Project Genscapes is a proof-of-concept tech demo on AI-powered procedural landscape generation. Inspired by AI-driven content creation tools such as Runway and Artbreeder, the demo uses a custom neural network model to synthesize realistic-looking landscapes.

　　A toolkit utilizing this and other exciting technologies is currently under work in progress, so stay tuned!

Features

　　Random Generation

　　Pressing run with an empty grid executes random generation, filling the grid with random samples. This is the most basic and straightforward way of retrieving samples.

　　The truncation value parameter controls the quality and variety of the sampled heightmaps. Higher truncation values result in more diverse samples, while lower truncation values result in better quality samples.

　　Proximity Search

　　Similar samples with a specific heightmap can be found using proximity search. Loading a heightmap sample into the center item of the grid switches the mode to proximity search.

　　The search distance parameter determines how similar you want the samples to be to the loaded heightmap. Higher distances result in less similar heightmaps being sampled.

　　Grid Interpolation

　　Interpolate between four samples using grid-based interpolation. By loading heightmap samples into the four edges of the grid, the mode switches to grid interpolation. You don't need to load heightmaps for all four edges to use this feature, as edges left blank will be automatically filled with a random sample.

　　Two-Point Interpolation

　　Blend between two heightmaps using two-point interpolation.

　　Visualization

　　The demo currently supports four different visualization presets. Press load and select the heightmap you wish to visualize.

Instructions