Photos | Waiting for the Bullet Train
Shi Zhiyong and companions stand poised for departure in front of Tokyo's high-speed railway.
BLIP-2 Description:
a man and a woman standing in front of a trainMetadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
Location:
urban subway portrait glasses transportation costume trip tie formal nishishinjuku train bullet_train jacket city shi zhiyong building lighting glove outdoors coat scarf japan pants selfie vehicle real architecture machine station hat bullet terminal wear hood railway accessories photography headgear shelter cap part
Detected Text
metering mode
5
aperture
f/2.5
focal length
6mm
shutter speed
1/60s
camera make
CASIO COMPUTER CO.,LTD.
camera model
overall
(25.12%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.67%)
failure
(-4.22%)
harmonious color
(-7.59%)
immersiveness
(0.71%)
interaction
(1.00%)
interesting subject
(-20.97%)
intrusive object presence
(-3.64%)
lively color
(-29.86%)
low light
(16.77%)
noise
(-18.55%)
pleasant camera tilt
(-6.40%)
pleasant composition
(-34.06%)
pleasant lighting
(-55.86%)
pleasant pattern
(7.89%)
pleasant perspective
(-2.49%)
pleasant post processing
(-3.69%)
pleasant reflection
(-2.61%)
pleasant symmetry
(0.93%)
sharply focused subject
(0.71%)
tastefully blurred
(-46.73%)
well chosen subject
(-39.84%)
well framed subject
(14.31%)
well timed shot
(-5.42%)
all
(-9.24%)
* 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.
* 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.