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Sketch to Terrain Pix2Pix

Implementation

This is my implementation of the following paper. Guérin, Éric, Julie Digne, Éric Galin, Adrien Peytavie, Christian Wolf, Bedrich Benes, and Benoît Martinez. “Interactive Example-Based Terrain Authoring with Conditional Generative Adversarial Networks.” ACM Transactions on Graphics 36, no. 6 (2017): 1–13. https://doi.org/10.1145/3130800.3130804.

I decided to use Keras with Tensorflow as backend. I used the indications provided by the author in pix2pix, with no BN. I decided to add noise to the bottleneck of the U-Net to achieve more varability and to provide more stability in training as well.

I used NASA Visible Earth Topography images to to extract the data, and pysheds and georasters to do the corresponding processing.

PySheds: https://github.com/mdbartos/pysheds GeoRasters: https://github.com/ozak/georasters

Results

Generated image is on the left. Image used to extract the sketches right.

The sketches follow the next nomeclature: ridges, rivers, peaks, basins (see paper for reference)

sketch 42 sketch 71 sketch 74 sketch 93

Discussion

I managed to replicate the results from the paper where I couldn't find the source code. I think the generator can be improved using more recent techniques like the ones I listed below. Nevertheless, the result is impressive and I want to create a fully procedurally generated Earth using Unity.

Renders

I Used Unity to generate a fully procedural render of the terrains with procedural splatmapping as well. Everything runs live, I will be sharing the code soon! Here is the result!

all_sketches

Generated DEM

DEM

Render

render

Future Work