Photos | March for Change
A large crowd of protesters take to the streets, holding signs and chanting for justice and equality. Clarence Delgado, Natasha Leggero, Newton Thomas Sigel, B-Real, Gerina Piller, and Vani Kapoor are among the 86 people marching for a better future.
BLIP-2 Description:
a large group of people walking down a street with signsMetadata
Capture date:
Original Dimensions:
3504w x 2336h - (download 4k)
Usage
Dominant Color:
urban leggero flag clarence delgado recreation young racis glasses child outdoor org vani footwear bag sun march necklace city full jewelry protest natasha lia optometrist vias anos sign shoe handbag credito gerina piller answerla enemy boy parade solution wristwatch road metropolis real performance alto fradkin hat rights part angels text kapoor banner comite newton thomas sigel accessories latino immigrants crowd dr land
Detected Text
iso
400
metering mode
5
aperture
f/14
focal length
17mm
shutter speed
1/400s
camera make
Canon
camera model
lens model
overall
(27.66%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.56%)
failure
(-0.17%)
harmonious color
(-4.06%)
immersiveness
(0.15%)
interaction
(1.00%)
interesting subject
(-47.41%)
intrusive object presence
(-5.83%)
lively color
(3.13%)
low light
(8.08%)
noise
(-2.37%)
pleasant camera tilt
(-10.44%)
pleasant composition
(-89.06%)
pleasant lighting
(-28.30%)
pleasant pattern
(4.52%)
pleasant perspective
(-8.53%)
pleasant post processing
(1.02%)
pleasant reflection
(-4.37%)
pleasant symmetry
(0.22%)
sharply focused subject
(0.15%)
tastefully blurred
(-12.87%)
well chosen subject
(11.38%)
well framed subject
(-70.70%)
well timed shot
(11.77%)
all
(-5.71%)
* 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.