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When reading the Deeplab V3+ code, I found it seems that current Deeplab V3+ model doesn't support ResNet-50 as backbone, and it only support ResNet-101 as backbone.
class DeepLab(BaseModel):
def __init__(self, num_classes, in_channels=3, backbone='xception', pretrained=True,
output_stride=16, freeze_bn=False, freeze_backbone=False, **_):
super(DeepLab, self).__init__()
assert ('xception' or 'resnet' in backbone)
if 'resnet' in backbone:
self.backbone = ResNet(in_channels=in_channels, output_stride=output_stride, pretrained=pretrained)
low_level_channels = 256
class ResNet(nn.Module):
def __init__(self, in_channels=3, output_stride=16, backbone='resnet101', pretrained=True):
super(ResNet, self).__init__()
model = getattr(models, backbone)(pretrained)
You can see when DeepLab class create ResNet as backbone, it doesn't pass backbone parameter.
The text was updated successfully, but these errors were encountered:
panovr
changed the title
Deeplab V3+ model doesn't support ResNet-50?
Deeplab V3+ model doesn't support ResNet-50 as backbone?
Mar 20, 2024
When reading the Deeplab V3+ code, I found it seems that current Deeplab V3+ model doesn't support ResNet-50 as backbone, and it only support ResNet-101 as backbone.
You can see when DeepLab class create ResNet as backbone, it doesn't pass backbone parameter.
The text was updated successfully, but these errors were encountered: