Photos | Mayday Rally Marches Through Metropolis

A diverse crowd of 36 people, including 2 women, 2 men, and 2 helmets, walk down a city street adorned with billboards and storefronts during the 2008 Mayday Rally. Blue skies and towering buildings frame the scene as accessories and footwear add personal touches to the urban landscape.
BLIP-2 Description:
a group of people walking down the street in a cityMetadata
Capture date:
Original Dimensions:
4368w x 2912h - (download 4k)
Usage
Dominant Color:
flag neighborhood urban sha building window footwear belleza barber wercedes pedestrian area sidewalk luggage hat escuela vocation mercedes road outdoor studio tuxedos mayday_rally intersection costura text sky container co tarmac city shoe land bag street completo storefront overlock shorts school una beauty path lease metropolis helmet billboards sign banner por servicio rekognition_c hie salon rally zebra accessories goleth's crossing unisex aguia handbag oto town walking mayday scuela tur se advertisement de shop crowd
Detected Text
iso
100
metering mode
5
aperture
f/6.3
exposure bias
-1
focal length
16mm
shutter speed
1/400s
camera make
Canon
camera model
lens model
date
2008-05-01T16:01:17-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(31.18%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.61%)
failure
(-0.49%)
harmonious color
(2.73%)
immersiveness
(0.71%)
interaction
(1.00%)
interesting subject
(-56.88%)
intrusive object presence
(-16.60%)
lively color
(-5.77%)
low light
(70.65%)
noise
(-2.54%)
pleasant camera tilt
(-7.98%)
pleasant composition
(-87.35%)
pleasant lighting
(-44.80%)
pleasant pattern
(4.69%)
pleasant perspective
(-0.50%)
pleasant post processing
(4.85%)
pleasant reflection
(2.45%)
pleasant symmetry
(0.44%)
sharply focused subject
(0.34%)
tastefully blurred
(-9.73%)
well chosen subject
(-23.50%)
well framed subject
(-53.32%)
well timed shot
(4.17%)
all
(-7.17%)
* 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.