Photos | Nightlife Adventure on the Back of the Bus

Matt Patricia and Francisco C join a lively crowd of 15 people, enjoying the urban nightlife scene while riding on a bus fitted with nightclub-inspired interior frames. Clothing, shoes, and accessories are on full display, making the ride a fun and stylish experience.
BLIP-2 Description:
a group of people sitting on the back of a busMetadata
Capture date:
Original Dimensions:
4032w x 3024h - (download 4k)
Usage
urban pub frame mobile bar footwear beverage transportation hat wristwatch restaurant furniture counter shoe party bag art hardware fun shoes justin club alcohol matt patricia glasses indoors audience life bus interior electronics vehicle screen accessories nightclub monitor room night handbag couch charles phone cup computer crowd francisco c
iso
100
metering mode
5
aperture
f/1.8
focal length
4mm
shutter speed
1/5s
camera make
Apple
camera model
lens model
date
2017-07-21T12:51:15.466000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(26.32%)
curation
(93.07%)
highlight visibility
(2.45%)
behavioral
(70.61%)
failure
(-2.05%)
harmonious color
(-0.47%)
immersiveness
(0.32%)
interaction
(1.00%)
interesting subject
(10.56%)
intrusive object presence
(-2.42%)
lively color
(-41.19%)
low light
(89.84%)
noise
(-6.93%)
pleasant camera tilt
(-8.91%)
pleasant composition
(-35.74%)
pleasant lighting
(-34.77%)
pleasant pattern
(11.96%)
pleasant perspective
(-2.98%)
pleasant post processing
(-27.49%)
pleasant reflection
(-0.35%)
pleasant symmetry
(0.49%)
sharply focused subject
(0.61%)
tastefully blurred
(-37.21%)
well chosen subject
(-28.34%)
well framed subject
(-21.69%)
well timed shot
(-8.30%)
all
(-8.91%)
* 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.