Photos | Nightclub Gathering
Jeremy Wotherspoon poses with a group of friends amidst the energetic crowd at a popular nightclub in 2003.
BLIP-2 Description:
a group of people standing in a dark roomChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
tie headgear bride formal urban pub baseball portrait bar baby cap beverage wedding outdoors hat counter baseball cap party old hardware fun club alcohol junglescene jeremy wotherspoon audience disco life interior wear nature electronics screen respect accessories nightclub monitor room night lighting photography computer crowd cinema
Detected Text
date
2003-12-08T16:50:18-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(14.39%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.63%)
failure
(-1.00%)
harmonious color
(-0.01%)
immersiveness
(0.15%)
interaction
(1.00%)
interesting subject
(-57.03%)
intrusive object presence
(-12.94%)
lively color
(-8.48%)
low light
(99.66%)
noise
(-12.35%)
pleasant camera tilt
(-7.72%)
pleasant composition
(-80.47%)
pleasant lighting
(-66.80%)
pleasant pattern
(1.98%)
pleasant perspective
(-7.99%)
pleasant post processing
(-13.68%)
pleasant reflection
(1.46%)
pleasant symmetry
(0.07%)
sharply focused subject
(0.22%)
tastefully blurred
(-2.58%)
well chosen subject
(-27.42%)
well framed subject
(-49.44%)
well timed shot
(-8.78%)
all
(-13.73%)
* 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.
* NOTE: This image was scaled up from its original size using an AI model called GFP-GAN (Generative Facial Prior), which is a
Generative adversartial network that can be used to repair (or upscale in this case) photos, sometimes the results are a little...
weird.
* 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.