def get_training_data(self):
self.syn_loader = DataLoader(syn_dataset(train=True),
batch_size=self.batch_size,
shuffle=True,
num_workers=4)
self.real_loader = DataLoader(real_dataset(
img_transform=self.img_transform,
joint_transform=self.joint_transform,
depth_transform=self.depth_transform),
batch_size=self.batch_size,
shuffle=True,
num_workers=4)
def get_validation_data(self):
self.syn_val_dataset = syn_dataset(train=False)
self.syn_val_dataloader = DataLoader(self.syn_val_dataset,
shuffle=False,
batch_size=self.batch_size,
num_workers=4)
self.syn_val_sample_dataloader = DataLoader(self.syn_val_dataset,
shuffle=True,
batch_size=self.batch_size,
num_workers=4)
self.syn_val_sample_images, self.syn_label = next(
iter(self.syn_val_sample_dataloader))
self.syn_val_sample_images = Variable(
self.syn_val_sample_images.cuda())
self.syn_label = (1.0 + self.syn_label) / 2.0
self.real_val_dataset = real_dataset(
data_file='test.txt',
phase='test',
img_transform=self.img_transform,
joint_transform=self.joint_transform,
depth_transform=self.depth_transform)
self.real_val_dataloader = DataLoader(self.real_val_dataset,
shuffle=False,
batch_size=self.batch_size,
num_workers=4)
self.real_val_sample_dataloader = DataLoader(
self.real_val_dataset,
shuffle=True,
batch_size=self.batch_size,
num_workers=4)
self.real_val_sample_images, self.real_val_sample_filenames = next(
iter(self.real_val_sample_dataloader))
self.real_val_sample_images = self.real_val_sample_images['left_img']
self.real_val_sample_images = Variable(
self.real_val_sample_images.cuda())
def get_validation_data(self):
self.syn_val_dataloader = DataLoader(syn_dataset(train=False), batch_size=self.batch_size, shuffle=False, num_workers=4)
def get_training_data(self):
self.syn_loader = DataLoader(syn_dataset(train=True,
resize_mode='bicubic'),
batch_size=self.batch_size,
shuffle=True,
num_workers=4)
