#679's picture is kinda scary lol
Book of Monsters
A collection of 2000 AI generated monsters and their descriptions. Each entry has an image with a description of the monster. The AI was trained on images from D&D. This is mostly just for fun, but maybe it can give you inspiration for a story, game, campaign, etc. Feel free to use anything as long as it is non-commercially. You can download a pdf for offline viewing, be aware that it is somewhat big (360mb).
For a little easter egg, press S on your keyboard to get an extended description.
Seeing as this is AI generated there is always a risk it generates something weird. I have gone through a bunch of it and automatically filtered out a lot, but there is always a chance I missed something. So read at your own discretion, and if you find something you think doesn't belong, please let me know.
Tech & Credits
- Images generated by training a ruDALL-E model on D&D images, with the help of Looking Glass.
- Image tag identification using Google Vision AI.
- Name generation by Fantasy Name Generators.
- Text generated using GPT-J.
- UI borders by ScrewyLightBulb.
I might add more monsters in the future if people like this, but for now 2000 should keep you busy for a while :)
Thanks for checking this out! If you liked it, a comment or rating is always appreciated!
Click download now to get access to the following files:
- PDF versionMay 10, 2022
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#1777 is a sneezy death bunny
Sparrela (Number 9) [Most]
Hexecta (Number Twenty)
Droreman (Number Seventy Seven)
Hexican (Number One Hundred One)
Var'gonneth (Number Two Hundred Thirty-Seven)
Hummelope (Four Hundred Seventy One)
Tesakshaex (Eight Hundred Fifty)
Mothildox (Nine Hundred Ninety-Five)
Peebu (Numbara One Thousand Three Hundred Fifty-Nine)
Buyasukh (Numbara One Thousand Six Hundred Seven)
The Hungry Existence Absorber (Number 1956) [Most]
Mulabura (Number Nineteen Ninety-Six)
Chuanile (Number Two-Thousand)
Wow, its so good. So many card game potential. Wonderful. I would love to see the card game version. These artificial intelligences are so brilliant.
Glad you like them! Yeah some game with it would be awesome to see. And the cool thing about AI is that it can just keep generating near infinitely.
If he is sent some food by a person, he will say "I'm full, but I'd love some more.
This creature might seem like an ordinary flowering plant, but is actually the cutest little thing you've ever seen.
He lives in a small garden made by a man named Sna-Gurth. Achuksuh is friends with another furry creature named Sna-Methos. He is also friends with the "honeybee" creature named Sna-Ree
Achuksuh and Sna-Methos are good friends and like to go out and find flowers and other things to eat. However, their main hobby is to go out and look for other creatures.
Achuksuh is a being that brings happiness to others. He is the kindest of creatures and likes to eat flowers and berries. He will befriend any creature that he sees, and he is also very friendly and kind to humans.
amazing. thank you for this. Achuksuh brought me happiness.
Wow, that's probably the cutest description in there, also love those names.
And I guess if Achuksuh brought you happiness that means the description is true.
Is it possible to put a download to this I would love this (I have already spent about an hour on this)
Haha, nice to hear you can get lost in it. I added a pdf to the downloads that contains every monster. Might be somewhat slow to load but hope it works.
This is so cool! Can't wait to spend hours lost in this. <3
As always, you surprised me! Congratulations :)
This is so great. Any possibility of a downloadable PDF version?
Oh, that's an interesting suggestion! Might be possible, gonna have to look into it.
Glad you like it!
Thanks. The interface is a bit wonky in different browsers, and I'd love to be able to zoom in on the art more easily. It appears the consistent visual framing of creature against plain white background gave the GAN a lot to work with effectively.
Ah, I tried to get the UI right for most devices. For what browser is it wonky for you? Zooming function is also a good idea.
Yeah I'm really surprised how well the GAN actually performed, especially with a somewhat small dataset.