Photos | Unforgettable Cam Grad Party 2023
A memorable moment as friends and family, including Donald Glover and LaLa Nestor, gather to celebrate the Cam Grad Party on June 10, 2023. Surrounded by laughter, nature, and creative decor, everyone united in joy and festivity beneath the vibrant banner.
BLIP-2 Description:
a group of people posing for a photo in front of a bannerChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
6000w x 4000h - (download 4k)
Usage
Dominant Color:
marissa lala dress jeans party portrait glasses child shirt cap festival costume mandy girl footwear bag grass park jeremiah laughing crowd necklace tree chair jewelry rose happy sign glove shoe handbag luna outdoors grad nature lori balloon coat kimmie umbrella dave b pants plant wristwatch cup cameron cam baseball hat blouse utensil nestor banner furniture fun accessories photography donald glover art
iso
160
metering mode
5
aperture
f/7.1
focal length
24mm
shutter speed
1/80s
camera make
Canon
camera model
lens model
overall
(54.05%)
curation
(97.92%)
highlight visibility
(8.01%)
behavioral
(70.69%)
failure
(-0.05%)
harmonious color
(4.78%)
immersiveness
(0.17%)
interaction
(2.00%)
interesting subject
(51.81%)
intrusive object presence
(-16.16%)
lively color
(5.22%)
low light
(3.22%)
noise
(-1.07%)
pleasant camera tilt
(-1.80%)
pleasant composition
(-41.80%)
pleasant lighting
(2.58%)
pleasant pattern
(6.45%)
pleasant perspective
(23.71%)
pleasant post processing
(3.63%)
pleasant reflection
(2.72%)
pleasant symmetry
(1.00%)
sharply focused subject
(1.20%)
tastefully blurred
(-1.03%)
well chosen subject
(-9.16%)
well framed subject
(11.33%)
well timed shot
(25.29%)
all
(7.02%)
* 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-4-0314
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.