CIoU Loss
CIoULoss class
keras_cv.losses.CIoULoss(bounding_box_format, eps=1e-07, **kwargs)
Implements the Complete IoU (CIoU) Loss
CIoU loss is an extension of GIoU loss, which further improves the IoU optimization for object detection. CIoU loss not only penalizes the bounding box coordinates but also considers the aspect ratio and center distance of the boxes. The length of the last dimension should be 4 to represent the bounding boxes.
Arguments
- bounding_box_format: a case-insensitive string (for example, "xyxy"). Each bounding box is defined by these 4 values. For detailed information on the supported formats, see the KerasCV bounding box documentation.
- eps: A small value added to avoid division by zero and stabilize calculations.
References
Example
y_true = np.random.uniform(
size=(5, 10, 5),
low=0,
high=10)
y_pred = np.random.uniform(
(5, 10, 4),
low=0,
high=10)
loss = keras_cv.losses.CIoULoss()
loss(y_true, y_pred).numpy()
Usage with the compile() API:
model.compile(optimizer='adam', loss=CIoULoss())