Photos | Nightclub Party with a Happy Guest

A man wearing a vibrant hat and eyeglasses smiles for a photo while surrounded by a lively crowd at a nightclub party in September 2002. Thirteen people, including five men and two babies, can be seen in the background along with various accessories and decorative plants.
BLIP-2 Description:
a group of people at a party with a man smilingMetadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
lighting speaker cap room outdoors urban furniture eyeglasses dining photobombing baby candle lamp fun plant teen old muse indoors accessories bag beverage photography equipment shirt baseball jewelry pub optical night glasses footwear building architecture crowd club counter portrait party bar table boy interior junglescene nightclub restaurant alcohol life handbag bracelet headgear hat nature electronics necklace shoe
Detected Text
date
2002-09-28T13:21:06-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(24.30%)
curation
(65.47%)
highlight visibility
(5.54%)
behavioral
(70.66%)
failure
(-0.51%)
harmonious color
(0.09%)
immersiveness
(0.12%)
interaction
(1.00%)
interesting subject
(-36.23%)
intrusive object presence
(-11.33%)
lively color
(10.31%)
low light
(98.78%)
noise
(-11.57%)
pleasant camera tilt
(-6.89%)
pleasant composition
(-67.48%)
pleasant lighting
(-56.59%)
pleasant pattern
(4.81%)
pleasant perspective
(-6.76%)
pleasant post processing
(1.28%)
pleasant reflection
(0.99%)
pleasant symmetry
(0.12%)
sharply focused subject
(0.42%)
tastefully blurred
(-1.93%)
well chosen subject
(-29.17%)
well framed subject
(-25.76%)
well timed shot
(-6.73%)
all
(-8.70%)
* 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.