Photos | Women Marching for Equality
A crowd of around 59 people, including men, women and children, protesting for their rights under a blue sky and cloudy weather in Washington DC on January 21, 2017. Arundhati Kirkire holds a banner with skyscrapers and palm trees in the background.
BLIP-2 Description:
a large crowd of people holding signs and protestingMetadata
Capture date:
Original Dimensions:
5760w x 3840h - (download 4k)
Usage
Dominant Color:
urban womens oppressed flag phone silence glasses child palm outdoor mobile footwear bag leisure arundhati kirkire respect sky coachella activities xing tree city protest patriarchy concert building skyscraper ge flick sign place electronics shoe handbag viol cloudy boy adventure plant parade metropolis ped resistance hat text blue light pre traffic banner audience existen lamppost headgear expect accessories crowd
Detected Text
iso
400
metering mode
5
aperture
f/2.8
focal length
16mm
shutter speed
1/8000s
camera make
Canon
camera model
lens model
overall
(33.18%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.73%)
failure
(-0.51%)
harmonious color
(1.15%)
immersiveness
(1.00%)
interaction
(1.00%)
interesting subject
(-62.16%)
intrusive object presence
(-12.70%)
lively color
(4.96%)
low light
(8.25%)
noise
(-1.73%)
pleasant camera tilt
(-9.99%)
pleasant composition
(-80.52%)
pleasant lighting
(-16.80%)
pleasant pattern
(5.08%)
pleasant perspective
(1.97%)
pleasant post processing
(1.64%)
pleasant reflection
(-0.66%)
pleasant symmetry
(0.29%)
sharply focused subject
(0.39%)
tastefully blurred
(-5.68%)
well chosen subject
(9.78%)
well framed subject
(-68.07%)
well timed shot
(-1.16%)
all
(-3.15%)
* 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.