Preprocess & train

“All-in-one” command.

Subsequently run the preprocessing and the training.

biom3d.preprocess_train.preprocess_train(img_path: str, msk_path: str, num_classes: str, config_dir: str = 'configs/', base_config: str | None = None, ct_norm: bool = False, desc: str = 'unet', max_dim: int = 128, num_epochs: int = 1000, is_2d: bool = False) → Builder[source]

Preprocess images and masks, then launch training with given configuration.

This function automates preprocessing configuration creation and runs the training process.

Parameters:

  • img_path (str) – Path to the collection conating images.

  • msk_path (str) – Path to the collection conating masks.

  • num_classes (int) – Number of classes for segmentation, background not included.

  • config_dir (str,default="configs/") – Directory where preprocessing configurations are saved.

  • base_config (str or None, optional) – Path to a base configuration file to start from.

  • ct_norm (bool, default=False) – Whether to apply CT normalization during preprocessing.

  • desc (str, default="unet") – Model name.

  • max_dim (int, default=128) – Maximum dimension size used in preprocessing.

  • num_epochs (int, default=1000) – Number of epochs for training.

  • is_2d (bool, default=False) – Whether to treat the input data as 2D slices.

Returns:

The Builder instance that was used to run training, which contains training details and results.

Return type:

biom3d.builder.Builder