def __getitem__(self, index):
file_name = [self.dataset_dir + self.file_list[index]]
with h5py.File(file_name[0], 'r') as hf:
data_SAI_y = np.array(hf.get('Lr_SAI_y'))
label_SAI_y = np.array(hf.get('Hr_SAI_y'))
data_SAI_y, label_SAI_y = augmentation(data_SAI_y, label_SAI_y)
data_SAI_y = ToTensor()(data_SAI_y.copy())
label_SAI_y = ToTensor()(label_SAI_y.copy())
return data_SAI_y, label_SAI_y
def __getitem__(self, index):
dataset_dir = self.dataset_dir
index = index + 1
file_name = [dataset_dir + '/%06d' % index + '.h5']
with h5py.File(file_name[0], 'r') as hf:
data = np.array(hf.get('data'))
label = np.array(hf.get('label'))
data, label = augmentation(data, label)
data = ToTensor()(data.copy())
label = ToTensor()(label.copy())
return data, label
def __getitem__(self, index):
file_name = [self.dataset_dir + self.file_list[index]]
with h5py.File(file_name[0], 'r') as hf:
Lr_SAI_y = np.array(hf.get('Lr_SAI_y'))
Hr_SAI_y = np.array(hf.get('Hr_SAI_y'))
Lr_SAI_y = np.transpose(Lr_SAI_y, (1, 0))
Hr_SAI_y = np.transpose(Hr_SAI_y, (1, 0))
Lr_SAI_y = ToTensor()(Lr_SAI_y.copy())
Hr_SAI_y = ToTensor()(Hr_SAI_y.copy())
return Lr_SAI_y, Hr_SAI_y
def __getitem__(self, index):
file_name = self.dataset_dir + '/' + self.file_list[index]
with h5py.File(file_name, 'r') as hf:
data = np.array(hf.get('data'))
label = np.array(hf.get('label'))
data, label = np.transpose(data, (1, 0)), np.transpose(label, (1, 0))
data, label = ToTensor()(data.copy()), ToTensor()(label.copy())
return data, label
