Photos | Building Blocks for Success
Tarundeep Rai and a colleague strategize over a tower of wooden blocks during a working lunch at a San Francisco restaurant.
BLIP-2 Description:
a man and a woman sitting at a table with a tower of wooden blocksChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
3024w x 4032h - (download 4k)
Usage
Dominant Color:
Location:
architecture glass bay necklace tableware interior design urban optical pub building north portrait food beach mobile equipment plywood money restaurant furniture lumber utensil pion flooring court container wood eyeglasses drinking desk today glasses indoors dining tabletop tarundeep rai electronics jewelry hardwood table accessories room st game part phone cal photography cup floor
iso
80
metering mode
5
aperture
f/1.8
focal length
4mm
latitude
37.81
longitude
-122.41
shutter speed
1/60s
camera make
Apple
camera model
lens model
date
2019-08-02T16:49:54.066000-07:00
tzoffset
-25200
tzname
America/Los_Angeles
overall
(45.41%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.61%)
failure
(-0.29%)
harmonious color
(1.42%)
immersiveness
(0.20%)
interaction
(1.00%)
interesting subject
(33.11%)
intrusive object presence
(-9.23%)
lively color
(-3.51%)
low light
(6.47%)
noise
(-9.03%)
pleasant camera tilt
(-6.05%)
pleasant composition
(-25.90%)
pleasant lighting
(-23.03%)
pleasant pattern
(8.72%)
pleasant perspective
(2.60%)
pleasant post processing
(1.20%)
pleasant reflection
(-3.70%)
pleasant symmetry
(0.46%)
sharply focused subject
(1.29%)
tastefully blurred
(-2.92%)
well chosen subject
(-48.17%)
well framed subject
(39.45%)
well timed shot
(12.48%)
all
(-0.11%)
* 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.