Photos | Women March in DC

Asako Hoshina joins the massive crowd of protesters holding banners and signs to advocate for women's rights and equality, under a cloudy sky with a backdrop of urban buildings at the Women's March in Washington DC.
BLIP-2 Description:
a large crowd of people holding signs and protestingMetadata
Capture date:
Original Dimensions:
5760w x 3840h - (download 4k)
Usage
Dominant Color:
activities patriarch urban plant building pre leisure mobile violence transportation hat wristwatch offroad asako hoshino tree outdoor text sky traffic bag city exam cloudy womens fuck ou politics parade glasses coachella audience metropolis banner sign electronics vehicle comb light room skyscraper accessories adventure handbag cant keep lamppost phone palm protest silence crowd oppressed
Detected Text
iso
400
metering mode
5
aperture
f/2.8
focal length
16mm
shutter speed
1/6400s
camera make
Canon
camera model
lens model
date
2017-01-21T12:52:00-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(34.40%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.59%)
failure
(-0.39%)
harmonious color
(1.29%)
immersiveness
(0.85%)
interaction
(2.00%)
interesting subject
(-53.47%)
intrusive object presence
(-11.11%)
lively color
(4.03%)
low light
(9.69%)
noise
(-1.46%)
pleasant camera tilt
(-8.09%)
pleasant composition
(-84.08%)
pleasant lighting
(-19.46%)
pleasant pattern
(7.08%)
pleasant perspective
(-0.36%)
pleasant post processing
(0.07%)
pleasant reflection
(1.07%)
pleasant symmetry
(0.37%)
sharply focused subject
(0.49%)
tastefully blurred
(-11.77%)
well chosen subject
(9.02%)
well framed subject
(-74.95%)
well timed shot
(-0.30%)
all
(-3.62%)
* 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.