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:
restaurant accessories architecture urban vehicle food table bread álex cruz kennedy cafe grace c sign electronics handbag cafeteria shirt transportation fico dining room necklace crowd indoors furniture hat outdoors athletics hut room dining court courtney building ben photography undershirt please scissors cup portrait cream rural dave nature countryside no plate meal roots dessert dinner bag camera pub dish shelter car jewelry neighborhood pacifico icing glasses lunch
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 with AI (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.