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)