Implements the GIoU loss function.
tfa.losses.giou_loss(
y_true: tfa.types.TensorLike
,
y_pred: tfa.types.TensorLike
,
mode: str = 'giou'
) -> tf.Tensor
GIoU loss was first introduced in the
Generalized Intersection over Union:
A Metric and A Loss for Bounding Box Regression.
GIoU is an enhancement for models which use IoU in object detection.
Args |
y_true
|
true targets tensor. The coordinates of the each bounding
box in boxes are encoded as [y_min, x_min, y_max, x_max].
|
y_pred
|
predictions tensor. The coordinates of the each bounding
box in boxes are encoded as [y_min, x_min, y_max, x_max].
|
mode
|
one of ['giou', 'iou'], decided to calculate GIoU or IoU loss.
|
Returns |
GIoU loss float Tensor .
|