GoodWin/Deep-Multi-scale

1import os.path2from data.base_dataset import BaseDataset, get_transform3from data.image_folder import make_dataset4from PIL import Image5 6 7class SingleDataset(BaseDataset):8    @staticmethod9    def modify_commandline_options(parser, is_train):10        return parser11 12    def initialize(self, opt):13        self.opt = opt14        self.root = opt.dataroot15        self.dir_A = os.path.join(opt.dataroot)16 17        self.A_paths = make_dataset(self.dir_A)18 19        self.A_paths = sorted(self.A_paths)20 21        self.transform = get_transform(opt)22 23    def __getitem__(self, index):24        A_path = self.A_paths[index]25        A_img = Image.open(A_path).convert('RGB')26        A = self.transform(A_img)27        if self.opt.which_direction == 'BtoA':28            input_nc = self.opt.output_nc29        else:30            input_nc = self.opt.input_nc31 32        if input_nc == 1:  # RGB to gray33            tmp = A[0, ...] * 0.299 + A[1, ...] * 0.587 + A[2, ...] * 0.11434            A = tmp.unsqueeze(0)35 36        return {'A': A, 'A_paths': A_path}37 38    def __len__(self):39        return len(self.A_paths)40 41    def name(self):42        return 'SingleImageDataset'43