def get(cls, args):
train_file = args.train_file
val_file = args.val_file
train_dataset = cls(args,
args.data,
'train',
train_file,
args.cache,
transform=transforms.Compose([
videotransforms.RandomCrop(args.input_size),
videotransforms.RandomHorizontalFlip()
]),
input_size=args.input_size)
val_dataset = cls(args,
args.data,
'val',
val_file,
args.cache,
transform=transforms.Compose(
[videotransforms.CenterCrop(256)]),
input_size=args.input_size)
valvideo_dataset = cls(
args,
args.data,
'val_video',
val_file,
args.cache,
#transform=transforms.Compose([
# videotransforms.CenterCrop(256)
#]),
input_size=args.input_size)
return train_dataset, val_dataset, valvideo_dataset
def get(cls, args, splits=('train', 'val', 'val_video')):
train_file = args.train_file
val_file = args.val_file
if 'train' in splits:
train_dataset = cls(
args, args.data, 'train', train_file, args.cache,
transform=transforms.Compose([
videotransforms.RandomCrop(args.input_size),
videotransforms.RandomHorizontalFlip()
]),
input_size=args.input_size)
else:
train_dataset = None
if 'val' in splits:
val_dataset = cls(
args, args.data, 'val', val_file, args.cache,
transform=transforms.Compose([
videotransforms.CenterCrop(args.input_size)
]),
input_size=args.input_size)
else:
val_dataset = None
if 'val_video' in splits:
valvideo_dataset = cls(
args, args.data, 'val_video', val_file, args.cache,
transform=transforms.Compose([
videotransforms.CenterCrop(args.input_size)
]),
input_size=args.input_size)
else:
valvideo_dataset = None
return train_dataset, val_dataset, valvideo_dataset