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rslearn.models.feature_center_crop

feature_center_crop

Apply center cropping on a feature map.

FeatureCenterCrop

Bases: IntermediateComponent

Apply center cropping on the input feature maps.

Source code in rslearn/models/feature_center_crop.py 
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class FeatureCenterCrop(IntermediateComponent):
    """Apply center cropping on the input feature maps."""

    def __init__(
        self,
        sizes: list[tuple[int, int]],
    ) -> None:
        """Create a new FeatureCenterCrop.

        Only the center of each feature map will be retained and passed to the next
        module.

        Args:
            sizes: a list of (height, width) tuples, with one tuple for each input
                feature map.
        """
        super().__init__()
        self.sizes = sizes

    def forward(self, intermediates: Any, context: ModelContext) -> FeatureMaps:
        """Apply center cropping on the feature maps.

        Args:
            intermediates: output from the previous model component, which must be a FeatureMaps.
            context: the model context.

        Returns:
            center cropped feature maps.
        """
        if not isinstance(intermediates, FeatureMaps):
            raise ValueError("input to FeatureCenterCrop must be FeatureMaps")

        new_features = []
        for i, feat in enumerate(intermediates.feature_maps):
            height, width = self.sizes[i]
            if feat.shape[2] < height or feat.shape[3] < width:
                raise ValueError(
                    "feature map is smaller than the desired height and width"
                )
            start_h = feat.shape[2] // 2 - height // 2
            start_w = feat.shape[3] // 2 - width // 2
            feat = feat[:, :, start_h : start_h + height, start_w : start_w + width]
            new_features.append(feat)
        return FeatureMaps(new_features)

forward 

forward(intermediates: Any, context: ModelContext) -> FeatureMaps

Apply center cropping on the feature maps.

Parameters:

Name Type Description Default
intermediates Any

output from the previous model component, which must be a FeatureMaps.

 required
context ModelContext

the model context.

 required

Returns:

Type Description
FeatureMaps

center cropped feature maps.
Source code in rslearn/models/feature_center_crop.py 
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def forward(self, intermediates: Any, context: ModelContext) -> FeatureMaps:
    """Apply center cropping on the feature maps.

    Args:
        intermediates: output from the previous model component, which must be a FeatureMaps.
        context: the model context.

    Returns:
        center cropped feature maps.
    """
    if not isinstance(intermediates, FeatureMaps):
        raise ValueError("input to FeatureCenterCrop must be FeatureMaps")

    new_features = []
    for i, feat in enumerate(intermediates.feature_maps):
        height, width = self.sizes[i]
        if feat.shape[2] < height or feat.shape[3] < width:
            raise ValueError(
                "feature map is smaller than the desired height and width"
            )
        start_h = feat.shape[2] // 2 - height // 2
        start_w = feat.shape[3] // 2 - width // 2
        feat = feat[:, :, start_h : start_h + height, start_w : start_w + width]
        new_features.append(feat)
    return FeatureMaps(new_features)