| import PIL.Image
|
| import PIL.ImageOps
|
| from packaging import version
|
| from PIL import Image
|
|
|
|
|
| if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"):
|
| PIL_INTERPOLATION = {
|
| "linear": PIL.Image.Resampling.BILINEAR,
|
| "bilinear": PIL.Image.Resampling.BILINEAR,
|
| "bicubic": PIL.Image.Resampling.BICUBIC,
|
| "lanczos": PIL.Image.Resampling.LANCZOS,
|
| "nearest": PIL.Image.Resampling.NEAREST,
|
| }
|
| else:
|
| PIL_INTERPOLATION = {
|
| "linear": PIL.Image.LINEAR,
|
| "bilinear": PIL.Image.BILINEAR,
|
| "bicubic": PIL.Image.BICUBIC,
|
| "lanczos": PIL.Image.LANCZOS,
|
| "nearest": PIL.Image.NEAREST,
|
| }
|
|
|
|
|
| def pt_to_pil(images):
|
| images = (images / 2 + 0.5).clamp(0, 1)
|
| images = images.cpu().permute(0, 2, 3, 1).float().numpy()
|
| images = numpy_to_pil(images)
|
| return images
|
|
|
|
|
| def numpy_to_pil(images):
|
| """
|
| Convert a numpy image or a batch of images to a PIL image.
|
| """
|
| if images.ndim == 3:
|
| images = images[None, ...]
|
| images = (images * 255).round().astype("uint8")
|
| if images.shape[-1] == 1:
|
|
|
| pil_images = [Image.fromarray(image.squeeze(), mode="L") for image in images]
|
| else:
|
| pil_images = [Image.fromarray(image) for image in images]
|
|
|
| return pil_images
|
|
|
