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