Current implementations:

• DIAGNOSIS (MRNet based)

• DCGAN

• VQVAE - VQVAE2
• INTROVAE
• BIGAN

Own Creations:

• MoCoAE, MocoGAN
• Transition Networks for pseudo 3D analysis for DCGAN, INTROVAE, BIGAN

Install

Later this will simply be something like:

pip install deeptool

For now the source code needs to be downloaded. Then navigation to the downloaded folder is required and the package can be installed with:

pip install -e .

How to use

1. Import the library

from deeptool.train_loop import get_model, test_one_batch, main_loop
from deeptool.parameters import get_all_args, compat_args

2. Adjust the arguments for training for your needs

check parameters.py for more information about the effect of each parameter

args = get_all_args()
args.dim = 2  # Dimension of network reduced to 2
args.batch_size = 1 # How many pictures are included per training update
args.n_res_2d = 1  # architecture contains resnet blocks
args.watch_batch = 100  # visualize every 100 batches
args.model_type = "introvae"  # train the introvae model
args = compat_args(args) # solve argument interactions

3. Train the model

main_loop(args) # run the training

4. Experience Results

Watch the model improve on the task, as displayed below...