tensorflow下的Mask RCNN的CIOU损失函数代码

以下是tensorflow下的Mask RCNN的CIOU损失函数代码，参考自https://github.com/matterport/Mask_RCNN/blob/master/mrcnn/model.py：

def ciou_loss(gt_bbox, pred_bbox):
    """
    Compute the Complete IoU (CIoU) loss between ground truth bounding boxes and predicted bounding boxes.

    Arguments:
    gt_bbox -- tensor of shape (batch_size, 4) representing the ground truth bounding boxes
    pred_bbox -- tensor of shape (batch_size, 4) representing the predicted bounding boxes

    Returns:
    ciou_loss -- tensor of shape () representing the CIoU loss
    """

    # Calculate IoU
    iou = bbox_iou(gt_bbox, pred_bbox)

    # Calculate IoU penalty term
    v = ((4 / (math.pi ** 2)) * tf.square(tf.math.atan2(gt_bbox[:, 2], gt_bbox[:, 3]) 
         - tf.math.atan2(pred_bbox[:, 2], pred_bbox[:, 3])))
    alpha = v / (1 - iou + v)

    # Calculate center distance term
    gt_center_x = (gt_bbox[:, 0] + gt_bbox[:, 2]) / 2
    gt_center_y = (gt_bbox[:, 1] + gt_bbox[:, 3]) / 2
    pred_center_x = (pred_bbox[:, 0] + pred_bbox[:, 2]) / 2
    pred_center_y = (pred_bbox[:, 1] + pred_bbox[:, 3]) / 2
    center_distance = tf.square(gt_center_x - pred_center_x) + tf.square(gt_center_y - pred_center_y)

    # Calculate width and height term
    gt_width = tf.math.abs(gt_bbox[:, 2] - gt_bbox[:, 0])
    gt_height = tf.math.abs(gt_bbox[:, 3] - gt_bbox[:, 1])
    pred_width = tf.math.abs(pred_bbox[:, 2] - pred_bbox[:, 0])
    pred_height = tf.math.abs(pred_bbox[:, 3] - pred_bbox[:, 1])
    v1 = tf.math.log(gt_width / pred_width)
    v2 = tf.math.log(gt_height / pred_height)
    w = (v1 + v2) / 2
    ciou = iou - alpha * (center_distance / (tf.square(w) + tf.square(1 - iou) - center_distance + alpha))

    # Calculate CIoU loss
    ciou_loss = 1 - ciou

    return ciou_loss