To train a small U-Net with 5cm-cubed sparse voxels:

1. Download ScanNet files
2. Split the files *vh_clean_2.ply and *_vh_clean_2.labels.ply files into 'train/' and 'val/' folders
3. Run 'pip install plyfile'
4. Run 'python prepare_data.py'
5. Run 'python unet.py'

You can train a bigger/more accurate network by changing m / block_reps / residual_blocks / scale / val_reps in unet.py / data.py, e.g.

m=32 # Wider network
block_reps=2 # Deeper network
residual_blocks=True # ResNet style basic blocks
scale=50 # 1/50 m = 2cm voxels
val_reps=3 # Multiple views at test time
batch_size=5 # Fit in 16GB of GPU memory