Photos | Cartoon Mural on City Building

Kazuya Minekura captures the colorful artwork of a cartoon character on a building in Los Angeles.
BLIP-2 Description:
a mural of a cartoon character on the side of a buildingMetadata
Capture date:
Original Dimensions:
4032w x 3024h - (download 4k)
Usage
Dominant Color:
Location:
west lighting path machine wheel city urban outdoors mural hydrant baby intersection car vehicle day entrance sky symbol fire minutes lamppost transportation sat stop public parking accessories sidewalk sign bureau violation 赏 outdoor street sun pm road jewelry media night maximum glasses building footwear architecture skyscraper kazuya minekura flat district wall water convenient light courthouse metropolis advertising painting bus traffic land advertisement art nature 爾 shoe
Detected Text
iso
100
metering mode
5
aperture
f/1.8
focal length
4mm
shutter speed
1/6s
camera make
Apple
camera model
lens model
date
2017-07-28T23:32:09.464000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(34.30%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.58%)
failure
(-0.56%)
harmonious color
(0.93%)
immersiveness
(0.46%)
interaction
(1.00%)
interesting subject
(-49.58%)
intrusive object presence
(-2.69%)
lively color
(-13.70%)
low light
(97.17%)
noise
(-4.69%)
pleasant camera tilt
(-6.63%)
pleasant composition
(-37.30%)
pleasant lighting
(-41.24%)
pleasant pattern
(8.69%)
pleasant perspective
(7.07%)
pleasant post processing
(1.50%)
pleasant reflection
(-2.52%)
pleasant symmetry
(1.12%)
sharply focused subject
(0.44%)
tastefully blurred
(-9.52%)
well chosen subject
(-13.68%)
well framed subject
(-18.19%)
well timed shot
(1.80%)
all
(-3.31%)
* 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.