FBetaDetection

class easypl.metrics.detection.f_beta.FBetaDetection(iou_threshold: Union[float, List[float]], confidence: Optional[List[float]] = None, num_classes: Optional[int] = None, beta: float = 1.0, eps: float = 1e-09, **kwargs)

Evaluate optimal confidence by F beta metric and return with precision, recall values.

iou_threshold

Iou threshold/thresholds for boxes.

Type:

Union[float, List[float]]

confidence

Confidence/confidences thresholds or None. If is None then evaluate as arange from 0 to 1 with step 0.05.

Type:

Optional[List[float]]

num_classes

Number of classes.

Type:

Optional[int]

beta

Parameter of F metric.

Type:

float

eps

Epsilon.

Type:

float

kwargs

Torchmetrics Metric args.