nicetoolbox.evaluation.metrics.keypoint.JumpDetection

class nicetoolbox.evaluation.metrics.keypoint.JumpDetection(keypoints_mapping: Dict[str, Any])

Bases: Metric

Detects jumps in keypoint sequences based on sudden large movements.

Initializes the metric. Subclasses can use kwargs for specific setup.

Methods

compute	Compute the final metric, returning both frame-based results and a summary.
get_axis3	Get the names of the joints used for jump detection.
reset	Initializes and resets the metric's internal state.
update	Detects jumps and stores the results.

compute() → Dict[Tuple[str, str, str], List[BatchResult] | AggregatedResult]

Compute the final metric, returning both frame-based results and a summary.

get_axis3(meta_chunk: ChunkWorkItem) → List[str]

Get the names of the joints used for jump detection.

reset() → None

Initializes and resets the metric’s internal state.

update(preds: torch.Tensor, gts: None, meta_chunk: ChunkWorkItem, meta_frames: List[FrameInfo]) → None

Detects jumps and stores the results.