Photos | Three Friends in Baseball Caps

Three young men smile for a portrait while wearing matching baseball caps and casual clothing. Two cardboard boxes and a pair of sneakers sit behind them on a couch. (Tags: 3 Hats, Cap, Baseball Cap, Clothing, Shoe, Footwear, Portrait, 3 Males, Teen, Boy, 2 Boxes, T-Shirt, Bracelet, Accessories, Couch, Furniture, People)
BLIP-2 Description:
three men are smiling and posing for a pictureMetadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
bracelet headgear boy pants baseball portrait move publication footwear mobile cap hat furniture induc carton container shoe cardboard glove old world desk shirt mouth junglescene teeth indoors teen book cessing baseball glove electronics photos/world_move jewelry sport table accessories couch package part laughing photography phone delivery happy weasel cardboard box box
Detected Text
date
2002-11-03T18:17:03-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(30.64%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.69%)
failure
(-0.34%)
harmonious color
(2.56%)
immersiveness
(0.07%)
interaction
(1.00%)
interesting subject
(5.75%)
intrusive object presence
(-17.92%)
lively color
(-17.75%)
low light
(94.78%)
noise
(-12.30%)
pleasant camera tilt
(-4.29%)
pleasant composition
(-65.48%)
pleasant lighting
(-56.10%)
pleasant pattern
(1.17%)
pleasant perspective
(1.42%)
pleasant post processing
(-1.04%)
pleasant reflection
(6.73%)
pleasant symmetry
(0.17%)
sharply focused subject
(0.93%)
tastefully blurred
(0.38%)
well chosen subject
(-42.94%)
well framed subject
(26.49%)
well timed shot
(12.51%)
all
(-7.35%)
* 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.