Spaces:
Runtime error
Runtime error
File size: 1,766 Bytes
0d2ed80 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 |
from abc import abstractmethod
import torchvision.transforms as transforms
class TransformsConfig(object):
def __init__(self, opts):
self.opts = opts
@abstractmethod
def get_transforms(self):
pass
class EncodeTransforms(TransformsConfig):
def __init__(self, opts):
super(EncodeTransforms, self).__init__(opts)
def get_transforms(self):
transforms_dict = {
'transform_gt_train': transforms.Compose([
transforms.Resize((256, 256)),
transforms.RandomHorizontalFlip(0.5),
transforms.ToTensor(),
transforms.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])]),
'transform_source': None,
'transform_test': transforms.Compose([
transforms.Resize((256, 256)),
transforms.ToTensor(),
transforms.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])]),
'transform_inference': transforms.Compose([
transforms.Resize((256, 256)),
transforms.ToTensor(),
transforms.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])])
}
return transforms_dict
class CarsEncodeTransforms(TransformsConfig):
def __init__(self, opts):
super(CarsEncodeTransforms, self).__init__(opts)
def get_transforms(self):
transforms_dict = {
'transform_gt_train': transforms.Compose([
transforms.Resize((192, 256)),
transforms.RandomHorizontalFlip(0.5),
transforms.ToTensor(),
transforms.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])]),
'transform_source': None,
'transform_test': transforms.Compose([
transforms.Resize((192, 256)),
transforms.ToTensor(),
transforms.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])]),
'transform_inference': transforms.Compose([
transforms.Resize((192, 256)),
transforms.ToTensor(),
transforms.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])])
}
return transforms_dict
|