0.15%)
tastefully blurred
(-10.15%)
well chosen subject
(4.56%)
well framed subject
(-62.89%)
well timed shot
(0.41%)
all
(-6.64%)
* 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.