def create_loss(self,
box_preds,
cls_preds,
cls_targets,
cls_weights,
reg_targets,
reg_weights,
num_class,
use_sigmoid_cls=True,
encode_rad_error_by_sin=True,
box_code_size=7):
batch_size = int(box_preds.shape[0])
box_preds = box_preds.view(batch_size, -1, box_code_size)
if use_sigmoid_cls:
cls_preds = cls_preds.view(batch_size, -1, num_class)
else:
cls_preds = cls_preds.view(batch_size, -1, num_class + 1)
one_hot_targets = one_hot(
cls_targets, depth=num_class + 1, dtype=box_preds.dtype)
if use_sigmoid_cls:
one_hot_targets = one_hot_targets[..., 1:]
if encode_rad_error_by_sin:
# sin(a - b) = sinacosb-cosasinb
box_preds, reg_targets = self.add_sin_difference(box_preds, reg_targets)
loc_losses = weighted_smoothl1(box_preds, reg_targets, beta=1 / 9., \
weight=reg_weights[..., None], avg_factor=1.)
cls_losses = weighted_sigmoid_focal_loss(cls_preds, one_hot_targets, \
weight=cls_weights[..., None], avg_factor=1.)
return loc_losses, cls_losses
def get_direction_target(self, anchors, reg_targets, use_one_hot=True):
batch_size = reg_targets.shape[0]
anchors = anchors.view(batch_size, -1, 7)
rot_gt = reg_targets[..., -1] + anchors[..., -1]
dir_cls_targets = (rot_gt > 0).long()
if use_one_hot:
dir_cls_targets = one_hot(dir_cls_targets, 2, dtype=anchors.dtype)
return dir_cls_targets
