Skip to content
  • API documentation
  • careamics_napari
  • careamics_utils
  • n2v_configs

n2v_configs

N2VAdvancedConfig #

Bases: AdvancedConfig

N2V advanced configuration.

Source code in src/careamics_napari/careamics_utils/n2v_configs.py 
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
class N2VAdvancedConfig(AdvancedConfig):
    """N2V advanced configuration."""

    use_n2v2: bool = False
    """To use N2V2"""

    roi_size: int = 11
    """The size of the area around each pixel that will be manipulated by N2V."""

    masked_pixel_percentage: float = 0.2
    """How many pixels per patch will be manipulated."""

    n_channels: int | None = None
    """Number of channels in the input image (C must be in axes)."""

masked_pixel_percentage = 0.2 class-attribute instance-attribute #

How many pixels per patch will be manipulated.

n_channels = None class-attribute instance-attribute #

Number of channels in the input image (C must be in axes).

roi_size = 11 class-attribute instance-attribute #

The size of the area around each pixel that will be manipulated by N2V.

use_n2v2 = False class-attribute instance-attribute #

To use N2V2

get_default_n2v_config() #

Return a default N2V configuration.

Source code in src/careamics_napari/careamics_utils/n2v_configs.py 
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
def get_default_n2v_config() -> BaseConfig:
    """Return a default N2V configuration."""
    num_workers = get_num_workers()

    config = create_n2v_configuration(
        experiment_name="careamics_n2v",
        data_type="array",
        axes="YX",
        patch_size=[64, 64],
        batch_size=16,
        num_epochs=30,
        independent_channels=True,
        train_dataloader_params={"num_workers": num_workers},
        val_dataloader_params={"num_workers": num_workers},
        logger="tensorboard",
    )
    config = BaseConfig(**config.model_dump(), needs_gt=False)

    return config