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| from dataclasses import dataclass
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| from enum import Enum
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| from detectron2.config import CfgNode
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| class DensePoseUVConfidenceType(Enum):
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| """
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| Statistical model type for confidence learning, possible values:
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| - "iid_iso": statistically independent identically distributed residuals
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| with anisotropic covariance
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| - "indep_aniso": statistically independent residuals with anisotropic
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| covariances
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| For details, see:
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| N. Neverova, D. Novotny, A. Vedaldi "Correlated Uncertainty for Learning
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| Dense Correspondences from Noisy Labels", p. 918--926, in Proc. NIPS 2019
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| """
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| IID_ISO = "iid_iso"
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| INDEP_ANISO = "indep_aniso"
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| @dataclass
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| class DensePoseUVConfidenceConfig:
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| """
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| Configuration options for confidence on UV data
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| """
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| enabled: bool = False
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| epsilon: float = 0.01
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| type: DensePoseUVConfidenceType = DensePoseUVConfidenceType.IID_ISO
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| @dataclass
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| class DensePoseSegmConfidenceConfig:
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| """
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| Configuration options for confidence on segmentation
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| """
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| enabled: bool = False
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| epsilon: float = 0.01
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| @dataclass
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| class DensePoseConfidenceModelConfig:
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| """
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| Configuration options for confidence models
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| """
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| uv_confidence: DensePoseUVConfidenceConfig
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| segm_confidence: DensePoseSegmConfidenceConfig
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| @staticmethod
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| def from_cfg(cfg: CfgNode) -> "DensePoseConfidenceModelConfig":
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| return DensePoseConfidenceModelConfig(
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| uv_confidence=DensePoseUVConfidenceConfig(
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| enabled=cfg.MODEL.ROI_DENSEPOSE_HEAD.UV_CONFIDENCE.ENABLED,
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| epsilon=cfg.MODEL.ROI_DENSEPOSE_HEAD.UV_CONFIDENCE.EPSILON,
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| type=DensePoseUVConfidenceType(cfg.MODEL.ROI_DENSEPOSE_HEAD.UV_CONFIDENCE.TYPE),
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| ),
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| segm_confidence=DensePoseSegmConfidenceConfig(
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| enabled=cfg.MODEL.ROI_DENSEPOSE_HEAD.SEGM_CONFIDENCE.ENABLED,
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| epsilon=cfg.MODEL.ROI_DENSEPOSE_HEAD.SEGM_CONFIDENCE.EPSILON,
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| ),
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| )
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