Photos | A Sea of Humanity on a Sunny Day
Liu Xiaobo captured the moment of an enormous crowd walking down the sidewalk during the 2011/wbtla ordination ceremony on a bright and delightful day.
BLIP-2 Description:
a large crowd of people walking down the sidewalkChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
architecture tie formal conifer urban wbtla plant building mobile gown footwear pedestrian outdoors transportation sidewalk tree liu xiaobo outdoor campus sky traffic shoe wbtla_ordination bag city land glove fashion coat glasses indoors shorts metropolis path shrub nature corridor electronics ordination wear car grass vehicle college fir light suit accessories arbour high heel handbag walking garden phone palm dress crowd monastery
iso
100
metering mode
5
aperture
f/8
focal length
16mm
shutter speed
1/250s
camera make
Canon
camera model
lens model
date
2011-05-15T12:37:15.560000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(46.36%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.72%)
failure
(-0.27%)
harmonious color
(2.08%)
immersiveness
(1.15%)
interaction
(1.00%)
interesting subject
(-4.27%)
intrusive object presence
(-15.41%)
lively color
(8.02%)
low light
(10.86%)
noise
(-3.17%)
pleasant camera tilt
(-6.95%)
pleasant composition
(-68.46%)
pleasant lighting
(-10.00%)
pleasant pattern
(11.67%)
pleasant perspective
(14.54%)
pleasant post processing
(2.80%)
pleasant reflection
(2.99%)
pleasant symmetry
(1.34%)
sharply focused subject
(0.54%)
tastefully blurred
(-7.07%)
well chosen subject
(-3.55%)
well framed subject
(-44.07%)
well timed shot
(4.81%)
all
(1.26%)
* 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.