Photos | Lunchtime Gathering
Five people enjoying a meal together at the dining table, surrounded by furniture and tableware, at an indoor dining room in a building. Three males and two boys are wearing baseball caps and casual clothing while eating from plates and drinking from cups with utensils.
BLIP-2 Description:
a group of people eating food at a tableChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
dish cutlery beverage photography cafeteria table dinner old shirt restaurant food pizza eating dining diner hat office dining table couch utensil furniture building architecture baseball fork lunch junglescene blade jeans buffet portrait breakfast tableware cap wood photos/hackers_and_my_office wristwatch cup meal knife weapon headgear boy teen spoon hackers brunch court plate tabletop plywood room indoors
Detected Text
date
2003-01-23T13:52:42-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(27.12%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.75%)
failure
(-0.59%)
harmonious color
(-0.05%)
immersiveness
(0.12%)
interaction
(1.00%)
interesting subject
(-26.05%)
intrusive object presence
(-12.26%)
lively color
(-9.83%)
low light
(33.76%)
noise
(-13.55%)
pleasant camera tilt
(-5.39%)
pleasant composition
(-63.67%)
pleasant lighting
(-44.63%)
pleasant pattern
(5.91%)
pleasant perspective
(-7.95%)
pleasant post processing
(0.67%)
pleasant reflection
(1.75%)
pleasant symmetry
(0.15%)
sharply focused subject
(0.32%)
tastefully blurred
(-26.76%)
well chosen subject
(-25.46%)
well framed subject
(-20.28%)
well timed shot
(-13.40%)
all
(-8.72%)
* 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.