Photos | Respect Xmas: Faces of Friendship
A bulletin board filled with portraits of 19 people, including 3 men and 4 males, all with smiles and different hats. The display also includes a tennis ball, a sign, and a Christmas tree. This snapshot captured the spirit of togetherness and respect during the holiday season in 2004.
BLIP-2 Description:
a bulletin board with pictures of peopleMetadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
instrument respect_xmas portrait glasses transportation shirt computer cabinet teen respect musical tennis studio car hardware device table building lighting sign electronics desk boy microphone room bedroom ernie pants stickers ball bed screen vehicle architecture guitar hat sport text furniture accessories photography inyl indoors monitor electrical xmas living room
flash fired
true
metering mode
5
aperture
f/2.5
focal length
6mm
shutter speed
1/30s
camera make
CASIO COMPUTER CO.,LTD.
camera model
overall
(6.28%)
curation
(65.44%)
highlight visibility
(2.45%)
behavioral
(70.35%)
failure
(-0.54%)
harmonious color
(-2.33%)
immersiveness
(0.05%)
interaction
(1.00%)
interesting subject
(-75.59%)
intrusive object presence
(-4.20%)
lively color
(-14.83%)
low light
(27.56%)
noise
(-13.38%)
pleasant camera tilt
(-15.91%)
pleasant composition
(-74.46%)
pleasant lighting
(-57.91%)
pleasant pattern
(2.71%)
pleasant perspective
(-10.44%)
pleasant post processing
(-1.18%)
pleasant reflection
(-7.45%)
pleasant symmetry
(0.15%)
sharply focused subject
(0.17%)
tastefully blurred
(-19.53%)
well chosen subject
(-19.54%)
well framed subject
(-38.75%)
well timed shot
(-7.81%)
all
(-13.31%)
* 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.