Photos | Dining with Friends
Two women and a man sit around a table enjoying a meal, while a fourth person checks their phone. The dining room is filled with furniture and decor, including a china cabinet and cabinets filled with glasses and plates.
BLIP-2 Description:
a couple of people sitting at a tableChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
lighting jacket couch room cap furniture desk remote dining dining room hardware wear screen sink tv mammal formal indoors accessories cabinet bag photography beverage baseball video jewelry animal shelf chair pants plate glasses building camera architecture old_eecue food monitor pet dog cupboard faucet portrait suit table mobile phone cup restaurant alcohol meal closet computer handbag control living canine interior design door hat electronics necklace china coat
date
2003-03-24T16:10:47-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(24.38%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.72%)
failure
(-0.83%)
harmonious color
(0.91%)
immersiveness
(0.17%)
interaction
(1.00%)
interesting subject
(-48.34%)
intrusive object presence
(-7.32%)
lively color
(-14.55%)
low light
(73.93%)
noise
(-8.42%)
pleasant camera tilt
(-11.05%)
pleasant composition
(-75.10%)
pleasant lighting
(-49.15%)
pleasant pattern
(7.40%)
pleasant perspective
(-7.17%)
pleasant post processing
(0.21%)
pleasant reflection
(-4.32%)
pleasant symmetry
(0.22%)
sharply focused subject
(0.27%)
tastefully blurred
(-19.46%)
well chosen subject
(-37.67%)
well framed subject
(-35.28%)
well timed shot
(-8.08%)
all
(-10.70%)
* 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.