Photos | Blurred Partygoer at Nightclub
A woman dances in the low lighting of a nightclub, her image blurred in the motion of the crowd. Taken in November 2003.
BLIP-2 Description:
a blurry image of a woman at a partyChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
architecture urban pub building portrait chair bar footwear food baby beverage outdoors jorge capitanich restaurant furniture court shoe old toilet club alcohol junglescene indoors dining disco miyuki bar counter interior nature life table nightclub room respect high night heel lighting photography bathroom crowd cinema
Detected Text
date
2003-11-21T15:12:53-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(22.29%)
curation
(66.47%)
highlight visibility
(5.61%)
behavioral
(70.45%)
failure
(-2.03%)
harmonious color
(-0.27%)
immersiveness
(0.32%)
interaction
(1.00%)
interesting subject
(-33.72%)
intrusive object presence
(-9.28%)
lively color
(-23.88%)
low light
(99.66%)
noise
(-42.92%)
pleasant camera tilt
(-10.28%)
pleasant composition
(-62.16%)
pleasant lighting
(-56.84%)
pleasant pattern
(2.91%)
pleasant perspective
(-13.53%)
pleasant post processing
(0.21%)
pleasant reflection
(-3.52%)
pleasant symmetry
(0.22%)
sharply focused subject
(0.44%)
tastefully blurred
(-4.06%)
well chosen subject
(-16.24%)
well framed subject
(-13.48%)
well timed shot
(-8.80%)
all
(-11.00%)
* 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.