Photos | Cheers to 46 Cans
This wooden frame display showcases 46 cans of delicious beer from San Francisco, California. Gather your friends, crack open a cold one, and enjoy! 🍻 #beer #alcohol #beverage #tin #shelf #furniture #4people #cannedgoods #sanfrancisco #lager
BLIP-2 Description:
a display of beer cans in a wooden frameMetadata
Capture date:
Original Dimensions:
4032w x 3024h - (download 4k)
Usage
Dominant Color:
Location:
期期 net civic ambrin rams ml primer bavarian shinen laber air corona cabinet canned ack chic aluminium malt shelf food liquor container atts horse closet 及 goods caracu fl lager schmiers carfish ter r kiri 使 heat oz tin wenbrau society jack brewe brow ale g finest 啤 center labatt's 小島 beverage blue beer gold cupboard bottle tap furniture contents neu pola premium derbr luger black alcohol point
Detected Text
12 1867 215 355 84 air ale bavarian beer brewe brow blue caracu carfish chic contents corona derbr finest fl g gold horse jack kiri lager liquor labatt's luger m net neu oz pola premium rams society schmiers shinen tap ter wenbrau a ack ambrin atts black heat laber malt ml point primer r 使 及 啤 小島 期期
iso
800
metering mode
5
aperture
f/2.2
focal length
8mm
latitude
37.78
longitude
-122.42
shutter speed
1/30s
camera make
Apple
camera model
overall
(50.44%)
curation
(25.00%)
highlight visibility
(2.44%)
behavioral
(70.20%)
failure
(-0.10%)
harmonious color
(8.41%)
immersiveness
(0.22%)
interaction
(1.00%)
interesting subject
(-26.20%)
intrusive object presence
(-0.68%)
lively color
(26.59%)
low light
(11.79%)
noise
(-1.56%)
pleasant camera tilt
(-6.58%)
pleasant composition
(12.51%)
pleasant lighting
(25.24%)
pleasant pattern
(25.78%)
pleasant perspective
(16.36%)
pleasant post processing
(4.23%)
pleasant reflection
(-6.73%)
pleasant symmetry
(5.57%)
sharply focused subject
(3.66%)
tastefully blurred
(5.27%)
well chosen subject
(-7.98%)
well framed subject
(19.75%)
well timed shot
(5.62%)
all
(12.18%)
* 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.