| import os.path | |
| import torchvision.transforms as transforms | |
| from data.base_dataset import BaseDataset, get_transform | |
| from data.image_folder import make_dataset | |
| from PIL import Image | |
| class SingleDataset(BaseDataset): | |
| def initialize(self, opt): | |
| self.opt = opt | |
| self.root = opt.dataroot | |
| self.dir_A = os.path.join(opt.dataroot) | |
| self.A_paths = make_dataset(self.dir_A) | |
| self.A_paths = sorted(self.A_paths) | |
| self.transform = get_transform(opt) | |
| def __getitem__(self, index): | |
| A_path = self.A_paths[index] | |
| A_img = Image.open(A_path).convert('RGB') | |
| A_size = A_img.size | |
| A_size = A_size = (A_size[0]//16*16, A_size[1]//16*16) | |
| A_img = A_img.resize(A_size, Image.BICUBIC) | |
| A_img = self.transform(A_img) | |
| return {'A': A_img, 'A_paths': A_path} | |
| def __len__(self): | |
| return len(self.A_paths) | |
| def name(self): | |
| return 'SingleImageDataset' | |