Method inverse

monai/transforms/croppad/array.py:168–179

(self, data: MetaTensor)

        return pad_func(img_t, to_pad_, self.get_transform_info(), mode_, lazy_, **kwargs_)

    def inverse(self, data: MetaTensor) -> MetaTensor:
        transform = self.pop_transform(data)
        padded = transform[TraceKeys.EXTRA_INFO]["padded"]
        if padded[0][0] > 0 or padded[0][1] > 0:  # slicing the channel dimension
            s = padded[0][0]
            e = min(max(padded[0][1], s + 1), len(data))
            data = data[s : len(data) - e]  # type: ignore
        roi_start = [i[0] for i in padded[1:]]
        roi_end = [i - j[1] for i, j in zip(data.shape[1:], padded[1:])]
        cropper = SpatialCrop(roi_start=roi_start, roi_end=roi_end)
        with cropper.trace_transform(False):
            return cropper(data)  # type: ignore


class SpatialPad(Pad):