Photos | Lunch Gathering in the City
Álex Cruz, Courtney Kennedy, and Grace C joined a group of 22 people for a delicious meal at a crowded restaurant in the heart of the city. With a variety of dishes and drinks on the table, the atmosphere was lively and full of energy.
BLIP-2 Description:
a group of people in a restaurantMetadata
Capture date:
Original Dimensions:
3088w x 2320h - (download 4k)
Usage
Dominant Color:
urban countryside plate restaurant glasses portrait transportation shirt athletics cream dave grace c camera dinner bread bag court ben no food necklace cafeteria pacifico courtney icing jewelry car please table building lunch pub sign electronics outdoors handbag nature dessert neighborhood scissors hut roots room fico dish rural cafe undershirt cup dining room vehicle architecture hat meal álex cruz furniture kennedy accessories photography dining indoors shelter crowd
iso
100
metering mode
5
aperture
f/2.2
focal length
3mm
shutter speed
1/60s
camera make
Apple
camera model
lens model
overall
(38.40%)
curation
(96.28%)
highlight visibility
(78.78%)
behavioral
(70.67%)
failure
(-0.32%)
harmonious color
(-1.80%)
immersiveness
(0.12%)
interaction
(4.00%)
interesting subject
(3.94%)
intrusive object presence
(-7.62%)
lively color
(7.37%)
low light
(6.59%)
noise
(-3.08%)
pleasant camera tilt
(-8.88%)
pleasant composition
(-65.33%)
pleasant lighting
(-27.27%)
pleasant pattern
(6.59%)
pleasant perspective
(-4.88%)
pleasant post processing
(2.08%)
pleasant reflection
(-1.99%)
pleasant symmetry
(0.22%)
sharply focused subject
(0.73%)
tastefully blurred
(-10.74%)
well chosen subject
(-37.40%)
well framed subject
(-29.37%)
well timed shot
(1.63%)
all
(-4.58%)
* NOTE: Amazon Rekognition
detected a celebrity in this image using the
Celebrity Recognition API. The API isn't perfect, but it does give you the MatchConfidence which I display
next to the celebrity's name along with links _↗ to their info.
* 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.