CAAI CNN template

Scripts used at CAAI group at Rigshospitalet

HOW TO USE THE SCRIPTS

Once the python libraries for training and predicting a CNN is installed, you can use it for building a new CNN, e.g. using a U-Net. All you need is:

• A main script calling the training and inference
• A data generator
• Data
• A pickle file containing the splits between training and validation

Setup local training folder

Two templates are available for main.py and data_generator.py from the github repo:

mkdir your_project
cp CAAI/CNN/scripts/* your_project

You need to edit in both files to match your project.

In the same script folder, an example file for the data split is available (generate_data_pickle.py).

Training

Once you have set up your data, data_generator and main functions, you are ready to train - just run

python3 main.py

The script will generate

• TensorBoard logs in "logs"
• Checkpoint models in "checkpoint"
• Config files in "configs"

Resume model training

If your training is interrupted, you can resume from last saved checkpoint by just running the training again, it will automatically resume training if you did not modify any of the parameters in the config.

HOW TO INSTALL

mkdir build
cd build
cmake ..
make install

POST INSTALLATION

Add "source /opt/caai/toolkit-config.sh" to .bashrc / .bash_profile

KNOWN ISSUES

Install on ubuntu

sudo make install gives error on install_manifest.txt

Solution:

Prior to install run:

sudo mkdir /opt/caai
sudo chown -R <user>:<group> /opt/caai

Proceed to install with "make install" without sudo.

Examples for usage

hello-world example

Example setting only model name, data directory and train/valid splits.

cnn = CNN(model_name='v1',
          data_pickle='/users/claes/projects/LowdosePET/PETrecon/HjerteFDG_mnc/data_6fold.pickle',
          data_folder='/users/claes/projects/LowdosePET/PETrecon/HjerteFDG_mnc'
      )
cnn.data_loader = DataGenerator(cnn.config)  

cnn.train()    

Custom network and metrics example

Use of custom network architecture and metrics imported from elsewhere.

from networks import customNET
from CAAI.losses import rmse

cnn = CNN(model_name='v1',
          data_pickle='/users/claes/projects/LowdosePET/PETrecon/HjerteFDG_mnc/data_6fold.pickle',
          data_folder='/users/claes/projects/LowdosePET/PETrecon/HjerteFDG_mnc'
      )
cnn.data_loader = DataGenerator(cnn.config)  

cnn.custom_network_architecture = customNET

cnn.metrics.append('mse')
cnn.metrics.append(rmse)
cnn.custom_objects['rmse'] = rmse
cnn.compile_network()

cnn.train()    

Custom loss

Use of custom losses

from networks import customNET
from CAAI.losses import rmse

cnn = CNN(model_name='v1',
          data_pickle='/users/claes/projects/LowdosePET/PETrecon/HjerteFDG_mnc/data_6fold.pickle',
          data_folder='/users/claes/projects/LowdosePET/PETrecon/HjerteFDG_mnc'
      )
cnn.data_loader = DataGenerator(cnn.config)  

cnn.loss_functions=[[rmse,1]]
cnn.custom_objects['rmse'] = rmse
cnn.compile_network()

cnn.train()