Photos | A Lavish Dinner with Celebrities
Matthew Fox, Sho Kosugi, Sachi Hamano, Guo Xinxin, Eileen Olszewski, and Yang Hyang-ja enjoy a grand performance by Ozomatli at a fancy restaurant filled with chandeliers and a bustling crowd in 2007.
BLIP-2 Description:
a large group of people sitting at tables in a fancy restaurantChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
4368w x 2912h - (download 4k)
Usage
Dominant Color:
architecture reception pen performances sho banquet ja building eileen olszewski hyang food chair xinxin lamp hat grand restaurant furniture guo flooring design court grand_performances_ozomatli waiting room fun kosugi hall indoors dining sachi hamano interior matthew fox light table room ozomatli home plate chandelier decor cup floor ballroom crowd linen yang
iso
1250
metering mode
5
aperture
f/2.8
focal length
24mm
shutter speed
1/400s
camera make
Canon
camera model
lens model
date
2007-06-10T11:22:59-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(36.55%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.48%)
failure
(-0.42%)
harmonious color
(3.37%)
immersiveness
(0.20%)
interaction
(1.00%)
interesting subject
(-34.67%)
intrusive object presence
(-10.33%)
lively color
(-29.47%)
low light
(53.22%)
noise
(-3.22%)
pleasant camera tilt
(-8.57%)
pleasant composition
(-85.84%)
pleasant lighting
(-34.72%)
pleasant pattern
(10.74%)
pleasant perspective
(15.31%)
pleasant post processing
(-1.24%)
pleasant reflection
(-3.06%)
pleasant symmetry
(1.66%)
sharply focused subject
(0.24%)
tastefully blurred
(-12.84%)
well chosen subject
(23.69%)
well framed subject
(-51.81%)
well timed shot
(6.40%)
all
(-4.54%)
* 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.