Photos | Vanessa da Mata Rocks Coachella 2012
A packed crowd watches as Vanessa da Mata and her band perform at Coachella 2012 Weekend 2 Friday. The colorful cord lights and high-energy drum beats add to the electric atmosphere of the concert.
BLIP-2 Description:
a band playing in a large tent with a crowd watchingChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
bracelet spotlight urban rock music speaker footwear stage microphone musical instrument basketball performing arts performance shoe weekend art hall glasses friday coachella ball indoors audience (ball) life cord electronics vanessa da mata theater jewelry sport light accessories auditorium night recreation speakers lighting device concert crowd drum electrical
iso
6400
metering mode
5
aperture
f/2.8
focal length
21mm
shutter speed
1/200s
camera make
Canon
camera model
lens model
date
2012-04-20T22:32:24.820000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(52.88%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.30%)
failure
(-0.29%)
harmonious color
(11.24%)
immersiveness
(0.98%)
interaction
(1.00%)
interesting subject
(27.00%)
intrusive object presence
(-12.92%)
lively color
(-45.70%)
low light
(98.83%)
noise
(-1.98%)
pleasant camera tilt
(-6.20%)
pleasant composition
(-53.52%)
pleasant lighting
(-2.05%)
pleasant pattern
(6.76%)
pleasant perspective
(24.73%)
pleasant post processing
(4.01%)
pleasant reflection
(8.31%)
pleasant symmetry
(3.42%)
sharply focused subject
(0.24%)
tastefully blurred
(-19.89%)
well chosen subject
(-2.02%)
well framed subject
(-23.46%)
well timed shot
(25.32%)
all
(4.35%)
* 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.