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| from torch.utils.data import Dataset | |
| from PIL import Image | |
| from utils import data_utils | |
| class ImagesDataset(Dataset): | |
| def __init__(self, source_root, target_root, opts, target_transform=None, source_transform=None): | |
| self.source_paths = sorted(data_utils.make_dataset(source_root)) | |
| self.target_paths = sorted(data_utils.make_dataset(target_root)) | |
| self.source_transform = source_transform | |
| self.target_transform = target_transform | |
| self.opts = opts | |
| def __len__(self): | |
| return len(self.source_paths) | |
| def __getitem__(self, index): | |
| from_path = self.source_paths[index] | |
| from_im = Image.open(from_path) | |
| from_im = from_im.convert('RGB') if self.opts.label_nc == 0 else from_im.convert('L') | |
| to_path = self.target_paths[index] | |
| to_im = Image.open(to_path).convert('RGB') | |
| if self.target_transform: | |
| to_im = self.target_transform(to_im) | |
| if self.source_transform: | |
| from_im = self.source_transform(from_im) | |
| else: | |
| from_im = to_im | |
| return from_im, to_im | |