def resnet101_unet64(input_channels=3,
num_classes=1,
dropout=0.5,
pretrained=True):
encoder = E.Resnet101Encoder(pretrained=pretrained, layers=[0, 1, 2, 3, 4])
if input_channels != 3:
encoder.change_input_channels(input_channels)
return UnetSegmentationModel(encoder,
num_classes=num_classes,
unet_channels=[64, 128, 256, 512],
dropout=dropout)
def resnet101_fpncatv2_256(num_classes=5,
dropout=0.0,
pretrained=True,
classifiers=True):
encoder = E.Resnet101Encoder(pretrained=pretrained)
return FPNCatSegmentationModelV2(
encoder,
num_classes=num_classes,
disaster_type_classes=len(DISASTER_TYPES) if classifiers else None,
damage_type_classes=len(DAMAGE_TYPES) if classifiers else None,
fpn_channels=256,
dropout=dropout,
abn_block=partial(ABN, activation=ACT_RELU),
)
def resnet101_unet_v2(input_channels=6,
num_classes=5,
dropout=0.0,
pretrained=True,
classifiers=True):
encoder = E.Resnet101Encoder(pretrained=pretrained, layers=[0, 1, 2, 3, 4])
return UnetV2SegmentationModel(
encoder,
num_classes=num_classes,
disaster_type_classes=len(DISASTER_TYPES) if classifiers else None,
damage_type_classes=len(DAMAGE_TYPES) if classifiers else None,
unet_channels=[64, 128, 256, 384],
dropout=dropout,
abn_block=partial(ABN, activation=ACT_RELU),
)
def resnet101_fpn(num_classes=1, fpn_features=256):
encoder = E.Resnet101Encoder()
return FPNSegmentationModel(encoder, num_classes, fpn_features)