Photos | Ordination Ceremony Crowd
Nenad Puhovski, Mike Schmidt, and Angela Finocchiaro join 36 other people and 9 handbags outside of a beautiful building during the 2011 WBTLA ordination ceremony. The architecture and decorative plants frame the large crowd gathered on the sidewalk.
BLIP-2 Description:
a large group of people standing outside of a buildingChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
urban street mike น palm transportation outdoor footwear grass bag garden path ordination เพ sky tree pedestrian wbtla_ordination potted ริน city decorative flagstone car nenad puhovski sidewalk arch building heel traffic light shoe handbag outdoors campus nature college angela finocchiaro plant วิ metropolis wristwatch road vehicle high architecture wbtla blue hat light bus schmidt ช shrub accessories walking walkway crowd land
iso
100
metering mode
5
aperture
f/8
focal length
16mm
shutter speed
1/250s
camera make
Canon
camera model
lens model
overall
(43.12%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.84%)
failure
(-0.12%)
harmonious color
(1.98%)
immersiveness
(1.81%)
interaction
(1.00%)
interesting subject
(-17.57%)
intrusive object presence
(-11.40%)
lively color
(2.44%)
low light
(0.54%)
noise
(-2.29%)
pleasant camera tilt
(-7.50%)
pleasant composition
(-72.66%)
pleasant lighting
(-3.91%)
pleasant pattern
(6.42%)
pleasant perspective
(16.28%)
pleasant post processing
(-0.54%)
pleasant reflection
(-1.06%)
pleasant symmetry
(0.76%)
sharply focused subject
(0.24%)
tastefully blurred
(0.86%)
well chosen subject
(8.49%)
well framed subject
(-46.90%)
well timed shot
(2.68%)
all
(0.56%)
* 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.