Photos | Spooktacular Party Costumes
A group of 12 people dressed in a variety of costumes, including a plant, a microphone and electrical device, and a woman in a stunning gown with accessories, pose for a portrait at a Halloween-themed party in 2002.
BLIP-2 Description:
a group of people dressed up in costumes at a partyChronologically Adjacent
Note: You can also navigate with your arrow keys or swiping.
Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
costume beer necklace urban plant pub portrait chair gown publication bar baby beverage microphone hat wristwatch furniture jacket counter container bag party halloween old fashion fun club alcohol coat junglescene glasses belt life book jewelry performer suit accessories respect night photos/halloween_respect blazer formal wear lighting device photography dress cup handbag electrical
Detected Text
date
2002-11-01T11:05:54-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(30.42%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.62%)
failure
(-0.59%)
harmonious color
(-2.67%)
immersiveness
(0.20%)
interaction
(1.00%)
interesting subject
(-25.56%)
intrusive object presence
(-9.03%)
lively color
(18.14%)
low light
(98.58%)
noise
(-10.50%)
pleasant camera tilt
(-5.15%)
pleasant composition
(-60.06%)
pleasant lighting
(-42.87%)
pleasant pattern
(3.44%)
pleasant perspective
(-7.34%)
pleasant post processing
(-0.49%)
pleasant reflection
(1.34%)
pleasant symmetry
(0.17%)
sharply focused subject
(1.10%)
tastefully blurred
(-5.73%)
well chosen subject
(-43.16%)
well framed subject
(-8.83%)
well timed shot
(-2.93%)
all
(-6.52%)
* NOTE: This image was scaled up from its original size using an AI model called GFP-GAN (Generative Facial Prior), which is a
Generative adversartial network that can be used to repair (or upscale in this case) photos, sometimes the results are a little...
weird.
* 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.