Photos | Women's March in the Metropolis
Daniela Anschütz-Thoms, Fusae Ōta, Tatsuya Tanaka and a crowd of 50 people hold signs and protest in front of a skyscraper in the heart of the city during the 2017 Women's March.
BLIP-2 Description:
a large group of people holding signs in the streetChronologically Adjacent
Note: You can also navigate with your arrow keys or swiping.
Metadata
Capture date:
Original Dimensions:
5760w x 3840h - (download 4k)
Usage
Dominant Color:
protest city urban tatsuya tanaka womens pre sky shoe ōta coachella acceling bag accessories ou traffic outdoor cante glasses building footwear architecture crowd skyscraper omb parade audience office light metropolis fusae oppressed bride handbag chargi daniela anschütz-thoms change xing cloudy hat ped wedding things
iso
400
metering mode
5
aperture
f/2.8
focal length
16mm
shutter speed
1/8000s
camera make
Canon
camera model
lens model
date
2017-01-21T12:52:02.940000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(31.88%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.63%)
failure
(-0.20%)
harmonious color
(2.98%)
immersiveness
(0.59%)
interaction
(1.00%)
interesting subject
(-61.47%)
intrusive object presence
(-12.65%)
lively color
(14.10%)
low light
(1.98%)
noise
(-0.68%)
pleasant camera tilt
(-12.37%)
pleasant composition
(-88.77%)
pleasant lighting
(-17.71%)
pleasant pattern
(6.13%)
pleasant perspective
(0.33%)
pleasant post processing
(-2.15%)
pleasant reflection
(-1.18%)
pleasant symmetry
(0.17%)
sharply focused subject
(0.24%)
tastefully blurred
(-7.89%)
well chosen subject
(10.41%)
well framed subject
(-67.68%)
well timed shot
(-1.22%)
all
(-3.74%)
* 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.