Photos | The March of 57 People
A crowd of 57 people, including Julianna Gamiz, Kaan Aydogdu, and Jairzinho, make their way down a street in protest, sporting hats, handbags, and signs.
BLIP-2 Description:
a large crowd of people walking down a streetChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
3504w x 2336h - (download 4k)
Usage
Dominant Color:
bracelet org headgear necklace flag aydogdu legalizacion immigrants urban baseball ala footwear cap rights natalia anciso hat crowd contacto text performance ahora esi shoe bag alto city usa julianna gamiz un answerla inmigrantes parade camera glasses full metropolis contra sign electronics banner punto vera jewelry accessories recreation optome handbag calie jairzinho hecho kaan protest bai anteojos march migrantes yang
Detected Text
iso
100
metering mode
5
aperture
f/4
focal length
17mm
shutter speed
1/1000s
camera make
Canon
camera model
lens model
date
2006-03-25T10:47:00-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(25.61%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.54%)
failure
(-0.29%)
harmonious color
(-2.04%)
immersiveness
(0.22%)
interaction
(1.00%)
interesting subject
(-57.03%)
intrusive object presence
(-22.36%)
lively color
(3.05%)
low light
(3.83%)
noise
(-2.37%)
pleasant camera tilt
(-9.97%)
pleasant composition
(-92.14%)
pleasant lighting
(-32.91%)
pleasant pattern
(4.13%)
pleasant perspective
(-7.28%)
pleasant post processing
(3.59%)
pleasant reflection
(-0.90%)
pleasant symmetry
(0.20%)
sharply focused subject
(0.20%)
tastefully blurred
(-12.88%)
well chosen subject
(12.76%)
well framed subject
(-76.27%)
well timed shot
(9.30%)
all
(-6.01%)
* 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.