class BinaryModelConfig:

    seed = 42

    in_channels = 1

    layers_to_freeze = 0

    pre_transforms = [

        dict(

            name="Resize",

            params=dict(

                height=512,

                width=512,

                p=1.0,

            )

        ),

    ]

    augmentations = []

    post_transforms = []

    output_channels = 2

    model = 'UnetPlusPlus'

    backbone = 'resnext101_32x4d'

    encoder_weights = 'swsl'

    best_dict = 'checkpoints/Binary.pth'

    link = 'https://drive.google.com/uc?id=1uUb8rw8JM6sG9xtaahBrr4SCBcWB70qr'

class MultiModelConfig:

    seed = 42

    in_channels = 1

    layers_to_freeze = 0

    pre_transforms = [

        dict(

            name="Resize",

            params=dict(

                height=512,

                width=512,

                p=1.0,

            )

        ),

    ]

    augmentations = []

    post_transforms = []

    output_channels = 4

    model = 'UnetPlusPlus'

    backbone = 'resnet101'

    best_dict = 'checkpoints/MultiClass.pth'

    link = 'https://drive.google.com/uc?id=1W8V3t-TDXH7Bwem6-2I6vYKLmQmOiyXa'

class LungsModelConfig:

    seed = 42

    in_channels = 1

    layers_to_freeze = 0

    pre_transforms = [

        dict(

            name="Resize",

            params=dict(

                height=512,

                width=512,

                p=1.0,

            )

        ),

    ]

    augmentations = []

    post_transforms = []

    output_channels = 3

    model = 'UnetPlusPlus'

    backbone = 'resnext101_32x4d'

    encoder_weights = 'swsl'

    best_dict = 'checkpoints/Lungs.pth'

    link = 'https://drive.google.com/uc?id=1n0evx7Rk0z5MKqo1sXZtX3qkWlwAuTYB'