Photos | Nightlife Vibes at the Club
Mix Master Mike rocks the crowd as Fiona Ma enjoys the urban party scene with her friends at a packed nightclub.
BLIP-2 Description:
a crowd of people at a nightclub with a man in the middleChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
lighting room urban baby hardware screen fun child cinema old accessories helmet photography mike jewelry pub night glasses photos/mix_master_mike crowd necklace club monitor master concert audience party portrait interior boy disco junglescene bride nightclub computer life mix fiona ma electronics wedding
Detected Text
date
2003-01-19T04:17:15-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(16.26%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.58%)
failure
(-1.25%)
harmonious color
(-2.27%)
immersiveness
(0.12%)
interaction
(1.00%)
interesting subject
(-62.70%)
intrusive object presence
(-11.33%)
lively color
(-21.66%)
low light
(99.85%)
noise
(-29.37%)
pleasant camera tilt
(-10.13%)
pleasant composition
(-85.11%)
pleasant lighting
(-75.00%)
pleasant pattern
(2.15%)
pleasant perspective
(-15.52%)
pleasant post processing
(0.63%)
pleasant reflection
(-1.91%)
pleasant symmetry
(0.15%)
sharply focused subject
(0.15%)
tastefully blurred
(-4.50%)
well chosen subject
(-3.45%)
well framed subject
(-59.86%)
well timed shot
(0.40%)
all
(-13.58%)
* 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.