Photos | Group Photo in the City

Ni Hua and a crowd of 28 people pose in front of a graffiti-covered building on a sunny day in San Francisco. The vibrant urban scene includes speakers blasting music, a traffic light in the background, and a mixture of casual clothing and tattoos on the diverse group.
BLIP-2 Description:
a group of people taking a photo in front of a buildingMetadata
Capture date:
Original Dimensions:
3024w x 4032h - (download 4k)
Usage
Dominant Color:
Location:
skin jeans pants neighborhood urban graffiti music mobile footwear cap transportation wristwatch hat girl road outdoor baseball cap sky container bag shoe city traffic land street art glasses teen soma metropolis electronics backpack car vehicle light accessories tattoo speakers wallet part phone crowd ni hua box
Detected Text
iso
100
metering mode
5
aperture
f/1.8
focal length
4mm
latitude
37.78
longitude
-122.4
shutter speed
1/121s
camera make
Apple
camera model
lens model
date
2019-08-15T19:52:56.517000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(45.41%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.73%)
failure
(-0.10%)
harmonious color
(1.39%)
immersiveness
(0.27%)
interaction
(1.00%)
interesting subject
(26.66%)
intrusive object presence
(-5.32%)
lively color
(-3.58%)
low light
(4.03%)
noise
(-2.34%)
pleasant camera tilt
(-7.60%)
pleasant composition
(-54.35%)
pleasant lighting
(-8.30%)
pleasant pattern
(5.62%)
pleasant perspective
(10.45%)
pleasant post processing
(1.51%)
pleasant reflection
(0.97%)
pleasant symmetry
(0.44%)
sharply focused subject
(0.88%)
tastefully blurred
(-0.75%)
well chosen subject
(-32.86%)
well framed subject
(2.00%)
well timed shot
(15.86%)
all
(0.75%)
* 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.