Photos | Intersection Crossing in San Francisco
Matsuko Deluxe and 26 others navigate through a crowded intersection in San Francisco on a cloudy day. Cars, buses, motorcycles and bicycles all present as vehicles compete with pedestrians for space.
BLIP-2 Description:
a group of people are crossing the street at an intersectionChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
3024w x 4032h - (download 4k)
Usage
Dominant Color:
Location:
tarmac path machine city urban asphalt intersection vehicle car matsuko sky bicycle transportation mission lane bag accessories sidewalk helmet traffic outdoor street road footwear zebra district automobile light metropolis pedestrian handbag bus crossing deluxe rekognition_c land cloudy motorcycle neighborhood crosswalk shoe
iso
125
metering mode
5
aperture
f/2.4
focal length
2mm
latitude
37.76
longitude
-122.42
shutter speed
1/120s
camera make
Apple
camera model
date
2020-01-18T17:10:53.788000-08:00
tzoffset
-28800
tzname
GMT-0800
overall
(43.12%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.56%)
failure
(-1.03%)
harmonious color
(-0.57%)
immersiveness
(5.93%)
interaction
(1.00%)
interesting subject
(-36.96%)
intrusive object presence
(-5.47%)
lively color
(1.67%)
low light
(13.89%)
noise
(-1.81%)
pleasant camera tilt
(-4.38%)
pleasant composition
(-21.25%)
pleasant lighting
(-18.92%)
pleasant pattern
(8.54%)
pleasant perspective
(12.92%)
pleasant post processing
(2.34%)
pleasant reflection
(5.37%)
pleasant symmetry
(0.98%)
sharply focused subject
(0.59%)
tastefully blurred
(-5.29%)
well chosen subject
(-10.89%)
well framed subject
(-20.50%)
well timed shot
(1.55%)
all
(2.76%)
* 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.