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model.py
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model.py
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### Initializing model
import segmentation_models_pytorch as smp
def load_model(
train_model: str,
backbone: str,
backbone_weight: str
):
model_choices = ["U-Net", "DeepLab", "FPN", "U-Net++", "MANet", "PSPNet", "DeepLab+"]
if train_model == model_choices[0]:
model = smp.Unet(
encoder_name=backbone,
encoder_weights=backbone_weight,
in_channels=1,
classes=1,
)
if train_model == model_choices[1]:
model = smp.DeepLabV3(
encoder_name=backbone,
encoder_weights=backbone_weight,
in_channels=1,
classes=1,
)
if train_model == model_choices[2]:
model = smp.FPN(
encoder_name=backbone,
encoder_weights=backbone_weight,
in_channels=1,
classes=1,
)
if train_model == model_choices[3]:
model = smp.UnetPlusPlus(
encoder_name=backbone,
encoder_weights=backbone_weight,
in_channels=1,
classes=1,
)
if train_model == model_choices[4]:
model = smp.MAnet(
encoder_name=backbone,
encoder_weights=backbone_weight,
in_channels=1,
classes=1,
)
if train_model == model_choices[5]:
model = smp.PSPNet(
encoder_name=backbone,
encoder_weights=backbone_weight,
in_channels=1,
classes=1,
)
if train_model == model_choices[6]:
model = smp.DeepLabV3Plus(
encoder_name=backbone,
encoder_weights=backbone_weight,
in_channels=1,
classes=1,
)
return model