Machine learning based improvements for image resizing

Not really, as noticed in the comments, this is mainly due to an implementation bug with the image downsizing algorithms in the ML libraries:

Look like developers of ML libraries are not always image processing experts :slight_smile:

1 Like

Coo, what fun! I came across this image:

I sampled it with ImageMagick:

magick c.jpg -sample 267x233 s.jpg

And the result is this:
s

… which is undeniable proof that Leo de Vinci was a time-traveller. Or that he secretly liked toes. Or something.

2 Likes

The concerned cat turning into a smug dog with a raincoat is too funny.

Most definitely. Too many papers leave me scratching my head.

da Vinci’s time doppelganger no doubt.

Thanks for the correction. I couldn’t remember the painter’s name, and was too lazy to look it up, and made my best guess.

If anyone doesn’t realise: I edited the Mona Lia image replacing one pixel in every 64 with the appropriate pixel from my toes image. IM’s simple and fast “-sample” picks out just those pixels.

I saved the edited Mona Lisa as a lossy JPEG, so that messes up the embedded toes image. When I save it losslessly, “-sample” reproduces the toes exactly.