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tfa.losses.giou_loss

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`.

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Last updated 2021-01-15 UTC.

Args