Photos | City Parade

Hiroyuki Kaiō and Sreelakshmi Suresh join the crowd of 52 people marching through the busy city streets during the annual Metropolis festival. The photo captures the vibrant energy of the parade, with its colorful banners, traffic lights, and towering architecture all around.
BLIP-2 Description:
a large group of peopleMetadata
Capture date:
Original Dimensions:
3504w x 2336h - (download 4k)
Usage
Dominant Color:
architecture foro urban building window cr mayoreo footwear festival tipp pedestrian wholesale area hat montebello road outdoor tel gold ela traffic city jiamand pann shoe land bag street hiroyuki kaiō elefante bro dave parade garantizado metropolis sign ay light marching sreelakshmi accessories diamante handbag metrd walking centro cols suresh de shop crowd
Detected Text
flash fired
true
iso
100
metering mode
5
aperture
f/4
focal length
17mm
shutter speed
1/800s
camera make
Canon
camera model
lens model
date
2006-05-01T11:27:20-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(32.35%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.42%)
failure
(-0.15%)
harmonious color
(0.29%)
immersiveness
(0.78%)
interaction
(1.00%)
interesting subject
(-57.23%)
intrusive object presence
(-9.47%)
lively color
(-10.83%)
low light
(3.15%)
noise
(-0.68%)
pleasant camera tilt
(-12.52%)
pleasant composition
(-83.89%)
pleasant lighting
(-30.52%)
pleasant pattern
(8.74%)
pleasant perspective
(8.19%)
pleasant post processing
(2.09%)
pleasant reflection
(-0.17%)
pleasant symmetry
(0.83%)
sharply focused subject
(0.12%)
tastefully blurred
(-8.78%)
well chosen subject
(14.44%)
well framed subject
(-64.45%)
well timed shot
(9.52%)
all
(-3.85%)
* 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.