def label_read(path):
if (os.path.exists(path)):
pic = Image.open(path)
transform = tv.transforms.Compose([LabelToLongTensor()])
label = transform(pic)
else:
label = torch.LongTensor(1, *size).fill_(
255) # Put label that will be ignored
return label
def label_read(path):
if os.path.exists(path):
pic = Image.open(path)
transform = tv.transforms.Compose(
[tv.transforms.Resize(size, interpolation=Image.NEAREST),
LabelToLongTensor()])
label = transform(pic)
else:
label = torch.LongTensor(1,*size).fill_(255) # Put label that will be ignored
return label
def label_read(path):
pic = Image.open(path)
transform = tv.transforms.Compose([LabelToLongTensor()])
label = transform(pic)
return label