Photos | The Ordination Crowd
David Ogden Stiers and Kaleigh Fratkin among the 39 people in formal wear standing outside the college building on a sunny day, surrounded by palm trees and cars, on May 15th, 2011.
BLIP-2 Description:
a crowd of people standing outside of a buildingChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
architecture tie formal arch urban plant building wbtla overcoat footwear tuxedo pedestrian boulevard sidewalk transportation walkway tree road outdoor jacket femple campus sky traffic bag wbtla_ordination sandal city land shoe david ogden stiers machine fratkin coat glasses metropolis path bus wear ordination car vehicle college light suit accessories handbag blazer walking automobile kaleigh palm crowd
iso
100
metering mode
5
aperture
f/8
focal length
17mm
shutter speed
1/250s
camera make
Canon
camera model
lens model
date
2011-05-15T12:36:40.890000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(39.16%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.79%)
failure
(-0.15%)
harmonious color
(3.89%)
immersiveness
(1.00%)
interaction
(1.00%)
interesting subject
(-35.86%)
intrusive object presence
(-8.35%)
lively color
(2.00%)
low light
(1.37%)
noise
(-0.76%)
pleasant camera tilt
(-6.89%)
pleasant composition
(-75.24%)
pleasant lighting
(-13.65%)
pleasant pattern
(5.79%)
pleasant perspective
(11.25%)
pleasant post processing
(-0.14%)
pleasant reflection
(0.45%)
pleasant symmetry
(0.66%)
sharply focused subject
(0.29%)
tastefully blurred
(-5.95%)
well chosen subject
(1.78%)
well framed subject
(-54.00%)
well timed shot
(-2.61%)
all
(-1.69%)
* 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.