Photos | Trombone Performance Draws Huge Crowd

Tang Lingsheng wows the audience with his trombone skills during the 2007 Grand Performances Ozomatli concert. Prakash Amritraj is among the many people in attendance enjoying the music.
BLIP-2 Description:
a crowd of people gathered around a man playing a tromboneMetadata
Capture date:
Original Dimensions:
4368w x 2912h - (download 4k)
Usage
performances tuba activities headgear leisure baseball music mobile footwear trumpet section hat wristwatch horn grand musician lax performance shoe grand_performances_ozomatli bag amritraj parade taff glasses brass audience belt helmet sunglasses electronics prakash performer tang lingsheng group performance accessories drummer musical instrument recreation handbag band percussion ozomatli phone concert crowd drum event
iso
1600
metering mode
5
aperture
f/5
focal length
24mm
shutter speed
1/100s
camera make
Canon
camera model
lens model
date
2007-06-10T18:34:42-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(42.36%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.56%)
failure
(-0.15%)
harmonious color
(1.82%)
immersiveness
(0.32%)
interaction
(1.00%)
interesting subject
(26.68%)
intrusive object presence
(-10.74%)
lively color
(-7.59%)
low light
(2.93%)
noise
(-0.71%)
pleasant camera tilt
(-5.73%)
pleasant composition
(-75.63%)
pleasant lighting
(-28.83%)
pleasant pattern
(2.93%)
pleasant perspective
(9.17%)
pleasant post processing
(1.16%)
pleasant reflection
(0.51%)
pleasant symmetry
(0.27%)
sharply focused subject
(1.12%)
tastefully blurred
(-1.97%)
well chosen subject
(-25.37%)
well framed subject
(-39.72%)
well timed shot
(27.39%)
all
(-1.95%)
* 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.