Photos | Rocking the Stage
Fabiana Dadone and 16 other performers electrify the crowd at Coachella Weekend 2, Day 1 in 2013. The Empire Polo Club is lit up as the stage comes alive with music and energy.
BLIP-2 Description:
a group of people on stage at a concertChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
Location:
tie group activities formal spotlight urban rock leisure music speaker footwear stage arts hat performing musician outdoor performance shoe bag land weekend art hall glasses indoors coachella audience shorts fabiana life path helmet interior rekognition_c electronics wear theater dadone performer light auditorium accessories room musical instrument night recreation handbag band lighting day concert crowd
iso
3200
metering mode
5
aperture
f/2.8
exposure bias
-0.67
focal length
16mm
shutter speed
1/500s
camera make
Canon
camera model
lens model
date
2013-04-19T23:20:40-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(45.29%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.50%)
failure
(-0.85%)
harmonious color
(5.86%)
immersiveness
(1.37%)
interaction
(1.00%)
interesting subject
(-28.00%)
intrusive object presence
(-12.28%)
lively color
(-17.88%)
low light
(99.71%)
noise
(-6.01%)
pleasant camera tilt
(-10.07%)
pleasant composition
(-65.87%)
pleasant lighting
(-41.04%)
pleasant pattern
(10.01%)
pleasant perspective
(1.79%)
pleasant post processing
(2.12%)
pleasant reflection
(-0.20%)
pleasant symmetry
(1.03%)
sharply focused subject
(0.24%)
tastefully blurred
(-3.26%)
well chosen subject
(-1.60%)
well framed subject
(-43.04%)
well timed shot
(7.07%)
all
(-3.43%)
* 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.
* 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.