(num_classes=21, output_stride=8, pretrained_backbone=True)
return _load_model('deeplabv3plus', 'resnet50', num_classes, output_stride=output_stride, pretrained_backbone=pretrained_backbone)
Constructs a DeepLabV3 model with a ResNet-50 backbone.

    Args:
        num_classes (int): number of classes.
        output_stride (int): output stride for deeplab.
        pretrained_backbone (bool): If True, use the pretrained backbone.
Constructs a DeepLabV3 model with a ResNet-50 backbone.
Constructs a DeepLabV3 model with a ResNet - 50 backbone .
def deeplabv3plus_resnet50(num_classes=21, output_stride=8, pretrained_backbone=True):
    """Constructs a DeepLabV3 model with a ResNet-50 backbone.

    Args:
        num_classes (int): number of classes.
        output_stride (int): output stride for deeplab.
        pretrained_backbone (bool): If True, use the pretrained backbone.
    """
    return _load_model('deeplabv3plus', 'resnet50', num_classes, output_stride=output_stride, pretrained_backbone=pretrained_backbone)
def deeplabv3plus_resnet50 ( num_classes = 21 , output_stride = 8 , pretrained_backbone = True ) : return _load_model ( 'deeplabv3plus' , 'resnet50' , num_classes , output_stride = output_stride , pretrained_backbone = pretrained_backbone )