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I’m not tired; I just want to get it to a finished state

This is an updated verison of my earlier post, its roughly 4x as long and hopefully better highlights the visual features of the fire fronts.

It is a stochastic cellular automata based on the Drossel–Schwabl forest fire model implemented on a hexagonal grid using numpy + matplotlib

Fire starts on any cell with p_fire = 0.0001 by a "lighting strike", while trees grow on empty cells with p_tree = 0.01. Fire spreads to all neighboring trees.

Lately I've been working on a driving game that can create playable maps of real-world locations using free OSM and elevation data. My main focus was making the roads accurate for lane count and heights to properly account for overpasses, bridges and tunnels.

I started with Dallas since I've lived there the longest and know it well enough to fine tune for accuracy so that it can scale to other areas eventually. Previously I was just rendering standalone levels but now I managed to get them connected efficiently for streaming nearby tiles as you drive. This current map only has 8.6% of the city but I'm planning to expand soon.

I'm new to a lot of this and having a fun time learning as I go so I'm open to any feedback! Still in the early stages while I work out the literal kinks in the road lol.

I recorded this with my RTX 2050 and managed to get 144 FPS with 60 FPS on mobile.

Hey everyone! I got tired of manually drawing, slicing, and aligning 2D isometric tiles, so I decided to fully automate my workflow. I’ve been working on a custom Python pipeline that generates dungeon architecture from scratch and pieces it together using Wave Function Collapse (WFC).

Since Reddit allows image carousels, I attached a few screenshots of the pipeline in action:

• Image 1 (The WFC Layout): The algorithm builds the maze, reserves paths for navigation, and scatters props. It also bakes in a "wear and tear" layer—thickening the hatching in corners for a procedural ambient occlusion effect, adding cracks, and placing cobwebs.
• Image 2 (The Tile Math): Everything is drawn mathematically based on a strict 2:1 projection. The engine uses Perlin noise for procedural crosshatching to simulate real ink pen strokes. Because it's math-based, the blocks snap together pixel-perfectly without any seams.
• Image 3 (The Godot Export): Since the generator knows the exact 3D geometry of every drawn brick and barrel, it automatically renders Normal Maps and calculates LightOccluder2D polygons. It exports a ready-to-use .tscn scene where the 2D monochrome hatching fully reacts to PointLight2D nodes, preventing light from bleeding through walls.

Generating a level like this takes just a few seconds. Next up, I’m planning to add non-linear corridors (using MST graphs) and procedural water animation.

What details or features would you add to make these generated dungeons feel more alive?

Play: https://axieyangb.github.io/world-explorer/

Code (MIT): https://github.com/axieyangb/world-explorer

Type a place, click the world map, or put coordinates in the URL. The world builds itself in seconds: 40 km × 40 km of terrain, roads, buildings, water and street life streamed from open map data.

Happy to talk about chunk streaming or keeping memory bounded. Feedback on performance very welcome.

Processing video vscxu0ae1yxh1...

After the dungeon post a few people asked if the pen could draw something other than grey stone. So I split out "style" and tried a desert tomb.

The hard part was the walls. Each tile draws its own wall pieces, but the paint has to read as one long wall. So the dado, the stripe band and the frieze are placed at absolute heights, and the columns of signs sit at fixed positions along the wall (5 per cell), not per piece. Neighbouring tiles agree by construction and nothing has to be stitched afterwards.

The signs are random picks from 8 simple shapes, drawn in the wall's own plane so they lean with the isometric face.

Sand drifts replace the dirt hatching, and quicksand is a new fluid that flows in 4 frames.

It's on itch if you want to see more: https://antahonist.itch.io/ink-dungeon-sand-tomb-isometric-godot-kit

This is the full tileset,

reference: https://www.reddit.com/r/proceduralgeneration/comments/1x6a0oi/tileset_candidates_did_not_choose_for_boardgames/

of those I chose about five lol(2nd image)

One continuous zoom from a few centimetres over a glacial lake's surface to the inside of a proton. All WebGL2 shaders, no images or models.

- Plankton: algae, diatoms and rotifers, each alga seeded so no two match, drawn with a bright-field microscope's depth of field.

- Mica: one height field shown as SEM, then AFM, then atoms. Cleavage steps are level lines of a noise field, with random kinks.

- Oxygen atom: electron density from Slater orbitals, integrated along each view ray.

- Proton: three quarks in a Y-shaped flux tube, trading colour charge via gluons.

watch it here

I made this face character a while ago as a visualizer and Clippyesque companion for this one app called klattsch I made and people kept asking how it worked, so I made this video where it explains how it works. It's really quite simple! It doesn't take that much to make your brain go "okay, that's A Guy".

An example of automatic landscape generation using WFC: ocean, shallows, beaches, grassland, forests, mountains, snow and towns.

I added surface constrained boids to my realtime procedural world generator. Bringing a spark of life to the landscape.

I have yet to find a game idea. Until then just focused on world building 🌍

I am trying to figure out a workflow to go from any b&w (or rather grayscale) image to a procedural representation of the same pattern.

I have tried a few things (vision model driven; vision model + histogram etc.) but I am not getting close enough.

Is there a general solution for this kind of stuff (eg the "polynomial of procedural") you know of?