Show HN: Each country as a Pokemon, using Stable Diffusion

https://github.com/sradc/each-country-as-a-pokemon-stable-diffusion

60 21 4 years ago

Magi604• 4 years ago

Interesting premise, but unfortunately the results are not. There's nothing in the designs of the Pokemon that ties them to their connected country, so they all just end up looking generic.

montebicyclelo2• 4 years ago

Canada has a maple leaf for a tail :D [1]

But yep, I do hope to improve this. (And if I don't, I'm sure someone else will.)

[1] https://github.com/sradc/each-country-as-a-pokemon-stable-di...

aaaaaaaaata• 4 years ago

Good attitude!

bee_rider• 4 years ago

Ukraine got the colors right at least.

Vatican City is pretty good.

It is sort of interesting that United States and US Virgin Islands both have blue bodies and red paws.

arcastroe• 4 years ago

US has red white and blue. Well...white if you count the background color ;)

jannyfer• 4 years ago

I spot checked a few and the generated pokemon colours matched their flags.

Harlekuin• 4 years ago

Australia is a kangaroo with nipple tassels and a missing toe - pretty spot on

mickotron• 4 years ago

Also is green and gold in colour.

Xeoncross• 4 years ago

It's a been couple decades since I first saw pokemon, but is this what they look like now? Most of them kind of look like the same 2-legged, mammal thing in different primary colors.

sbf501• 4 years ago

It's about catching/buying them all. Best marketing strategy ever.

Multicomp2• 4 years ago

Some are two legged, others are 4, still others have 6 limbs like centaurs, and even so others have a 4 legged creature and a two legged TV stand thing following them around.

But I suspect their similar texture is because stable diffusion was trained on the official artwork for Pokemon rather than their in-game sprites/models, though that is just a guess.

oneoff7862• 4 years ago

Thankfully no, they’re still good

dragontamer• 4 years ago

https://bulbapedia.bulbagarden.net/wiki/Lechonk_(Pok%C3%A9mo...

https://bulbapedia.bulbagarden.net/wiki/Mimikyu_(Pok%C3%A9mo...

https://bulbapedia.bulbagarden.net/wiki/Greninja_(Pok%C3%A9m...

https://bulbapedia.bulbagarden.net/wiki/Buzzwole_(Pok%C3%A9m...

https://bulbapedia.bulbagarden.net/wiki/Corviknight_(Pok%C3%...

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Honestly, these monsters don't look much like Pokemon to me. But maybe cause I've played a good chunk of Pokemon.

I think its impressive that Stable Diffusion can make such "artwork", but its not quite "Pokemon". There's something terrible going on with Stable Diffusion's generation of eyes here, I don't know quite what, but its like Stable Diffusion doesn't understand "anime perspective" at all.

The eyes are often "bouncing" between 3/4ths perspective and straight-at-the-camera perspective, sometimes within the same generated monster. The algorithm is also trying to generate a 2nd face in the bottom-right of a lot of these pictures, for some reason.

char_star_star• 4 years ago

Now just train a model to generate types and move sets from Pokémon images and you can do procedurally generated Pokémon games.

Multicomp2• 4 years ago

I am incredibly impressed with this post and with the novel results of Stable Diffusion already.

The result for Ivory Coast looks like the latest+ dark n edgy brooding Pokemon for ash and company to love on and teach that life is not all grimdark after all, some 5 or so episodes after Ash gets to a new region and re learns type matchups for the Nth time.

+next in line after Mewtwo and Lucario

oneoff7862• 4 years ago

Vatican City is great. The rest… meh. These feel a bit overfit to me. I can tell with relative high confidence which pokemon is.

Ukraine is kind of cool with a custom articuno vibe

cookiengineer• 4 years ago

I was looking at Germany, expecting a bureaucrat pokemon. I was a little disappointed :D

Shorel• 4 years ago

Chad looks more like Colombia than Colombia.

I can't see any logic in Venezuela.

TillE• 4 years ago

A bunch of these (eg, Cameroon) have a weird extra limb, which is basically consistent with my experience of Stable Diffusion: it frequently produces images that are physically impossible, architecturally nonsensical, etc.

I'm not sure other models are better. I don't think they are. Seems like a big problem that won't be easy to solve.

hotpathdev• 4 years ago

Ever since I saw your pokemon fine tuning, I've been looking forward to trying it myself ! I find your results to be convincing, as a long time pokemon fan !

I made an account to say thank you for sharing your fine tuning code for others to use !

montebicyclelo2• 4 years ago

Hey, thank you! but it wasn't me who fine tuned [1] the model, it was https://github.com/justinpinkney

I agree that it produces some incredible results, and it's awesome that justinpinkney open sourced it!

[1] https://github.com/LambdaLabsML/examples/tree/main/stable-di...

Show HN: Each country as a Pokemon, using Stable Diffusion

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