Photos | The Crowd at the Stadium
Kiran Manisha Mohanty and Masaaki Satake walk amidst a diverse crowd outside of Levi's Stadium in Santa Clara, California, as the sky glows with the colors of sunset.
BLIP-2 Description:
a crowd of people walking in front of a stadiumChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
3024w x 4032h - (download 4k)
Usage
Dominant Color:
Location:
urban flag street phone portrait glasses transportation animal cap outdoor toyota arena shirt hoodie girl bird footwear sunlight © toyoti sun teen um jacket sky fence city masaaki car concert building mobile phone sunset lighting bicycle glove outdoors electronics shoe nature faithful coat kiran manisha mohanty helmet satake stadium wristwatch faithin road vehicle sunrise architecture blue hat baseball light traffic audience accessories photography headgear shelter crowd
iso
32
metering mode
5
aperture
f/1.8
focal length
4mm
latitude
37.41
longitude
-121.97
shutter speed
1/1379s
camera make
Apple
camera model
overall
(38.50%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.78%)
failure
(-0.61%)
harmonious color
(2.31%)
immersiveness
(0.78%)
interaction
(1.00%)
interesting subject
(-32.08%)
intrusive object presence
(-3.44%)
lively color
(-3.13%)
low light
(33.59%)
noise
(-3.66%)
pleasant camera tilt
(-11.19%)
pleasant composition
(-51.32%)
pleasant lighting
(-37.38%)
pleasant pattern
(12.87%)
pleasant perspective
(-6.30%)
pleasant post processing
(6.49%)
pleasant reflection
(-2.10%)
pleasant symmetry
(0.49%)
sharply focused subject
(0.37%)
tastefully blurred
(0.27%)
well chosen subject
(-21.26%)
well framed subject
(-41.06%)
well timed shot
(-2.40%)
all
(-4.05%)
* 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.