Method get_loss

tutorials/motr/motr.py:98–105

(self, loss, outputs, gt_instances, indices, num_boxes, **kwargs)

        return num_boxes

    def get_loss(self, loss, outputs, gt_instances, indices, num_boxes, **kwargs):
        loss_map = {
            'labels': self.loss_labels,
            'cardinality': self.loss_cardinality,
            'boxes': self.loss_boxes,
        }
        assert loss in loss_map, f'do you really want to compute {loss} loss?'
        return loss_map[loss](outputs, gt_instances, indices, num_boxes, **kwargs)

    def loss_boxes(self, outputs, gt_instances: List[Instances], indices: List[tuple], num_boxes):
        """Compute the losses related to the bounding boxes, the L1 regression loss and the GIoU loss