Photos | Lunch Date at the Diner
A man and a woman enjoy a meal together at a cozy diner, surrounded by furniture and plants. The dining table is set with plates, utensils, and glasses, as they chat and savor their food. In the background, a car and a couch can be seen, adding to the urban atmosphere of the restaurant.
BLIP-2 Description:
a man and a woman sitting at a table with a plate of foodChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
cutlery architecture pen dining room cafeteria spoon tableware pants urban plant building meal baseball portrait food cap dish transportation hat living dinner restaurant furniture utensil ice dessert bench diner old shirt junglescene queenlag indoors lunch glasses cream databass dining car vehicle fork table room accessories couch cafe plate potted photography cup shop
Detected Text
date
2002-09-15T15:00:11-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(32.84%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.75%)
failure
(-0.27%)
harmonious color
(-0.05%)
immersiveness
(0.17%)
interaction
(1.00%)
interesting subject
(-7.72%)
intrusive object presence
(-5.74%)
lively color
(-8.57%)
low light
(57.62%)
noise
(-16.06%)
pleasant camera tilt
(-5.68%)
pleasant composition
(-27.73%)
pleasant lighting
(-35.42%)
pleasant pattern
(11.50%)
pleasant perspective
(-4.95%)
pleasant post processing
(2.70%)
pleasant reflection
(-2.78%)
pleasant symmetry
(0.24%)
sharply focused subject
(0.56%)
tastefully blurred
(-7.43%)
well chosen subject
(-29.00%)
well framed subject
(26.05%)
well timed shot
(-2.65%)
all
(-3.77%)
* 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.