Create a mask. Args: image (`PIL.Image.Image`): The image input, should be a PIL image. Returns: `PIL.Image.Image`: The binarized image. Values less than 0.5 are set to 0, values greater than 0.5 are set to 1.
(self, image: PIL.Image.Image)
| 521 | return image |
| 522 | |
| 523 | def binarize(self, image: PIL.Image.Image) -> PIL.Image.Image: |
| 524 | """ |
| 525 | Create a mask. |
| 526 | |
| 527 | Args: |
| 528 | image (`PIL.Image.Image`): |
| 529 | The image input, should be a PIL image. |
| 530 | |
| 531 | Returns: |
| 532 | `PIL.Image.Image`: |
| 533 | The binarized image. Values less than 0.5 are set to 0, values greater than 0.5 are set to 1. |
| 534 | """ |
| 535 | image[image < 0.5] = 0 |
| 536 | image[image >= 0.5] = 1 |
| 537 | |
| 538 | return image |
| 539 | |
| 540 | def _denormalize_conditionally( |
| 541 | self, images: torch.Tensor, do_denormalize: list[bool] | None = None |
no outgoing calls
no test coverage detected