Photos | May Day Rally

A crowd of 26 people, including Sunita Singh and Ñengo Flow, gather on the street holding signs and flags in protest during the May Day rally in 2008. The blue sky and outdoor setting provide a scenic background for the performance.
BLIP-2 Description:
a group of people holding signs and flags in a streetMetadata
Capture date:
Original Dimensions:
4368w x 2912h - (download 4k)
Usage
traffic hos dividing flag division footwear sind rights transportation hat crowd road outdoor la mayday_rally text performance sky shoe coaltion families echos land son sunita singh art machine inmigrantes jadores familias parade glasses derechos wheel banner sign trabajadores rally vehicle light accessories las ñengo recreation unity mayday protest day worker de flow antes immigrant
Detected Text
iso
100
metering mode
5
aperture
f/7.1
focal length
16mm
shutter speed
1/400s
camera make
Canon
camera model
lens model
date
2008-05-01T12:12:32-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(36.50%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.72%)
failure
(-0.12%)
harmonious color
(-0.37%)
immersiveness
(0.51%)
interaction
(1.00%)
interesting subject
(-30.10%)
intrusive object presence
(-5.98%)
lively color
(18.26%)
low light
(0.61%)
noise
(-0.46%)
pleasant camera tilt
(-10.70%)
pleasant composition
(-78.91%)
pleasant lighting
(-12.55%)
pleasant pattern
(7.52%)
pleasant perspective
(-6.28%)
pleasant post processing
(0.44%)
pleasant reflection
(4.53%)
pleasant symmetry
(0.24%)
sharply focused subject
(0.49%)
tastefully blurred
(5.17%)
well chosen subject
(-20.68%)
well framed subject
(-54.15%)
well timed shot
(4.50%)
all
(-2.64%)
* 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.