def load_dataset(self):
feeder_class = import_class(self.args.dataset)
feeder = feeder_class(self.args.data_path,
num_points=self.args.num_points,
transform=None,
phase='train')
train_data = DataLoader(dataset=feeder,
batch_size=self.args.train_batch_size,
shuffle=True,
num_workers=8)
self.dataset['train'] = train_data
self.shape_names = feeder.shape_names
self.num_classes = feeder.num_classes
self.num_parts = feeder.num_parts
self.print_log(f'Train data loaded: {len(feeder)} samples.')
if self.args.eval_model:
feeder = feeder_class(self.args.data_path,
num_points=self.args.num_points,
transform=None,
phase='test')
test_data = DataLoader(dataset=feeder,
batch_size=self.args.test_batch_size,
shuffle=False,
num_workers=8)
self.dataset['test'] = test_data
self.print_log(f'Test data loaded: {len(feeder)} samples.')
def load_transform(self):
self.transform = utils.import_class(self.args.transform)
if self.transform is not None:
transform_args = self.args.transform_args
if transform_args is None:
transform_args = dict()
self.transform = self.transform(**transform_args)
self.print_log(self.transform, print_time=False)
def load_dataset(self):
feeder_class = import_class(self.args.dataset)
feeder = feeder_class(self.args.data_path,
num_points=self.args.num_points,
transform=self.transform,
phase='train')
self.dataset['train'] = DataLoader(
dataset=feeder,
batch_size=self.args.train_batch_size,
shuffle=True,
num_workers=8)
self.print_log(f'Train data loaded: {len(feeder)} samples.')
def load_dataset(self):
feeder_class = import_class(self.args.dataset)
self.feeder = feeder_class(
self.args.data_path, num_points=self.args.num_points,
transform=None, phase='test'
)
test_data = DataLoader(
dataset=self.feeder,
batch_size=self.args.test_batch_size,
shuffle=False,
num_workers=8
)
self.dataset['test'] = test_data
self.classes_dict = self.feeder.classes_dict
self.shape_names = self.feeder.shape_names
self.num_classes = self.feeder.num_classes
self.num_parts = self.feeder.num_parts
self.print_log(f'Test data loaded: {len(self.feeder)} samples.')