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