Photos | A Crowd of Ordained People Walking in Front of an Architectural Marvel
Eliezer Yudkowsky among the 33 people walking on the flagstone walkway amidst palm trees, shrubs, and firs in the college campus. The architecture of the building and the blue sky above makes a picturesque view.
BLIP-2 Description:
a large group of people walking in front of a buildingChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
architecture property arch urban plant building wbtla footwear pedestrian flagstone transportation sidewalk outdoors walkway crowd tree area outdoor femple campus sky traffic city wbtla_ordination shoe bag land path shrub nature ordination car vehicle college light fir suit accessories arbour real walking stroller garden palm eliezer yudkowsky handbag
Detected Text
iso
100
metering mode
5
aperture
f/8
focal length
16mm
shutter speed
1/250s
camera make
Canon
camera model
lens model
date
2011-05-15T12:36:02.950000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(40.19%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.75%)
failure
(-0.12%)
harmonious color
(1.68%)
immersiveness
(1.78%)
interaction
(1.00%)
interesting subject
(-26.20%)
intrusive object presence
(-10.42%)
lively color
(4.00%)
low light
(0.66%)
noise
(-1.29%)
pleasant camera tilt
(-8.84%)
pleasant composition
(-69.14%)
pleasant lighting
(-6.79%)
pleasant pattern
(7.08%)
pleasant perspective
(13.88%)
pleasant post processing
(-3.71%)
pleasant symmetry
(0.98%)
sharply focused subject
(0.22%)
tastefully blurred
(1.89%)
well chosen subject
(3.27%)
well framed subject
(-46.73%)
well timed shot
(-5.42%)
all
(-0.81%)
* 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.