code: def get_geometry_data(
      geometry_filename: str,
  ) -> List[List[torch.Tensor]]:
      """
      Utils function for parsing metadata files from the Objectron GitHub repo:
      https://github.com/google-research-datasets/Objectron/blob/master/notebooks/objectron-geometry-tutorial.ipynb  # noqa: B950
      """
      sequence_geometry = []
      with open(geometry_filename, "rb") as pb:
          proto_buf = pb.read()
  
          i = 0
          while i < len(proto_buf):
              # Read the first four Bytes in little endian '<' integers 'I' format
              # indicating the length of the current message.
              msg_len = struct.unpack("<I", proto_buf[i : i + 4])[0]
              i += 4
              message_buf = proto_buf[i : i + msg_len]
              i += msg_len
              frame_data = ar_metadata_protocol.ARFrame()
              frame_data.ParseFromString(message_buf)
  
              projection = np.reshape(
                  frame_data.camera.projection_matrix, (4, 4)
              )
              view = np.reshape(frame_data.camera.view_matrix, (4, 4))
  
              projection = torch.tensor(projection, dtype=torch.float32)
              view = torch.tensor(view, dtype=torch.float32)
  
              sequence_geometry.append((projection, view))
      return sequence_geometry
  
file_path: pytorchvideo/projects/video_nerf/dataset_utils.py
imports: import os
  import struct
  import sys
  from typing import List, Tuple
  import numpy
  import torch
  from objectron.schema import a_r_capture_metadata_pb2
  from PIL import Image
  from pytorch3d.transforms import Rotate, RotateAxisAngle, Translate
label_desc: Use image node_id 3 for calling a global function with example usage: get_geometry_data(geometry_filename) and returns: sequence_geometry