(data: np.ndarray)
| 38 | """ |
| 39 | |
| 40 | def _compute(data: np.ndarray) -> np.ndarray: |
| 41 | scaler = ScaleIntensity(minv=1.0, maxv=0.0) |
| 42 | return np.stack([scaler(i) for i in data], axis=0) |
| 43 | |
| 44 | if isinstance(x, torch.Tensor): |
| 45 | return torch.as_tensor(_compute(x.detach().cpu().numpy()), device=x.device) # type: ignore |
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