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from dataclasses import dataclass, field |
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from typing import Any, Dict, Optional |
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@dataclass |
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class LossConfiguration: |
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num_classes: int |
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xent_weight: float = 1.0 |
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dice_weight: float = 1.0 |
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focal_loss: bool = False |
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focal_loss_gamma: float = 2.0 |
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requires_frustrum: bool = True |
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requires_flood_mask: bool = False |
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class_weights: Optional[Any] = None |
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label_smoothing: float = 0.1 |
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@dataclass |
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class BackboneConfigurationBase: |
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pretrained: bool |
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frozen: bool |
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output_dim: bool |
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@dataclass |
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class DINOConfiguration(BackboneConfigurationBase): |
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pretrained: bool = True |
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frozen: bool = False |
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output_dim: int = 128 |
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@dataclass |
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class ResNetConfiguration(BackboneConfigurationBase): |
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input_dim: int |
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encoder: str |
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remove_stride_from_first_conv: bool |
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num_downsample: Optional[int] |
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decoder_norm: str |
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do_average_pooling: bool |
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checkpointed: bool |
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@dataclass |
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class ImageEncoderConfiguration: |
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name: str |
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backbone: Any |
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@dataclass |
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class ModelConfiguration: |
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segmentation_head: Dict[str, Any] |
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image_encoder: ImageEncoderConfiguration |
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name: str |
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num_classes: int |
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latent_dim: int |
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z_max: int |
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x_max: int |
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pixel_per_meter: int |
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num_scale_bins: int |
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loss: LossConfiguration |
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scale_range: list[int] = field(default_factory=lambda: [0, 9]) |
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z_min: Optional[int] = None |
