Photos | Dining with Friends
A group of four friends laugh and enjoy a meal together at a restaurant. The elegant dining table and comfortable furniture provide the backdrop for this joyful portrait.
BLIP-2 Description:
a man and a womanChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
spoon couch room drinking urban furniture potted dining dining room photobombing hardware screen part tableware laughing happy plant cafe glass indoors accessories beverage cabinet photography shirt bree diner lunch dish pub pants glasses building cafeteria architecture food monitor beer utensil portrait bar table dinner cutlery bride cup restaurant alcohol meal bar counter computer electronics wedding
flash fired
true
iso
105
metering mode
5
aperture
f/5.6
focal length
6mm
shutter speed
1/30s
camera make
OLYMPUS OPTICAL CO.,LTD
camera model
date
2006-05-28T23:34:26-07:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(33.86%)
curation
(65.82%)
highlight visibility
(5.72%)
behavioral
(90.75%)
failure
(-0.34%)
harmonious color
(-1.41%)
immersiveness
(0.05%)
interaction
(1.00%)
interesting subject
(22.22%)
intrusive object presence
(-11.87%)
lively color
(-15.10%)
low light
(96.78%)
noise
(-6.08%)
pleasant camera tilt
(-4.82%)
pleasant composition
(-43.77%)
pleasant lighting
(-48.41%)
pleasant pattern
(4.37%)
pleasant perspective
(2.80%)
pleasant post processing
(-1.92%)
pleasant reflection
(-0.30%)
pleasant symmetry
(0.29%)
sharply focused subject
(0.76%)
tastefully blurred
(-15.47%)
well chosen subject
(-48.41%)
well framed subject
(27.03%)
well timed shot
(9.78%)
all
(-5.81%)
* 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.