Photos | March for Change
A diverse group of 47 people march through the streets, holding signs and waving flags, as they advocate for change in their community. Lachlan Sharp and Louie Austen join the parade, wearing expressive clothing and accessories, while a young boy dribbles a basketball alongside them.
BLIP-2 Description:
a large group of people holding signs and flagsMetadata
Capture date:
Original Dimensions:
3504w x 2336h - (download 4k)
Usage
Dominant Color:
united flag rante backpack recreation rekognition_c idas stand glasses child ner bracelet shirt hr footwear bag louie austen lisacion march bill sharp indo crowd bili protest intra jewelry hope anos sign legia novas shoe handbag lachlan boy (ball) parade ball wristwatch belt performance alto life im todos para hat text sport created king banner accessories basketball cha art california
Detected Text
iso
100
metering mode
5
aperture
f/4
focal length
17mm
shutter speed
1/1000s
camera make
Canon
camera model
lens model
overall
(25.42%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.68%)
failure
(-0.17%)
harmonious color
(-2.24%)
immersiveness
(0.07%)
interaction
(1.00%)
interesting subject
(-56.05%)
intrusive object presence
(-17.41%)
lively color
(-2.49%)
low light
(5.79%)
noise
(-2.22%)
pleasant camera tilt
(-11.83%)
pleasant composition
(-95.56%)
pleasant lighting
(-38.65%)
pleasant pattern
(2.44%)
pleasant perspective
(-5.01%)
pleasant post processing
(1.14%)
pleasant reflection
(-1.07%)
pleasant symmetry
(0.12%)
sharply focused subject
(0.17%)
tastefully blurred
(-12.35%)
well chosen subject
(-5.78%)
well framed subject
(-70.21%)
well timed shot
(13.26%)
all
(-7.49%)
* 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.