Apply the transform to `img`.
(self, img: NdarrayOrTensor, offset: float | None = None)
| 246 | self.safe = safe |
| 247 | |
| 248 | def __call__(self, img: NdarrayOrTensor, offset: float | None = None) -> NdarrayOrTensor: |
| 249 | """ |
| 250 | Apply the transform to `img`. |
| 251 | """ |
| 252 | |
| 253 | img = convert_to_tensor(img, track_meta=get_track_meta()) |
| 254 | offset = self.offset if offset is None else offset |
| 255 | out = img + offset |
| 256 | out, *_ = convert_data_type(data=out, dtype=img.dtype, safe=self.safe) |
| 257 | |
| 258 | return out |
| 259 | |
| 260 | |
| 261 | class RandShiftIntensity(RandomizableTransform): |
nothing calls this directly
no test coverage detected