Photos | Metropolis Building Advertisement

Jack Tempchin and Nolan Gould stand in front of a large building with a prominent advertisement on the sign in downtown Metropolis.
BLIP-2 Description:
a large building with a sign on itMetadata
Capture date:
Original Dimensions:
2912w x 4368h - (download 4k)
Usage
Dominant Color:
tarmac path press city min urban furniture outdoors train nolan tacos express intersection car aids day vehicle hotel station los lamppost transportation storefront wristwatch downtown indoors parking accessories sidewalk sign window area outdoor street bus stop road sa glasses building architecture banner walk brient bench ant shoot light text office metropolis coat gould el hd angeles restaurant terminal railway bus land town advertisement neighborhood jack tempchin symbol
Detected Text
iso
100
metering mode
5
aperture
f/2.8
focal length
35mm
shutter speed
1/1000s
camera make
Canon
camera model
lens model
date
2008-10-04T10:53:54-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(28.56%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.62%)
failure
(-0.24%)
harmonious color
(-0.03%)
immersiveness
(0.37%)
interaction
(1.00%)
interesting subject
(-58.54%)
intrusive object presence
(-10.84%)
lively color
(-2.15%)
low light
(4.59%)
noise
(-1.17%)
pleasant camera tilt
(-16.27%)
pleasant composition
(-77.15%)
pleasant lighting
(-31.47%)
pleasant pattern
(15.36%)
pleasant perspective
(-1.09%)
pleasant post processing
(2.73%)
pleasant reflection
(-3.50%)
pleasant symmetry
(1.54%)
sharply focused subject
(0.27%)
tastefully blurred
(-1.53%)
well chosen subject
(6.13%)
well framed subject
(-44.19%)
well timed shot
(-1.07%)
all
(-5.19%)
* 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.