def get_metrics(self, verbose=False) -> Dict[str, Any]:
""" Returns a dictionnary of all metrics and losses being tracked
"""
metrics = super().get_metrics(verbose)
metrics["{}_acc".format(self._stage)] = meter_value(self._obj_acc)
metrics["{}_pos".format(self._stage)] = meter_value(self._pos_ratio)
metrics["{}_neg".format(self._stage)] = meter_value(self._neg_ratio)
if self._has_box_data:
mAP = sum(self._ap.values()) / len(self._ap)
metrics["{}_map".format(self._stage)] = mAP
if verbose and self._has_box_data:
metrics["{}_class_rec".format(self._stage)] = self._dict_to_str(self._rec)
metrics["{}_class_ap".format(self._stage)] = self._dict_to_str(self._ap)
return metrics
def get_metrics(self, verbose=False) -> Dict[str, Any]:
""" Returns a dictionnary of all metrics and losses being tracked
"""
metrics = super().get_metrics(verbose)
metrics["{}_acc".format(self._stage)] = meter_value(self._acc)
return metrics
def get_metrics(self, verbose=False) -> Dict[str, float]:
""" Returns a dictionnary of all metrics and losses being tracked
"""
metrics = super().get_metrics(verbose)
metrics["{}_loss_dimension".format(self._stage)] = meter_value(
self._loss_dimension)
metrics["{}__loss_epsilon".format(self._stage)] = meter_value(
self._loss_epsilon)
metrics["{}_loss_offset".format(self._stage)] = meter_value(
self._loss_offset)
metrics["{}_mae_a1".format(self._stage)] = meter_value(
self._loss_mae_a1)
metrics["{}_mae_a2".format(self._stage)] = meter_value(
self._loss_mae_a2)
metrics["{}_mae_a3".format(self._stage)] = meter_value(
self._loss_mae_a3)
metrics["{}_mae_x0".format(self._stage)] = meter_value(
self._loss_mae_x0)
metrics["{}_mae_y0".format(self._stage)] = meter_value(
self._loss_mae_y0)
metrics["{}_mae_z0".format(self._stage)] = meter_value(
self._loss_mae_z0)
metrics["{}_mae_e1".format(self._stage)] = meter_value(
self._loss_mae_e1)
metrics["{}_mae_e2".format(self._stage)] = meter_value(
self._loss_mae_e2)
return metrics