SemiSupervisedTrackerMixin

class lightning_pose.models.base.SemiSupervisedTrackerMixin

Bases: object

Mixin class providing training step function for semi-supervised models.

Methods Summary

evaluate_unlabeled(batch_dict[, stage, ...])	Compute and log the losses on a batch of unlabeled data (frames only).
get_loss_inputs_unlabeled(batch_dict)	Return predicted heatmaps and their softmaxes (estimated keypoints).
training_step(batch_dict, batch_idx)	Training step computes and logs both supervised and unsupervised losses.

Methods Documentation

evaluate_unlabeled(batch_dict: UnlabeledBatchDict | MultiviewUnlabeledBatchDict, stage: Literal['train', 'val', 'test'] | None = None, anneal_weight: float | Tensor = 1.0) → float32), 'cls_name': 'TensorType'}]

Compute and log the losses on a batch of unlabeled data (frames only).

get_loss_inputs_unlabeled(batch_dict: UnlabeledBatchDict) → dict

Return predicted heatmaps and their softmaxes (estimated keypoints).

training_step(batch_dict: SemiSupervisedBatchDict | SemiSupervisedHeatmapBatchDict, batch_idx: int) → dict[str, ~torch.Annotated[~torch.Tensor, {'__torchtyping__': True, 'details': ((), torch.float32), 'cls_name': 'TensorType'}]]

Training step computes and logs both supervised and unsupervised losses.

__init__()