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
Note: You can also navigate with your arrow keys or swiping.
Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
urban couch night plate party restaurant glasses portrait chillin dinner court teen interior peeps food cafeteria container chair table building lunch pub junglescene tableware lori alx dining table boy bday glass bar room bar counter plant dish lori_bday_dinner-lori_bday_dinner eating sushi cup beverage tabletop architecture meal utensil bottle furniture club alcohol accessories photography fun indoors dining crowd
Detected Text
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.