Photos | Crowd Goes Wild
The audience at the 2008 Coachella concert watches in awe as the band performs on stage, surrounded by the beautiful outdoor setting. Chad Green, Jake Langlois, John Petrucci, Ding Meiyuan, and Maria Rita Rossa are just a few of the excited fans in the crowd, taking in the incredible performance.
BLIP-2 Description:
a crowd of people watching a band perform at a concertChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
4368w x 2912h - (download 4k)
Usage
Dominant Color:
langlois instrument box backpack recreation chad green music band music glasses outdoor musician footwear bag grass leisure teen sky coachella musical activities tree john petrucci concert performer stage electronics shoe handbag glove boy jake meiyuan ding tent plant performance baseball speaker group sunglasses hat sport maria rita rossa audience speakers accessories crowd land
iso
100
metering mode
5
aperture
f/8
focal length
31mm
shutter speed
1/200s
camera make
Canon
camera model
lens model
overall
(32.23%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.56%)
failure
(-0.20%)
harmonious color
(-1.77%)
immersiveness
(0.56%)
interaction
(1.00%)
interesting subject
(-46.53%)
intrusive object presence
(-13.92%)
lively color
(1.10%)
low light
(0.63%)
noise
(-1.20%)
pleasant camera tilt
(-10.44%)
pleasant composition
(-86.13%)
pleasant lighting
(-21.58%)
pleasant pattern
(6.47%)
pleasant perspective
(0.11%)
pleasant post processing
(-4.27%)
pleasant reflection
(1.64%)
pleasant symmetry
(0.39%)
sharply focused subject
(0.37%)
tastefully blurred
(-0.25%)
well chosen subject
(-0.03%)
well framed subject
(-59.86%)
well timed shot
(8.04%)
all
(-4.41%)
* 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.