Emm Profile picture
Nov 8 26 tweets 14 min read
I designed the most incredible pack of potions with #AI (and nothing but AI - #StableDiffusion)

Mega-thread 🧵

Follow the exploration below, esp. if you're in the #gaming industry (Game dev, Game Artist, Creative Director, etc.) Content production is about to be transformed 🤯 ImageImage
The gaming industry always needs a lot of new content. 40% of their budget is in the art assets.

Take potions, a ubiquitous prop in RPG games.

Below are some of the “most popular” potion packs available on the Unity asset store (similar sets are on the Unreal marketplace). ImageImageImageImage
And these are some of the potions found on Artstation.

They look much more elaborate, and some designs are highly creative. However, there are only 740 results for the “potion” query, which seems limited. Image
Or, one can search for potion visuals on the Generative AI platforms. I often use @LexicaArt, for example (kudos @sharifshameem). 2,864 results are a lot! However… there’s no consistent collection that can be used for a game. Image
To include some potions in their game, creators can buy a pack on some asset marketplace (from $5 to $20). Or they work with artists that create elaborated/dedicated visuals (which then takes longer and is more expensive). Image
#AI can supercharge the #creativity and the #productivity of game makers, today (studios, indie devs & artists alike)

By fine-tuning Stable Diffusion, one can quickly iterate around different concepts and generate infinite variations, in less than 1 hour. The ideation phase...
... is significantly shortened, while the creative possibilities are multiplied by several orders of magnitude.

Also, “Prompting in the dark” is over: with adequate fine-tuning, the AI delivers consistent results around the concept of a potion (in this case). Image
In this demonstration, I used a dedicated training dataset of 98 images (which is quite large).

The initial training took 3 hours (9800 training steps), but the wait was worth it!

And here's what I got 🔮✨🧪
The first run starts with a simple prompt ("a potion") and as many batches as possible. It helps to define some key modifiers: "3D rendering", "intricately detailed", "beautiful", "holographic", "colorful". "3D vray render"

You think it's cool? You ain't seen nothing yet. ImageImage
When the modifiers are chosen, it's time to iterate around different variations: shapes, colors, light, and details...

"Spiral galaxy inside a glass potion, intricately detailed, beautiful, holographic, colorful. 3D vray render, purple dust on the floor" ImageImage
Keep going with various modifiers, and then, remove the background. Try to identify the potions that look the best.

(NB: this is only a subset, I generated 3x more items to choose from - all generated with the AI) ImageImage
Select the potions you like the most, and switch to #img2img... and run more batches

Here are 16 incredibly beautiful potions, created in 1 min 30.

"Multicolor bright glass potion, intricately detailed, beautiful, 3D vray render, trending on artstation" ImageImage
By the way, this was the original image used for img2im (left) and a variant (right) ImageImage
Some green variants (same prompt, with "green" included) ImageImage
Yellow. ImageImage
Turquoise ImageImage
Orange Image
Then, you can play with "add-ons". Details that can be added outside or inside the bottle, for example.

I started with this "branches & leaves around a bottle, intricately detailed, beautiful, 3D vray render, trending on artstation".

The first image (top-right) is for img2img ImageImageImageImage
The same prompt, but with a different shape (img2img) and color. ImageImageImageImage
This one, with a snake 🐍 ImageImage
Or ropes! ImageImage
And if you make it until the end, you deserve the best: "Fantasy dragon inside a potion, detailed, beautiful, 3D vray render, trending on artstation" ImageImageImageImage
I made lots of dragons, actually... (it just takes a few more minutes to wait, after all). Image
Now, I also tried prompting the "plain" versions of art generators, this is the (curated) output from Midjourney with "video games icons, 2d icons, potions icons, potions, arcane, shiny object, graphic design, high contrast, artstation --v 4" Image
If you like this post and exploration, please let us know your thoughts, questions, or remarks. Especially if you're a game industry professional.

Also, feel free to RT/like and follow, many more examples are to come! 🚀🙏👩‍💻
Also, here's a little game you can play, if you'd like

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More from @emmanuel_2m

Nov 10
I've explored a reliable method to create high-quality, style-consistent #game assets w. #StableDiffusion

We're just scratching the surface here & I believe this can become a very potent creation tool (like a "@Procreate on AI-steroids"🤔)

A demonstration with... spellbooks 🧵
Spellbooks are another ubiquitous asset in heroic #fantasy games, tabletop games, D&D, etc.

However (like for potions), the Unity/Unreal asset stores have limited choice, and most assets have a rather simplistic design.

Here's how #AI can solve such a situation. Image
At first, I generated a set of 38 "random" spellbooks, which I used to train a finetune model of Stable Diffusion (Dreambooth). It took 1 hr.

I then explored a set of possibilities with simple prompts and or limited modifiers (intricate, detailed, beautiful, 3D render...) ImageImage
Read 24 tweets
Nov 8
Okay, I believe this is the most INSANE set of assets I've designed so far with #StableDiffusion. Just ready for an excellent #RPG! Who wants some potions?

Take a look at the first selection below... the complete thread + how-to are coming in about 2-3 hours

#AI for #Gaming
Read 12 tweets
Nov 7
I've done a first pass on the dwarves, and they're fun.

This proves again that #AI / #StableDiffusion is a fantastic tool for designing and creating #game assets... when adequately fine-tuned.

Here's some of the exploration, so far - 🧵
The model was trained on just 11 pictures (!), with only 1500 training steps, which tuned out to be quick (20 min).

As before, the first step is to "explore“ the model with a few generic prompts. The goal is to find the modifiers that will keep a consistent style going forward.
Once the "stable modifiers" are found, it's time to select some of the best output and remove the background when needed.

"A dwarf, detailed, trending on Artstation, Clash of Clans"👇
Read 16 tweets
Nov 6
Working on a set of dwarves now, and this one will be killer.

Stay (fine)tuned.

#StableDiffusion #AI #Gaming
Huh ok. Maybe not. Let's change the prompt a little bit, I guess.
Me likey
Read 4 tweets
Nov 6
Sharing additional thoughts on #StableDiffusion to create #gaming content & #game assets 🧵

My last exploration was on golems; this one is with "Space Marines-like" heavy infantry.

This was a fun creation with lots of learnings 👨‍💻. Feel free to like/RT if you find it useful 🚀
1/ First (as mentioned before - ) > curate a training dataset (such as pictures of figurines) to feed a #Dreambooth finetune.

Once the model is ready, compare different generic prompts (e.g. "low-poly," "3D rendering“, "ultra-detailed," "pixel art," etc.)
2/ Once a prompt looks good, keep the modifiers (in this case: "3D rendering, highly detailed, trending on Artstation").

And start iterating around variations, such as colors (or pose). Don't over-engineer it, to keep the consistency. You should get this:
Read 15 tweets
Nov 5
Let’s keep using #StableDiffusion to design or create #game assets, quickly and consistently.

In 15 min, generated an army of golems with similar shapes and sizes, but various “materials” (lava, rock, water, ice, forest, sand, gold…).

No in-painting is needed. Thread 🧵
Step 1 (as in my previous examples with chests - ), I made a Dreambooth finetune w. just 11 pics.

As soon as the model was trained, the first step was randomly generating a large set of images w. a simple prompt ("golem, detailed, realistic, 3D rendering")
Each golem can be extracted by removing the images' backgrounds (reco: @photoroom_app).

Some of the designs are amazing. However, the golems all look very similar to each other. Let's separate them into categories.
Read 14 tweets

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