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How to run the proof-of-concept experiment

cd experiments/poc/

  1. Generate the proof-of-concept dataset (2D and 3D)

    python generate_poc_data.py

  2. Train the 2D UNet on 2D dataset

    python train_2d.py

  3. Locate where the 2D model checkpoint is saved (in ./tmp/noise0.5/shape/.../model.dat and then copy the path to POCVoxelEnv.shape_checkpoint in poc_config.py

  4. Train the 3D UNet on 3D volumesset, with or without 2D pretraining

    python train_3d.py

The default 3D model is ACSUNet p.. To change ACSConv to Conv3d / Conv2_5d or random initialization, modify POCVoxelConfig.conv and POCVoxelConfig.pretrained in poc_config.py.