Photos | Mayday Rally in Metropolis
Priscilla Lopes-Schliep and Carlos Saucedo lead a crowd of 72 people down a busy urban street during the 2008 Mayday Rally in Metropolis. The group marches past towering buildings, lush greenspace, and bustling traffic lights.
BLIP-2 Description:
a large group of people walking down a streetChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
3888w x 2592h - (download 4k)
Usage
Dominant Color:
architecture carlos handrail urban plant building fence footwear kiwa stairs pedestrian transportation hat road mayday_rally house text traffic city bag shoe saucedo glove parade audience bicycle metropolis shrub banner gol rally vehicle light workers migrant accessories handbag os housing mayday inmigrant onomy staircase crowd priscilla lopes-schliep
iso
400
metering mode
5
aperture
f/2.8
focal length
70mm
shutter speed
1/6400s
camera make
Canon
camera model
lens model
date
2008-05-01T14:48:52.590000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(35.77%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.41%)
failure
(-0.46%)
harmonious color
(1.12%)
immersiveness
(0.81%)
interaction
(1.00%)
interesting subject
(-22.63%)
intrusive object presence
(-6.40%)
lively color
(1.27%)
low light
(8.20%)
noise
(-4.08%)
pleasant camera tilt
(-5.51%)
pleasant composition
(-63.33%)
pleasant lighting
(-11.44%)
pleasant pattern
(17.82%)
pleasant perspective
(10.97%)
pleasant post processing
(-0.40%)
pleasant reflection
(-2.47%)
pleasant symmetry
(1.34%)
sharply focused subject
(0.61%)
tastefully blurred
(-4.33%)
well chosen subject
(2.19%)
well framed subject
(-49.66%)
well timed shot
(9.86%)
all
(0.04%)
* 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.