Photos | Urban Exploration in Fort Mason
Capturing a dynamic cityscape in Fort Mason on December 10th, 2023. The multi-faceted scene not only emphasizes diverse city life, with the focus on a lone car parked in the hustle and bustle, but also highlights the architectural aesthetics of the building in view. Smriti Mehra, amongst the busy crowd, cherishes this vibrant urban canvas.
BLIP-2 Description:
a parking lot with a car parked in front of a buildingMetadata
Capture date:
Original Dimensions:
6000w x 4000h - (download 4k)
Usage
Dominant Color:
urban street fort lamp plate restaurant glasses transportation outdoor eek footwear window motorcycle path parking stop cafeteria chair city automobile car sidewalk building table smriti mehra license sign bicycle intersection shoe desk tarmac neighborhood mason office cafe road vehicle symbol architecture machine hat furniture accessories indoors walking land
iso
1250
metering mode
5
aperture
f/13
focal length
600mm
shutter speed
1/250s
camera make
Canon
camera model
overall
(41.75%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.63%)
failure
(-0.39%)
harmonious color
(0.33%)
immersiveness
(1.07%)
interaction
(1.00%)
interesting subject
(-56.20%)
intrusive object presence
(-3.78%)
lively color
(-12.78%)
low light
(2.27%)
noise
(-0.76%)
pleasant camera tilt
(-9.52%)
pleasant composition
(-54.88%)
pleasant lighting
(-10.60%)
pleasant pattern
(8.11%)
pleasant perspective
(10.43%)
pleasant post processing
(3.10%)
pleasant reflection
(-5.23%)
pleasant symmetry
(3.47%)
sharply focused subject
(0.44%)
tastefully blurred
(0.27%)
well chosen subject
(0.55%)
well framed subject
(-47.05%)
well timed shot
(8.03%)
all
(0.13%)
* 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-4-0613
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.