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main

Module for CLI functionality and entrypoint.

Contains the CLI entrypoint, the run function; and first level subcommands train and predict. The conf subcommand is added through the app.add_typer function, and its implementation is contained in the conf.py file.

predict() #

Create and save predictions from CAREamics models.

Source code in src/careamics/cli/main.py 
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@app.command()
def predict():  # numpydoc ignore=PR01
    """Create and save predictions from CAREamics models."""
    # TODO: Need a save predict to workdir function
    raise NotImplementedError

run() #

CLI Entry point.

Source code in src/careamics/cli/main.py 
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def run():
    """CLI Entry point."""
    app()

train(source, train_source, train_target=None, val_source=None, val_target=None, use_in_memory=True, val_percentage=0.1, val_minimum_split=1, work_dir=None) #

Train CAREamics models.

Source code in src/careamics/cli/main.py 
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@app.command()
def train(  # numpydoc ignore=PR01
    source: Annotated[
        Path,
        typer.Argument(
            help="Path to a configuration file or a trained model.",
            exists=True,
            file_okay=True,
            dir_okay=False,
        ),
    ],
    train_source: Annotated[
        Path,
        typer.Option(
            "--train-source",
            "-ts",
            help="Path to the training data.",
            exists=True,
            file_okay=True,
            dir_okay=True,
        ),
    ],
    train_target: Annotated[
        Optional[Path],
        typer.Option(
            "--train-target",
            "-tt",
            help="Path to train target data.",
            exists=True,
            file_okay=True,
            dir_okay=True,
        ),
    ] = None,
    val_source: Annotated[
        Optional[Path],
        typer.Option(
            "--val-source",
            "-vs",
            help="Path to validation data.",
            exists=True,
            file_okay=True,
            dir_okay=True,
        ),
    ] = None,
    val_target: Annotated[
        Optional[Path],
        typer.Option(
            "--val-target",
            "-vt",
            help="Path to validation target data.",
            exists=True,
            file_okay=True,
            dir_okay=True,
        ),
    ] = None,
    use_in_memory: Annotated[
        bool,
        typer.Option(
            "--use-in-memory/--not-in-memory",
            "-m/-M",
            help="Use in memory dataset if possible.",
        ),
    ] = True,
    val_percentage: Annotated[
        float,
        typer.Option(help="Percentage of files to use for validation."),
    ] = 0.1,
    val_minimum_split: Annotated[
        int,
        typer.Option(help="Minimum number of files to use for validation,"),
    ] = 1,
    work_dir: Annotated[
        Optional[Path],
        typer.Option(
            "--work-dir",
            "-wd",
            help=("Path to working directory in which to save checkpoints and " "logs"),
            exists=True,
            file_okay=False,
            dir_okay=True,
        ),
    ] = None,
):
    """Train CAREamics models."""
    engine = CAREamist(source=source, work_dir=work_dir)
    engine.train(
        train_source=train_source,
        val_source=val_source,
        train_target=train_target,
        val_target=val_target,
        use_in_memory=use_in_memory,
        val_percentage=val_percentage,
        val_minimum_split=val_minimum_split,
    )