Photos | Funktion London Electricity Brings the House Down
A packed nightclub crowd gets lost in the music and raises their hands in unison during a Funktion London Electricity concert in 2006. Featuring Kim Nam-il, Eita Okuno, Kang Jung-ho, John Cipollina, Toshiaki Imae, John Michael McDonagh, Jodi g, and MC Q.
BLIP-2 Description:
a crowd of people at a concert with their hands upChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
3504w x 2336h - (download 4k)
Usage
Dominant Color:
bracelet g necklace ho urban footwear nam wristwatch crowd girl imae bag shoe party disk il toshiaki fun club london jung audience teen kim life interior jodi rekognition_c funktion jewelry kang accessories nightclub room night john cipollina john michael mcdonagh eita okuno electricity concert mc q handbag
iso
100
metering mode
5
aperture
f/4
focal length
17mm
shutter speed
1/250s
camera make
Canon
camera model
lens model
date
2006-06-15T01:45:18-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(16.10%)
curation
(68.40%)
highlight visibility
(5.76%)
behavioral
(70.51%)
failure
(-0.85%)
harmonious color
(-3.86%)
immersiveness
(0.12%)
interaction
(1.00%)
interesting subject
(-72.46%)
intrusive object presence
(-13.26%)
lively color
(-22.41%)
low light
(98.63%)
noise
(-2.37%)
pleasant camera tilt
(-12.07%)
pleasant composition
(-97.36%)
pleasant lighting
(-78.56%)
pleasant pattern
(0.95%)
pleasant perspective
(-16.15%)
pleasant post processing
(0.65%)
pleasant reflection
(3.09%)
pleasant symmetry
(0.10%)
sharply focused subject
(0.05%)
tastefully blurred
(-15.93%)
well chosen subject
(13.13%)
well framed subject
(-75.73%)
well timed shot
(18.98%)
all
(-12.47%)
* 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.