def get_tracker(self, wandb_log: bool, tensorboard_log: bool): """ Factory method for the tracker Arguments: wandb_log - Log using weight and biases tensorboard_log - Log using tensorboard Returns: [BaseTracker] -- tracker """ if self.is_patch: return PatchRegistrationTracker(self, wandb_log=wandb_log, use_tensorboard=tensorboard_log) else: if self.is_end2end: raise NotImplementedError("implement end2end tracker") else: return FragmentRegistrationTracker( num_points=self.num_points, tau_1=self.tau_1, tau_2=self.tau_2, rot_thresh=self.rot_thresh, trans_thresh=self.trans_thresh, wandb_log=wandb_log, use_tensorboard=tensorboard_log)
def get_tracker(self, wandb_log: bool, tensorboard_log: bool): """ Factory method for the tracker Arguments: wandb_log - Log using weight and biases tensorboard_log - Log using tensorboard Returns: [BaseTracker] -- tracker """ if self.is_patch: return PatchRegistrationTracker(self, wandb_log=wandb_log, use_tensorboard=tensorboard_log) else: return FragmentRegistrationTracker(self, wandb_log=wandb_log, use_tensorboard=tensorboard_log)
def get_tracker(model, dataset, wandb_log: bool, tensorboard_log: bool): """ Factory method for the tracker Arguments: task {str} -- task description dataset {[type]} wandb_log - Log using weight and biases Returns: [BaseTracker] -- tracker """ if (dataset.is_patch): return PatchRegistrationTracker(dataset, wandb_log=wandb_log, use_tensorboard=tensorboard_log) else: return FragmentRegistrationTracker(dataset, wandb_log=wandb_log, use_tensorboard=tensorboard_log)