diff options
| author | Taesung Park <taesung_park@berkeley.edu> | 2017-05-07 22:18:20 -0700 |
|---|---|---|
| committer | Taesung Park <taesung_park@berkeley.edu> | 2017-05-07 22:18:20 -0700 |
| commit | 5f6e2c4a115a6a706cc011b3bf9ed9e3ef149d98 (patch) | |
| tree | 29708b3526fcb354893982eab0b8d003c63bb12e /data | |
| parent | 349614a2f168654ba59bf1461ea61e1cb9358eb6 (diff) | |
1. Added flipping functionality
2. Changed the default options
Diffstat (limited to 'data')
| -rw-r--r-- | data/aligned_data_loader.py | 8 | ||||
| -rw-r--r-- | data/unaligned_data_loader.py | 14 |
2 files changed, 14 insertions, 8 deletions
diff --git a/data/aligned_data_loader.py b/data/aligned_data_loader.py index a1efde8..039c113 100644 --- a/data/aligned_data_loader.py +++ b/data/aligned_data_loader.py @@ -43,12 +43,16 @@ class AlignedDataLoader(BaseDataLoader): def initialize(self, opt): BaseDataLoader.initialize(self, opt) self.fineSize = opt.fineSize - transform = transforms.Compose([ + + transformations = [ # TODO: Scale transforms.Scale(opt.loadSize), transforms.ToTensor(), transforms.Normalize((0.5, 0.5, 0.5), - (0.5, 0.5, 0.5))]) + (0.5, 0.5, 0.5))] + if opt.isTrain and not opt.no_flip: + transformations.insert(1, transforms.RandomHorizontalFlip()) + transform = transforms.Compose(transformations) # Dataset A dataset = ImageFolder(root=opt.dataroot + '/' + opt.phase, diff --git a/data/unaligned_data_loader.py b/data/unaligned_data_loader.py index 77f9274..3deb55b 100644 --- a/data/unaligned_data_loader.py +++ b/data/unaligned_data_loader.py @@ -53,12 +53,14 @@ class PairedData(object): class UnalignedDataLoader(BaseDataLoader): def initialize(self, opt): BaseDataLoader.initialize(self, opt) - transform = transforms.Compose([ - transforms.Scale(opt.loadSize), - transforms.RandomCrop(opt.fineSize), - transforms.ToTensor(), - transforms.Normalize((0.5, 0.5, 0.5), - (0.5, 0.5, 0.5))]) + transformations = [transforms.Scale(opt.loadSize), + transforms.RandomCrop(opt.fineSize), + transforms.ToTensor(), + transforms.Normalize((0.5, 0.5, 0.5), + (0.5, 0.5, 0.5))] + if opt.isTrain and not opt.no_flip: + transformations.insert(1, transforms.RandomHorizontalFlip()) + transform = transforms.Compose(transformations) # Dataset A dataset_A = ImageFolder(root=opt.dataroot + '/' + opt.phase + 'A', |