Photos | Festival Frenzy

Crowds gather at Coachella 2017 to enjoy music, sunshine and good company. Maddie Rooney, Lee Dong-jun, Peter Lik, and Gisele Miró among the 54,000 music enthusiasts who came together to celebrate. #Coachella #Concert #Crowd
BLIP-2 Description:
a crowd of people at a music festivalMetadata
Capture date:
Original Dimensions:
5472w x 3648h - (download 4k)
Usage
Dominant Color:
Location:
bracelet peter lik headgear necklace ca plant baseball speaker footwear festival eos cap hat wristwatch grand tree states outdoor maddie rooney jun sky shoe land glasses coachella audience angeles gisele united sunglasses electronics los grass jewelry continental united states dong ave accessories broad downtown april spring canon che blue sky miró california concert lee crowd
Detected Text
iso
100
metering mode
5
aperture
f/2.8
focal length
16mm
shutter speed
1/2000s
camera make
Canon
camera model
lens model
date
2017-04-14T15:17:26.830000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(45.65%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.79%)
failure
(-0.29%)
harmonious color
(1.05%)
immersiveness
(1.49%)
interaction
(1.00%)
interesting subject
(24.55%)
intrusive object presence
(-10.64%)
lively color
(5.74%)
low light
(4.81%)
noise
(-1.78%)
pleasant camera tilt
(-9.16%)
pleasant composition
(-57.47%)
pleasant lighting
(-22.97%)
pleasant pattern
(17.53%)
pleasant perspective
(10.55%)
pleasant post processing
(-3.61%)
pleasant reflection
(3.45%)
pleasant symmetry
(0.83%)
sharply focused subject
(0.76%)
tastefully blurred
(1.96%)
well chosen subject
(3.75%)
well framed subject
(-44.36%)
well timed shot
(18.91%)
all
(1.60%)
* 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.