Photos | Dining with Lori and Friends
22 people gather around a dining table at a restaurant, enjoying a meal together with bottles, containers, utensils, and tableware. The warm and cozy interior room is decorated with furniture and two plants, while the crowd sits on chairs and other accessories.
BLIP-2 Description:
a group of people sitting at a table eatingChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
architecture dining table glass cafeteria boy tableware peeps urban plant building meal pub food chair portrait bar beverage dish chillin dinner restaurant furniture utensil court container party eating fun lori_bday_dinner-lori_bday_dinner club alcohol junglescene indoors lunch teen glasses tabletop dining bar counter sushi interior table room accessories lori night couch plate photography alx cup bday crowd bottle
Detected Text
date
2002-08-29T13:35:47-07:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(22.84%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.52%)
failure
(-0.71%)
harmonious color
(-1.55%)
immersiveness
(0.07%)
interaction
(1.00%)
interesting subject
(-52.39%)
intrusive object presence
(-11.67%)
lively color
(-8.52%)
low light
(97.61%)
noise
(-4.47%)
pleasant camera tilt
(-8.18%)
pleasant composition
(-90.63%)
pleasant lighting
(-74.37%)
pleasant pattern
(2.86%)
pleasant perspective
(-6.05%)
pleasant post processing
(4.09%)
pleasant reflection
(3.18%)
pleasant symmetry
(0.05%)
sharply focused subject
(0.10%)
tastefully blurred
(-20.73%)
well chosen subject
(-16.53%)
well framed subject
(-55.76%)
well timed shot
(-4.19%)
all
(-12.14%)
* 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.