Apply the transform to `img`.
(self, img: NdarrayOrTensor)
| 369 | return img |
| 370 | |
| 371 | def __call__(self, img: NdarrayOrTensor) -> NdarrayOrTensor: |
| 372 | """ |
| 373 | Apply the transform to `img`. |
| 374 | """ |
| 375 | img = convert_to_tensor(img, track_meta=get_track_meta(), dtype=self.dtype) |
| 376 | if self.channel_wise: |
| 377 | for i, d in enumerate(img): |
| 378 | img[i] = self._stdshift(d) # type: ignore |
| 379 | else: |
| 380 | img = self._stdshift(img) |
| 381 | return img |
| 382 | |
| 383 | |
| 384 | class RandStdShiftIntensity(RandomizableTransform): |
nothing calls this directly
no test coverage detected