Photos | Spotlight on Adrian Otaegui

Adrian Otaegui takes center stage as he performs under the glowing foliage and bright lights in a packed nightclub.
BLIP-2 Description:
a group of people standing around a microphone in a dark roomMetadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
lighting tripod speaker urban respect hardware device recreation screen plant spotlight wristwatch accessories video photography night club rob g performance jewelry pub cesar glasses unclescene camera foliage club monitor portrait light junglescene cup entertainer electrical computer adrian otaegui microphone electronics necklace
Detected Text
date
2002-08-29T13:45:55-07:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(18.92%)
curation
(67.89%)
highlight visibility
(5.72%)
behavioral
(70.37%)
failure
(-0.76%)
harmonious color
(-3.88%)
immersiveness
(0.17%)
interaction
(1.00%)
interesting subject
(-53.47%)
intrusive object presence
(-21.48%)
lively color
(-28.93%)
low light
(90.33%)
noise
(-15.89%)
pleasant camera tilt
(-12.02%)
pleasant composition
(-82.76%)
pleasant lighting
(-62.45%)
pleasant pattern
(3.59%)
pleasant perspective
(-6.65%)
pleasant post processing
(1.84%)
pleasant reflection
(-6.70%)
pleasant symmetry
(0.49%)
sharply focused subject
(0.17%)
tastefully blurred
(-8.95%)
well chosen subject
(-5.60%)
well framed subject
(-47.36%)
well timed shot
(4.44%)
all
(-11.88%)
* 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.