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rslearn.train.transforms.select_bands

select_bands

The SelectBands transform.

SelectBands

Bases: Transform

Select a subset of bands from an image.

Source code in rslearn/train/transforms/select_bands.py 
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class SelectBands(Transform):
    """Select a subset of bands from an image."""

    def __init__(
        self,
        band_indices: list[int],
        input_selector: str = "image",
        output_selector: str = "image",
        num_bands_per_timestep: int | None = None,
    ):
        """Initialize a new SelectBands.

        Args:
            band_indices: the bands to select from the channel dimension.
            input_selector: the selector to read the input image.
            output_selector: the output selector under which to save the output image.
            num_bands_per_timestep: deprecated, no longer used. Will be removed after
                2026-04-01.
        """
        super().__init__()

        if num_bands_per_timestep is not None:
            warnings.warn(
                "num_bands_per_timestep is deprecated and no longer used. "
                "It will be removed after 2026-04-01.",
                FutureWarning,
            )

        self.input_selector = input_selector
        self.output_selector = output_selector
        self.band_indices = band_indices

    def forward(
        self, input_dict: dict[str, Any], target_dict: dict[str, Any]
    ) -> tuple[dict[str, Any], dict[str, Any]]:
        """Apply band selection over the inputs and targets.

        Args:
            input_dict: the input
            target_dict: the target

        Returns:
            (input_dicts, target_dicts) tuple with selected bands
        """
        image = read_selector(input_dict, target_dict, self.input_selector)
        image.image = image.image[self.band_indices]
        write_selector(input_dict, target_dict, self.output_selector, image)
        return input_dict, target_dict

forward 

forward(input_dict: dict[str, Any], target_dict: dict[str, Any]) -> tuple[dict[str, Any], dict[str, Any]]

Apply band selection over the inputs and targets.

Parameters:

Name Type Description Default
input_dict dict[str, Any]

the input

 required
target_dict dict[str, Any]

the target

 required

Returns:

Type Description
tuple[dict[str, Any], dict[str, Any]]

(input_dicts, target_dicts) tuple with selected bands
Source code in rslearn/train/transforms/select_bands.py 
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def forward(
    self, input_dict: dict[str, Any], target_dict: dict[str, Any]
) -> tuple[dict[str, Any], dict[str, Any]]:
    """Apply band selection over the inputs and targets.

    Args:
        input_dict: the input
        target_dict: the target

    Returns:
        (input_dicts, target_dicts) tuple with selected bands
    """
    image = read_selector(input_dict, target_dict, self.input_selector)
    image.image = image.image[self.band_indices]
    write_selector(input_dict, target_dict, self.output_selector, image)
    return input_dict, target_dict