Photos | Mark Mangino Marches with Huge Crowd
The 2006 March in March, with Mark Mangino leading the way, draws a massive crowd of protestors down the city streets, carrying signs and setting a bold example for all.
BLIP-2 Description:
a large crowd of people walking down a streetChronologically Adjacent
Note: You can also navigate with your arrow keys or swiping.
Metadata
Capture date:
Original Dimensions:
3504w x 2336h - (download 4k)
Usage
Dominant Color:
accessories sun agend sto z vehicle shoe urban city march bicycle rights optometrist sign governor blame ie ball mo answe day transportation don't lasting answerla crowd sport hat immigrants fr protest flag wheel say dig students arnold no minute young footwear middle amnistía singels parade machine volleyball mark mangino full great text rty easte vote banner bri latinos (ball) vi metropolis glasses anos
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
(31.08%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.60%)
failure
(-0.10%)
harmonious color
(-2.47%)
immersiveness
(0.12%)
interaction
(1.00%)
interesting subject
(-43.21%)
intrusive object presence
(-15.65%)
lively color
(1.43%)
low light
(2.86%)
noise
(-1.27%)
pleasant camera tilt
(-10.50%)
pleasant composition
(-90.48%)
pleasant lighting
(-28.27%)
pleasant pattern
(5.86%)
pleasant perspective
(-0.90%)
pleasant post processing
(1.12%)
pleasant reflection
(-1.28%)
pleasant symmetry
(0.27%)
sharply focused subject
(0.17%)
tastefully blurred
(-10.61%)
well chosen subject
(6.99%)
well framed subject
(-65.04%)
well timed shot
(22.83%)
all
(-3.87%)
* 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 with AI (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.