Photos | A Stroll Down the Rainforest Walkway

A candid moment captured on March 3rd, 2024 as a woman and a young boy explore the rich environment of the California Academy of Sciences - Rainforest. Emphasizing the simple joy of curiosity, this photo beautifully juxtaposes the architectural elegance of the walkway with the vibrancy of human connection. Note the intricate detail of their clothing and the distinct urban elements surrounding them, representing the intriguing intersection of natural science and city life.
BLIP-2 Description:
a woman and a child walking down a walkwayMetadata
Capture date:
Original Dimensions:
4000w x 6000h - (download 4k)
Usage
Dominant Color:
architecture jeans boy pants handrail urban building fence portrait child footwear railing rainforest outdoors luggage hat walkway sidewalk road jacket house flooring container shoe city bag street academy coat glasses indoors airport corridor path backpack sciences accessories lori walking housing lighting photography terminal wesley california floor staircase handbag shelter
iso
2500
metering mode
5
aperture
f/3.2
focal length
24mm
shutter speed
1/500s
camera make
Canon
camera model
lens model
date
2024-03-03T11:05:31.330000-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(46.31%)
curation
(68.65%)
highlight visibility
(5.93%)
behavioral
(90.90%)
failure
(-0.44%)
harmonious color
(3.18%)
immersiveness
(3.20%)
interaction
(1.00%)
interesting subject
(16.39%)
intrusive object presence
(-3.74%)
lively color
(-2.34%)
low light
(22.34%)
noise
(-2.66%)
pleasant camera tilt
(-8.48%)
pleasant composition
(2.64%)
pleasant lighting
(-22.75%)
pleasant pattern
(16.60%)
pleasant perspective
(16.00%)
pleasant post processing
(7.68%)
pleasant reflection
(-6.18%)
pleasant symmetry
(2.29%)
sharply focused subject
(1.17%)
tastefully blurred
(0.27%)
well chosen subject
(-11.46%)
well framed subject
(38.06%)
well timed shot
(3.29%)
all
(4.55%)
* WARNING: The title and caption of this image were generated by an AI LLM (gpt-4-0613
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.