tfa.losses.giou_loss

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Implements the GIoU loss function.

tfa.losses.giou_loss(
    y_true: tfa.image.color_ops.TensorLike,
    y_pred: tfa.image.color_ops.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.

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.

GIoU loss float Tensor.