Photos | Brick Wall Portrait

A man and woman sit next to each other in front of a brick wall at Cinespace Tuesday. They are dressed in jackets and blazers, with the woman wearing glasses and the man sporting sunglasses.
BLIP-2 Description:
a man and woman sitting next to each otherMetadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
architecture tie brick door selfie pants necklace formal urban wall fall building portrait sweater november fireplace jacket cinespace ex tuesday hardware shirt coat glasses indoors teeth mouth wear sunglasses electronics jewelry screen accessories monitor blouse earring cinespace_tuesday blazer t-shirt part laughing photography smile happy computer undershirt knitwear
flash fired
true
metering mode
5
aperture
f/2.5
focal length
6mm
shutter speed
1/4s
camera make
CASIO COMPUTER CO.,LTD.
camera model
date
2003-11-18T13:26:37-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(38.75%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.47%)
failure
(-0.22%)
harmonious color
(0.09%)
immersiveness
(0.34%)
interaction
(1.00%)
interesting subject
(17.55%)
intrusive object presence
(-28.74%)
lively color
(-10.05%)
low light
(42.09%)
noise
(-13.16%)
pleasant camera tilt
(-3.90%)
pleasant composition
(-34.89%)
pleasant lighting
(-23.11%)
pleasant pattern
(5.32%)
pleasant perspective
(-1.37%)
pleasant post processing
(2.12%)
pleasant reflection
(-3.17%)
pleasant symmetry
(0.78%)
sharply focused subject
(1.03%)
tastefully blurred
(0.32%)
well chosen subject
(-23.05%)
well framed subject
(51.86%)
well timed shot
(6.92%)
all
(-1.64%)
* NOTE: This image was scaled up from its original size using an AI model called GFP-GAN (Generative Facial Prior), which is a
Generative adversartial network that can be used to repair (or upscale in this case) photos, sometimes the results are a little...
weird.
* 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.