Photos | Students Take to the Streets

Priscilla Lopes-Schliep and Sulakshana Naik join a crowd of 19 people in a student protest, waving banners and 5 flags while sporting hats and clothing adorned with messages of protest.
BLIP-2 Description:
a group of people holding signs and flagsMetadata
Capture date:
Original Dimensions:
3504w x 2336h - (download 4k)
Usage
Dominant Color:
org activities headgear lopes flag worldcantwait immigrants plant leisure kos child student wait ring transportation hat girl la regime text performance sulakshana naik odrive wai agains art answerla amnisti ou world parade glasses full rekognition_c banner sign an't priscilla reside jewelry vehicle ww schliep ise www accessories adventure recreation bush right can't protest gra crowd drive
Detected Text
iso
100
metering mode
5
aperture
f/1.2
exposure bias
-0.67
focal length
85mm
shutter speed
1/8000s
camera make
Canon
camera model
lens model
date
2006-04-15T10:14:14-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(45.21%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.61%)
failure
(-0.20%)
harmonious color
(0.05%)
immersiveness
(0.12%)
interaction
(1.00%)
interesting subject
(-5.69%)
intrusive object presence
(-9.81%)
lively color
(13.77%)
low light
(9.62%)
noise
(-6.91%)
pleasant camera tilt
(-5.53%)
pleasant composition
(-57.57%)
pleasant lighting
(0.16%)
pleasant pattern
(6.54%)
pleasant perspective
(7.07%)
pleasant post processing
(4.52%)
pleasant reflection
(-1.09%)
pleasant symmetry
(0.49%)
sharply focused subject
(3.93%)
tastefully blurred
(25.90%)
well chosen subject
(-7.92%)
well framed subject
(-13.34%)
well timed shot
(7.07%)
all
(2.26%)
* 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.