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import os
from torch.utils.data import Dataset
from PIL import Image
from PTI.utils.data_utils import make_dataset
from torchvision import transforms
class Image2Dataset(Dataset):
def __init__(self, image) -> None:
super().__init__()
self.image = image
self.transform = transforms.Compose(
[
transforms.ToTensor(),
transforms.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5]),
]
)
def __len__(self):
return 1
def __getitem__(self, index):
return "customIMG", self.transform(self.image)
class ImagesDataset(Dataset):
def __init__(self, source_root, source_transform=None):
self.source_paths = sorted(make_dataset(source_root))
self.source_transform = source_transform
def __len__(self):
return len(self.source_paths)
def __getitem__(self, index):
fname, from_path = self.source_paths[index]
from_im = Image.open(from_path).convert("RGB").resize([1024, 1024])
if self.source_transform:
from_im = self.source_transform(from_im)
return fname, from_im
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