Photos | Metropolis in Motion
Durga Shakti Nagpal leads a crowd of 59 people through the bustling city streets, accompanied by the glow of 4 traffic lights and 3 flags fluttering in the breeze. Accessories, shoes, and clothing of all varieties mix with the symbols and texts of 4 road signs in a visual spectacle of urban life.
BLIP-2 Description:
a large crowd of people walking down a streetChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
3504w x 2336h - (download 4k)
Usage
urban flag street white dosha glasses outdoor footwear bag loose certified park st way crowd ng pedestrian eastern durga shakti nagpal city shop instant wa sign sdzon shoe handbag interes anceles urban area los parade metropolis road belt astmmmc symbol diamonds hat platium light angeles diamantes gold banner text traffic bancom undtu accessories ne ono art one land
Detected Text
flash fired
true
iso
100
metering mode
5
aperture
f/5.6
focal length
66mm
shutter speed
1/500s
camera make
Canon
camera model
lens model
overall
(34.16%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.50%)
failure
(-0.17%)
harmonious color
(-1.47%)
immersiveness
(0.44%)
interaction
(1.00%)
interesting subject
(-55.52%)
intrusive object presence
(-17.02%)
lively color
(-2.55%)
low light
(2.32%)
noise
(-1.22%)
pleasant camera tilt
(-10.06%)
pleasant composition
(-88.96%)
pleasant lighting
(-20.68%)
pleasant pattern
(6.01%)
pleasant perspective
(2.38%)
pleasant post processing
(2.73%)
pleasant reflection
(-2.53%)
pleasant symmetry
(0.68%)
sharply focused subject
(0.24%)
tastefully blurred
(-6.89%)
well chosen subject
(13.33%)
well framed subject
(-66.85%)
well timed shot
(9.75%)
all
(-3.55%)
* 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.