train.md

Run trainning

The trainning creates a folder strcuture where you run the script

Run with hdf5 file

Execution

For this you need to run the HDF5 generator file from data folder

To execute the training, provide the necessary paths and configuration settings through command line arguments:

• --config_path: Path to the configuration file.
• --train_path: Path to the hdf5 file of train data.
• --val_path: Path to the hdf5 file of validation data.
• --num_channels: Number of input channels for the model [1,2,3]

Example:

python3 train.py --config_path path/to/config.yaml \
--train_path path/to/train.hdf5 \
--val_path path/to/val.hdf5 \
--num_channels 2

Run without hdf5 file

Execution

To execute the training, provide the necessary paths and configuration settings through command line arguments: ``

• --config_path: Path to the configuration file.
• --train_path: Path to the training dataset.
• --val_path: Path to the validation dataset.
• --num_channels: Number of input channels for the model. [1,2,3]

Example:

python3 train-UKbiobank.py --config_path path/to/config.yaml \
--train_path path/to/train/dataset \
--val_path path/to/val/dataset \
--num_channels 2