deeplabcut.pose_estimation_pytorch.config.model

Model configuration class for DeepLabCut pose estimation models.

Classes:

Name	Description
DetectorModelConfig	Configuration for detector models
ModelConfig	Complete model configuration.

DetectorModelConfig

Bases: DLCBaseConfig

Configuration for detector models

Attributes:

Name	Type	Description
type	str	Type of detector model (e.g., FasterRCNN)
freeze_bn_stats	bool	Whether to freeze batch normalization statistics
freeze_bn_weights	bool	Whether to freeze batch normalization weights
variant	str | None	Specific variant of the detector model
box_score_thresh	DefaultIfNone[Fraction]	The score below which the detector discards proposals internally. null is normalized to the default. The value is deliberately permissive, as raising this value silently drops detections. Note the distinction with bboxes_pcutoff in the project config, which is the cutoff used to plot bounding boxes.

Source code in deeplabcut/pose_estimation_pytorch/config/model.py

class DetectorModelConfig(DLCBaseConfig):
    """Configuration for detector models

    Attributes:
        type: Type of detector model (e.g., FasterRCNN)
        freeze_bn_stats: Whether to freeze batch normalization statistics
        freeze_bn_weights: Whether to freeze batch normalization weights
        variant: Specific variant of the detector model
        box_score_thresh: The score below which the detector discards proposals
            internally. ``null`` is normalized to the default. The value is
            deliberately permissive, as raising this value silently drops
            detections. Note the distinction with ``bboxes_pcutoff`` in the
            project config, which is the cutoff used to *plot* bounding boxes.
    """

    type: str = ""
    freeze_bn_stats: bool = False
    freeze_bn_weights: bool = False
    variant: str | None = None
    box_score_thresh: DefaultIfNone[Fraction] = 0.01

ModelConfig

Bases: DLCBaseConfig

Complete model configuration.

Attributes:

Name	Type	Description
backbone	dict	Backbone configuration
backbone_output_channels	int | None	Number of output channels from backbone
heads	dict[str, dict]	Dictionary of head configurations by name
neck	dict | None	Neck configuration
pose_model	dict | None	Pose model configuration

Source code in deeplabcut/pose_estimation_pytorch/config/model.py

class ModelConfig(DLCBaseConfig):
    """Complete model configuration.

    Attributes:
        backbone: Backbone configuration
        backbone_output_channels: Number of output channels from backbone
        heads: Dictionary of head configurations by name
        neck: Neck configuration
        pose_model: Pose model configuration
    """

    backbone: dict = Field(default_factory=dict)
    heads: dict[str, dict] = Field(default_factory=dict)
    backbone_output_channels: int | None = None
    neck: dict | None = None
    pose_model: dict | None = None