Dave Bullock / eecue

Photographer Engineering Leader Nerd

Photos | Ocean Scenery from the Train

Ocean Scenery from the Train

Caption

The view of the blue sky, cumulus clouds, and shoreline from the train window during our 2003 trip to Kobe, Japan.

BLIP-2 Description:

a view of the ocean from a train window

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Metadata

Capture date:

Tuesday, January 7th, 2003 at 11:35:36 PM

Original Dimensions:

640w x 480h - (download 4k)

Usage

Usage and Licensing

Dominant Color:

Location:

Nishishinjuku, Shinjuku, Kanto, Japan (35.69,139.69)

Tags

Albums

Photo Archive/2003/japan_trip/kobe kobe

Places

Tokyo Metropolitan Government Office

Venues

BASE Third Place Bar Udatsu Sushi View & Kitchen Quad 17 Asian Cuisine Dining Japanese Cuisine Restaurant Sushi Restaurant

EXIF Data:

iso

60

metering mode

5

aperture

f/2.9

focal length

6mm

shutter speed

1/1000s

camera make

OLYMPUS OPTICAL CO.,LTD

camera model

Apple Photos ML Scores

overall (39.92%)

curation (50.00%)

highlight visibility (4.36%)

behavioral (70.48%)

failure (-1.03%)

harmonious color (1.44%)

immersiveness (0.83%)

interaction (1.00%)

interesting subject (-23.72%)

intrusive object presence (-4.79%)

lively color (6.61%)

low light (0.54%)

noise (-2.20%)

pleasant camera tilt (-12.62%)

pleasant composition (-15.42%)

pleasant lighting (-28.00%)

pleasant pattern (5.40%)

pleasant perspective (-1.80%)

pleasant post processing (3.31%)

pleasant reflection (-7.40%)

pleasant symmetry (0.29%)

sharply focused subject (0.20%)

tastefully blurred (3.88%)

well chosen subject (-5.07%)

well framed subject (-1.47%)

well timed shot (2.26%)

all (0.36%)

* 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.