Photos | Grand Opening Ceremony of The Broad
José Huizar, Jerry Brown, Eric Garcetti, Eric G, and other dignitaries stand proudly in front of The Broad, flanked by a red ribbon to commemorate the grand opening. The building's sleek blue glass facades reflect the clear blue sky, while the crowd of well-dressed attendees add to the splendor of the occasion.
BLIP-2 Description:
people standing in front of a building with a red ribbonMetadata
Capture date:
Original Dimensions:
2448w x 3264h - (download 4k)
Usage
Dominant Color:
Location:
art urban josé huizar flag glasses transportation outdoor office building wall tie formal rise sky jacket necklace city jewelry device blazer eric garcetti building outdoors coat microphone helmet jerry metropolis handrail vehicle high architecture blue speech wear audience accessories brown electrical shelter crowd boat
iso
32
metering mode
5
aperture
f/2.2
focal length
4mm
latitude
34.05
longitude
-118.25
shutter speed
1/6623s
camera make
Apple
camera model
lens model
overall
(55.37%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.65%)
failure
(-0.20%)
harmonious color
(11.11%)
immersiveness
(0.32%)
interaction
(1.00%)
interesting subject
(-5.82%)
intrusive object presence
(-16.31%)
lively color
(20.28%)
low light
(9.20%)
noise
(-0.39%)
pleasant camera tilt
(-2.60%)
pleasant composition
(-8.20%)
pleasant lighting
(34.42%)
pleasant pattern
(81.98%)
pleasant perspective
(25.54%)
pleasant post processing
(1.27%)
pleasant reflection
(2.99%)
pleasant symmetry
(2.10%)
sharply focused subject
(4.15%)
tastefully blurred
(4.11%)
well chosen subject
(-7.79%)
well framed subject
(3.25%)
well timed shot
(6.49%)
all
(14.41%)
* 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.