Photos | Club Night Gathering
Maria Perepelkina and Alan W join a crowd of 17 people at a night club on March 14th, 2002. The urban clothing, handbags, accessories, and jewelry add fun and style to the indoor party atmosphere.
BLIP-2 Description:
a group of people standing around in a roomMetadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
kat urban lamp night jeans party glasses baby portrait shirt teylor d hoodie night life bag respect necklace counter spr jewelry pictures pub disco lionel junglescene handbag erica bar trace g pants plant teylor belt beverage hat alan maria perepelkina kate fun club alcohol accessories photography indoors crowd
Detected Text
overall
(10.75%)
curation
(67.99%)
highlight visibility
(5.73%)
behavioral
(70.48%)
failure
(-0.93%)
harmonious color
(-3.71%)
immersiveness
(0.17%)
interaction
(1.00%)
interesting subject
(-75.88%)
intrusive object presence
(-27.47%)
lively color
(-3.74%)
low light
(49.71%)
noise
(-14.99%)
pleasant camera tilt
(-12.16%)
pleasant composition
(-88.28%)
pleasant lighting
(-54.64%)
pleasant pattern
(3.47%)
pleasant perspective
(-17.93%)
pleasant post processing
(-0.60%)
pleasant reflection
(1.65%)
pleasant symmetry
(0.17%)
sharply focused subject
(0.15%)
tastefully blurred
(-13.00%)
well chosen subject
(-6.83%)
well framed subject
(-71.58%)
well timed shot
(-13.05%)
all
(-12.93%)
* 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.