Example-based Terrain Generation powered by real-earth datasets.
This is a platform for me to hack around on various machine-learning content generation / manipulation techniques. It uses the Hello Worlds library to render the terrain.
The current model is very naïve, expect the output to look crap.
Terrain elevation data input
real earth terrain heightmap example used as input in GAN model
(Silly) generated terrain from the pytorch GAN model
generated terrain heightmap from the GAN model]
![generated terrain heightmap from the GAN model]](https://github.com/kenjinp/terrain-synth/blob/main/media/example-gan-output.png?raw=true){kind=link}
- pytorch for ML learning
- onnex runtime (https://onnxruntime.ai/) for model inference
- react / typescript / vite for the app
- Hello Worlds library for terrain rendering
- react-three/fiber / threejs for 3D rendering
- pulumi / aws for deployment
Earth Terrain - From Kaggle user THOMAS PAPPAS