def hrnet48_unet32(input_channels=3, num_classes=1, dropout=0.0, pretrained=True): encoder = E.HRNetV2Encoder48(pretrained=pretrained) if input_channels != 3: encoder.change_input_channels(input_channels) return UnetSegmentationModel(encoder, num_classes=num_classes, unet_channels=[32, 64, 128, 256], dropout=dropout)
def hrnet48_unet64(input_channels=3, num_classes=1, dropout=0.0, pretrained=True): encoder = E.HRNetV2Encoder48(pretrained=pretrained, layers=[1, 2, 3, 4]) if input_channels != 3: encoder.change_input_channels(input_channels) return UnetV3SegmentationModel( encoder, num_classes=num_classes, unet_channels=[128, 128, 256], last_upsample_filters=64, dropout=dropout, abn_block=partial(ABN, activation=ACT_RELU), )
def hrnet48(num_classes=1, dropout=0.0, pretrained=True): encoder = E.HRNetV2Encoder48(pretrained=pretrained) return HRNetSegmentationModel(encoder, num_classes=num_classes, dropout=dropout)