Photos | Villa Resort Dining

A crowd of 32 people enjoy a summer meal at an indoor dining table near the pool at the Villa Resort in Ensenada, Mexico. The restaurant's architecture and foliage provide shelter and ambiance, while palm trees and other greenery remain visible through the building's large windows.
BLIP-2 Description:
a group of people sitting at tables near a poolMetadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
Location:
housing room shelter outdoors furniture rznn villa desk countryside potted dining baby hotel plant tree cafe futura summer rural old court indoors accessories bag zona photography mexico jewelry roof chair photos/futura_mexico building footwear cafeteria architecture crowd camera foliage hacienda food resort utensil bench palm portrait table junglescene restaurant handbag umbrella house bracelet hut centro hat nature electronics shoe
Detected Text
date
2002-09-23T10:50:20-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(27.91%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.57%)
failure
(-0.42%)
harmonious color
(-0.74%)
immersiveness
(1.83%)
interaction
(1.00%)
interesting subject
(-50.68%)
intrusive object presence
(-5.79%)
lively color
(-7.26%)
low light
(0.78%)
noise
(-10.52%)
pleasant camera tilt
(-8.28%)
pleasant composition
(-73.93%)
pleasant lighting
(-31.15%)
pleasant pattern
(8.50%)
pleasant perspective
(-1.40%)
pleasant post processing
(-2.33%)
pleasant reflection
(1.44%)
pleasant symmetry
(1.05%)
sharply focused subject
(0.39%)
tastefully blurred
(-4.65%)
well chosen subject
(4.79%)
well framed subject
(-56.54%)
well timed shot
(-2.06%)
all
(-5.59%)
* 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.