def __init__(self,
num_classes,
encoder=None): # use encoder to pass pretrained encoder
super().__init__()
if encoder is None:
self.encoder = Encoder(num_classes)
else:
self.encoder = encoder
self.decoder = erfnet.Decoder(num_classes)
def __init__(self, num_classes, encoder=None):
super().__init__()
print('Creating branched erfnet with {} classes'.format(num_classes))
if (encoder is None):
self.encoder = erfnet.Encoder(sum(num_classes))
else:
self.encoder = encoder
self.decoders = nn.ModuleList()
for n in num_classes:
self.decoders.append(erfnet.Decoder(n))
def __init__(self, num_classes, encoder=None):
super().__init__(num_classes, encoder)
self.cls_conv = erfnet.Decoder(num_classes[1] + 1)
self.seg = False
self.init_output()
def __init__(self, num_classes):
super().__init__(num_classes,
encoder=LabelEncoder(num_classes=sum(num_classes)))
self.cls_conv = erfnet.Decoder(num_classes[1] + 1)
self.seg = False