Photos | Women's March in the City
Silvia Giner, Megumi Fujii, Jan Friesinger, and Hideo Nakata join the massive crowd in the street holding empowering signs during the Women's March in the city on January 21, 2017.
BLIP-2 Description:
a large group of people holding signs in the streetMetadata
Capture date:
Original Dimensions:
5760w x 3840h - (download 4k)
Usage
urban compassion hetero white rekognition_c recreation cience womens cut bracelet silence glasses transportation choke outdoor girl bag vegan hideo nakata leisure teen humanity sky st vast coachella megumi fujii activities city fuck jewelry protest document car grabs building skyscraper say sign shit ove handbag protect carnist pus adventure smash friesinger parade metropolis silvia vehicle performance blue hat rights text light handwriting pre traffic banner jan accessories giner kun crowd
Detected Text
iso
400
metering mode
5
aperture
f/7.1
focal length
25mm
shutter speed
1/1250s
camera make
Canon
camera model
lens model
overall
(35.84%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.65%)
failure
(-0.15%)
harmonious color
(1.42%)
immersiveness
(0.39%)
interaction
(1.00%)
interesting subject
(-36.72%)
intrusive object presence
(-8.18%)
lively color
(16.48%)
low light
(10.01%)
noise
(-2.05%)
pleasant camera tilt
(-7.39%)
pleasant composition
(-79.44%)
pleasant lighting
(-7.01%)
pleasant pattern
(7.30%)
pleasant perspective
(4.70%)
pleasant post processing
(0.67%)
pleasant reflection
(1.01%)
pleasant symmetry
(0.39%)
sharply focused subject
(0.54%)
tastefully blurred
(-6.02%)
well chosen subject
(-13.48%)
well framed subject
(-59.13%)
well timed shot
(7.47%)
all
(-1.17%)
* 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.