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Runtime error
| from torchvision.io import read_image, ImageReadMode | |
| import torch | |
| import numpy as np | |
| from torchvision.transforms import CenterCrop, ConvertImageDtype, Normalize, Resize | |
| from torchvision.transforms.functional import InterpolationMode | |
| from PIL import Image | |
| class Transform(torch.nn.Module): | |
| def __init__(self, image_size): | |
| super().__init__() | |
| self.transforms = torch.nn.Sequential( | |
| Resize([image_size], interpolation=InterpolationMode.BICUBIC), | |
| CenterCrop(image_size), | |
| ConvertImageDtype(torch.float), | |
| Normalize( | |
| (0.48145466, 0.4578275, 0.40821073), | |
| (0.26862954, 0.26130258, 0.27577711), | |
| ), | |
| ) | |
| def forward(self, x: torch.Tensor) -> torch.Tensor: | |
| with torch.no_grad(): | |
| x = self.transforms(x) | |
| return x | |
| transform = Transform(224) | |
| def get_transformed_image(image): | |
| if image.shape[-1] == 3 and isinstance(image, np.ndarray): | |
| image = image.transpose(2, 0, 1) | |
| image = torch.tensor(image) | |
| return transform(image).unsqueeze(0).permute(0, 2, 3, 1).numpy() |