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.