Photos | Convention Crowd
Kazuhiro Koshi and Pete Escovedo among the 56 people in attendance at the 2009 NAMM convention, surrounded by a bustling crowd of industry professionals and music enthusiasts.
BLIP-2 Description:
a crowd of people at a conventionChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
architecture activities cafeteria headgear boy urban namm classroom building leisure food music child footwear food court kazuhiro koshi cap luggage hat crowd musician pete girl restaurant escovedo container shoe bag manufacturing grocery hardware night life factory indoors glasses audience pc school electronics performer screen accessories room monitor musical instrument store market laptop workshop part back computer shop handbag
iso
1600
metering mode
5
aperture
f/5
focal length
16mm
shutter speed
1/125s
camera make
Canon
camera model
lens model
date
2009-01-16T14:23:37.610000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(34.16%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.75%)
failure
(-0.61%)
harmonious color
(-1.76%)
immersiveness
(0.46%)
interaction
(1.00%)
interesting subject
(-36.43%)
intrusive object presence
(-10.64%)
lively color
(-16.31%)
low light
(68.31%)
noise
(-2.93%)
pleasant camera tilt
(-9.40%)
pleasant composition
(-83.94%)
pleasant lighting
(-39.84%)
pleasant pattern
(10.25%)
pleasant perspective
(-5.05%)
pleasant post processing
(3.65%)
pleasant reflection
(-3.24%)
pleasant symmetry
(0.49%)
sharply focused subject
(0.22%)
tastefully blurred
(-9.65%)
well chosen subject
(3.81%)
well framed subject
(-65.09%)
well timed shot
(0.48%)
all
(-7.14%)
* 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.