commit from $USER

configs/data_configs.py

@@ -1,41 +0,0 @@
-from configs import transforms_config
-from configs.paths_config import dataset_paths
-
-
-DATASETS = {
-	'ffhq_encode': {
-		'transforms': transforms_config.EncodeTransforms,
-		'train_source_root': dataset_paths['ffhq'],
-		'train_target_root': dataset_paths['ffhq'],
-		'test_source_root': dataset_paths['celeba_test'],
-		'test_target_root': dataset_paths['celeba_test'],
-	},
-	'cars_encode': {
-		'transforms': transforms_config.CarsEncodeTransforms,
-		'train_source_root': dataset_paths['cars_train'],
-		'train_target_root': dataset_paths['cars_train'],
-		'test_source_root': dataset_paths['cars_test'],
-		'test_target_root': dataset_paths['cars_test'],
-	},
-	'horse_encode': {
-		'transforms': transforms_config.EncodeTransforms,
-		'train_source_root': dataset_paths['horse_train'],
-		'train_target_root': dataset_paths['horse_train'],
-		'test_source_root': dataset_paths['horse_test'],
-		'test_target_root': dataset_paths['horse_test'],
-	},
-	'church_encode': {
-		'transforms': transforms_config.EncodeTransforms,
-		'train_source_root': dataset_paths['church_train'],
-		'train_target_root': dataset_paths['church_train'],
-		'test_source_root': dataset_paths['church_test'],
-		'test_target_root': dataset_paths['church_test'],
-	},
-	'cats_encode': {
-		'transforms': transforms_config.EncodeTransforms,
-		'train_source_root': dataset_paths['cats_train'],
-		'train_target_root': dataset_paths['cats_train'],
-		'test_source_root': dataset_paths['cats_test'],
-		'test_target_root': dataset_paths['cats_test'],
-	}
-}

configs/paths_config.py

@@ -1,28 +0,0 @@
-dataset_paths = {
-	#  Face Datasets (In the paper: FFHQ - train, CelebAHQ - test)
-	'ffhq': '',
-	'celeba_test': '',
-
-	#  Cars Dataset (In the paper: Stanford cars)
-	'cars_train': '',
-	'cars_test': '',
-
-	#  Horse Dataset (In the paper: LSUN Horse)
-	'horse_train': '',
-	'horse_test': '',
-
-	#  Church Dataset (In the paper: LSUN Church)
-	'church_train': '',
-	'church_test': '',
-
-	#  Cats Dataset (In the paper: LSUN Cat)
-	'cats_train': '',
-	'cats_test': ''
-}
-
-model_paths = {
-	'stylegan_ffhq': 'pretrained_models/stylegan2-ffhq-config-f.pt',
-	'ir_se50': 'pretrained_models/model_ir_se50.pth',
-	'shape_predictor': 'pretrained_models/shape_predictor_68_face_landmarks.dat',
-	'moco': 'pretrained_models/moco_v2_800ep_pretrain.pth'
-}

configs/transforms_config.py

@@ -1,62 +0,0 @@
-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