Photos | Sticker-Strewn Bar in Altadena
Hoot Gibson enjoys a drink at this character-filled pub, covered in stickers both inside and out.
BLIP-2 Description:
a bar with many different stickers on itChronologically Adjacent
Note: You can also navigate with your arrow keys or swiping.
Metadata
Capture date:
Original Dimensions:
2448w x 3264h - (download 4k)
Usage
Dominant Color:
Location:
discrimination job lighting one urban tape chipotle adrid sticker budweise fire vehicle act lamp symbol license uraclice transportation court way indoors black wood sign beverage sale outdoor great pub age breath plate asshole building architecture iva food mark shop counter kiosk bar text no trying alcohol restaurant hoot gibson like stream pepper sweets mate
Detected Text
iso
320
metering mode
3
aperture
f/2.2
focal length
4mm
latitude
34.19
longitude
-118.13
shutter speed
1/30s
camera make
Apple
camera model
lens model
date
2013-09-29T15:54:34.859000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(20.68%)
curation
(50.00%)
highlight visibility
(2.45%)
behavioral
(70.26%)
failure
(-0.68%)
harmonious color
(-2.28%)
immersiveness
(0.20%)
interaction
(1.00%)
interesting subject
(-64.50%)
intrusive object presence
(-8.52%)
lively color
(-17.99%)
low light
(86.47%)
noise
(-9.01%)
pleasant camera tilt
(-16.14%)
pleasant composition
(-68.12%)
pleasant lighting
(-71.58%)
pleasant pattern
(6.52%)
pleasant perspective
(-9.94%)
pleasant post processing
(0.00%)
pleasant reflection
(-4.40%)
pleasant symmetry
(0.76%)
sharply focused subject
(0.24%)
tastefully blurred
(-2.56%)
well chosen subject
(-13.99%)
well framed subject
(-27.88%)
well timed shot
(-1.09%)
all
(-11.63%)
* 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.