Photos | Ordination Outside
Dave Rose joins a crowd of 31 people standing outside of a building during the 2011 WBTLA ordination ceremony on a sunny day with blue skies and palm trees in the background.
BLIP-2 Description:
a group of people standing outside of a buildingChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
car wear bus high vehicle footwear outdoors rekognition_c suit arch plant femple urban wbtla traffic rose campus dave city heel garden glasses walking path hat necklace street sky office land building walkway road wbtla_ordination architecture boulevard jewelry automobile handbag college formal crowd nature palm ordination light transportation coat sandal pedestrian sidewalk outdoor machine metropolis tree bag shoe accessories arbour
iso
100
metering mode
5
aperture
f/8
focal length
19mm
shutter speed
1/250s
camera make
Canon
camera model
lens model
date
2011-05-15T12:36:37.570000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(42.72%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.76%)
failure
(-0.10%)
harmonious color
(3.27%)
immersiveness
(1.90%)
interaction
(1.00%)
interesting subject
(-25.59%)
intrusive object presence
(-8.03%)
lively color
(0.39%)
low light
(0.63%)
noise
(-1.17%)
pleasant camera tilt
(-8.91%)
pleasant composition
(-64.75%)
pleasant lighting
(-4.35%)
pleasant pattern
(5.37%)
pleasant perspective
(19.24%)
pleasant post processing
(-1.64%)
pleasant reflection
(-3.02%)
pleasant symmetry
(0.73%)
sharply focused subject
(0.20%)
tastefully blurred
(-0.23%)
well chosen subject
(15.36%)
well framed subject
(-53.86%)
well timed shot
(1.06%)
all
(1.11%)
* 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.