def METHOD_NAME(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