Photos | Women's March Protest in the City
Chris McGinn joins the 40-person strong crowd holding signs and chanting slogans protesting for women's rights in the heart of the metropolis.
BLIP-2 Description:
a large crowd of people holding signs and protestingChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
5760w x 3840h - (download 4k)
Usage
Dominant Color:
daytime activities others urban leisure building pre mobile footwear eos iii otters hat chris mcginn furniture ippressed outdoor one text performance sky bag shoe city sporting cloudy womens glove sun jo bench blue parade glasses coachella january winter metropolis mark banner sign electronics accessories skyscraper limen adventure handbag walking canon phone entertainment protest free crowd march event oppressed
iso
400
metering mode
5
aperture
f/2.8
focal length
16mm
shutter speed
1/8000s
camera make
Canon
camera model
lens model
date
2017-01-21T12:00:05.380000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(36.57%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.61%)
failure
(-0.37%)
harmonious color
(0.96%)
immersiveness
(2.15%)
interaction
(1.00%)
interesting subject
(-40.43%)
intrusive object presence
(-21.31%)
lively color
(-4.00%)
low light
(11.65%)
noise
(-1.44%)
pleasant camera tilt
(-12.02%)
pleasant composition
(-75.63%)
pleasant lighting
(-29.81%)
pleasant pattern
(5.91%)
pleasant perspective
(11.31%)
pleasant post processing
(-2.67%)
pleasant reflection
(1.40%)
pleasant symmetry
(0.59%)
sharply focused subject
(0.34%)
tastefully blurred
(-2.44%)
well chosen subject
(8.83%)
well framed subject
(-49.66%)
well timed shot
(3.96%)
all
(-3.08%)
* 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.