From 25124b8389f80d7a509b2d98ef69589cab597c9a Mon Sep 17 00:00:00 2001 From: SsnL Date: Thu, 6 Jul 2017 22:19:53 -0500 Subject: resize_or_crop and better display single image --- data/unaligned_dataset.py | 19 ++----------------- 1 file changed, 2 insertions(+), 17 deletions(-) (limited to 'data/unaligned_dataset.py') diff --git a/data/unaligned_dataset.py b/data/unaligned_dataset.py index 7333d16..3864bf3 100644 --- a/data/unaligned_dataset.py +++ b/data/unaligned_dataset.py @@ -1,6 +1,6 @@ import os.path import torchvision.transforms as transforms -from data.base_dataset import BaseDataset +from data.base_dataset import BaseDataset, get_transform from data.image_folder import make_dataset from PIL import Image import PIL @@ -21,22 +21,7 @@ class UnalignedDataset(BaseDataset): self.B_paths = sorted(self.B_paths) self.A_size = len(self.A_paths) self.B_size = len(self.B_paths) - - transform_list = [] - if opt.resize_or_crop == 'resize_and_crop': - osize = [opt.loadSize, opt.loadSize] - transform_list.append(transforms.Scale(osize, Image.BICUBIC)) - - if opt.isTrain and not opt.no_flip: - transform_list.append(transforms.RandomHorizontalFlip()) - - if opt.resize_or_crop != 'no_resize': - transform_list.append(transforms.RandomCrop(opt.fineSize)) - - transform_list += [transforms.ToTensor(), - transforms.Normalize((0.5, 0.5, 0.5), - (0.5, 0.5, 0.5))] - self.transform = transforms.Compose(transform_list) + self.transform = get_transform(opt) def __getitem__(self, index): A_path = self.A_paths[index % self.A_size] -- cgit v1.2.3-70-g09d2