) > 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:
3/ A broader view of the red, blue, gold and green battalions :)
4/ Now you can get creative and add more colors (I just prompted "rainbow space marine, colorful" in the set below)
5/ It's not just about colors. The look or style of the models can be altered with other modifiers.
Such as "a dark Halloween zombie space marine". Now all the models have been zombified 🧟♂️💀🧟♀️. They could also melt or glow in the dark.
6/ I randomly found that one of the soldiers looked like a baby, so I prompted "a cute baby space marine" and made everyone look younger, in seconds:
7/ Because the shape/silhouette of the "baby space marine" was interesting, I kept it and used #img2img to generate pixel art variations, in different colors:
8/ img2img is very powerful when combined with Dreambooth. I went back to my previous tweet (link -
), and selected a "cyclopean golem", to resembling space soldiers, like this
9/ Same story below, but with a different (white) golem.
Also, I added "no gun" as a negative prompt. None of the soldiers has the machine gun they held before.
10/ As a bonus, you can have more fun with your finetune and generate other storytelling visuals.
For example, "urban warfare background" or "a group of space marines dancing in a night club"
11/ Or even find the image of a tank and then run #img2img to generate tank-like space robots/creatures 🪖
12/ I'm hoping this somehow demonstrates the power of having your own "finetune(s)"
Training lets you iterate around a specific concept, style, or object. You get consistent results, faster, and possibly using your training data. No more endless random prompting. What else? :)
end/ I've had some great discussions about it with the gaming community (artists or studios) over the past few days. If you have questions or would like to have a chat, please comment or DM me; happy to connect with innovative game creators.
From multiple consistent objects within a single image to fully recreated 3D objects in Blender.
100% AI-generated.
Workflow detailed below 👇
Step 1/
Generate a grid of 6 consistent objects. For this, I used @Scenario_gg with the "Juicy Icons" model, which consistently creates cartoon-style, simplified 3D icons arranged in a grid.
Absolutely loving that this is happening during GDC week 😅. My schedule's packed with meetings & meetups, so not much time to vibe code, but I spun up a basic demo for a platformer jumping game, in minutes.
This was fully prompted via Claude 3.7 (on the left), zero manual tweaks. Link below 👇 and I'll keep sharing improvements and tips!
2025 is going to be a wild year for AI-powered game devs.
I used @JustinPBarnett's MCP on Github - check it out here
So far, it feels even easier than Blender, and I can’t wait to add more actions, assets, textures, and gameplay!github.com/justinpbarnett…
My main tip so far is that, just like with Blender MCP, you should proceed step by step >> one edit or element at a time.
Otherwise, Claude will go crazy and wil try doing everything at once (and fail).
Here are the key steps to creating stunning turnaround, using #Scenario ()
1/ Train or pick a character model (A).
2/ Optionaly>, pick a style model (B). Use it to create training images for (A), or you can merge both (A + B = C) for example.
3/ Utilize the custom model (A or C) to generate consistent characters. Then select a reference image to produce initial character turnarounds in your desired poses.
4/ Refine these initial outputs using Sketching and image2image.
5/ Select the best result and refine details in the Canvas for maximum consistency.
6/ Finally, upscale your final image (up to 8K resolution.)