def _do_accumulate(self, box_xywh_gt: torch.Tensor, box_xywh_est: torch.Tensor, dp_gt: Any):
        """
        Accumulate instances data for one image, given that the data is not empty

        Args:
            box_xywh_gt (tensor): GT bounding box
            box_xywh_est (tensor): estimated bounding box
            dp_gt: GT densepose data with the following attributes:
             - x: normalized X coordinates
             - y: normalized Y coordinates
             - segm: tensor of size [S, S] with coarse segmentation
             -
        """
        self.x_gt.append(dp_gt.x)
        self.y_gt.append(dp_gt.y)
        if hasattr(dp_gt, "segm"):
            self.s_gt.append(dp_gt.segm.unsqueeze(0))
        self.vertex_ids_gt.append(dp_gt.vertex_ids)
        self.vertex_mesh_ids_gt.append(torch.full_like(dp_gt.vertex_ids, dp_gt.mesh_id))
        self.bbox_xywh_gt.append(box_xywh_gt.view(-1, 4))
        self.bbox_xywh_est.append(box_xywh_est.view(-1, 4))
        self.point_bbox_with_dp_indices.append(
            torch.full_like(dp_gt.vertex_ids, self.nxt_bbox_with_dp_index)
        )
        self.point_bbox_indices.append(torch.full_like(dp_gt.vertex_ids, self.nxt_bbox_index))
        self.bbox_indices.append(self.nxt_bbox_index)
        self.nxt_bbox_with_dp_index += 1

        Accumulate instances data for one image, given that the data is not empty

        Args:
            box_xywh_gt (tensor): GT bounding box
            box_xywh_est (tensor): estimated bounding box
            dp_gt: GT densepose data with the following attributes:
             - x: normalized X coordinates
             - y: normalized Y coordinates
             - segm: tensor of size [S, S] with coarse segmentation
             -
        
EVA-02/det/projects/DensePose/densepose/modeling/losses/embed_utils.py