code: def _create_instances_sparsedp(self):
      image_shape = (540, 720)
      instances = Instances(image_shape)
      instances.gt_boxes = Boxes(
          torch.as_tensor(
              [
                  [50.0, 50.0, 130.0, 130.0],
                  [150.0, 150.0, 240.0, 240.0],
                  [50.0, 150.0, 230.0, 330.0],
              ]
          )
      )
      instances.proposal_boxes = Boxes(
          torch.as_tensor(
              [
                  [49.0, 51.0, 131.0, 129.0],
                  [151.0, 149.0, 241.0, 239.0],
                  [51.0, 149.0, 232.0, 329.0],
              ]
          )
      )
      instances.gt_densepose = DensePoseList(
          [
              None,
              self._create_dp_data(
                  {
                      "dp_x": [81.69, 153.47, 151.00],
                      "dp_y": [162.24, 128.71, 113.81],
                      "dp_vertex": [0, 1, 2],
                      "ref_model": "zebra_5002",
                      "dp_masks": [],
                  },
                  {"c": (166, 133), "r": 64},
              ),
              None,
          ],
          instances.gt_boxes,
          image_shape,
      )
      return instances
  
file_path: detectron2/projects/DensePose/tests/test_cse_annotations_accumulator.py
imports: import unittest
  import torch
  from detectron2.structures import Boxes, BoxMode, Instances
  from densepose.modeling.losses.embed_utils import CseAnnotationsAccumulator
  from densepose.structures import DensePoseDataRelative, DensePoseList
label_desc: Use image node_id 7 for calling the TestCseAnnotationsAccumulator obj's underlying member method code with example usage: obj._create_instances_sparsedp() and returns: instances