code: def interpolate_cameras(cameras, num_samples: int):
      """Interpolates the cameras to the number of output samples.
  
      Uses a spherical linear interpolation (Slerp) to interpolate the camera
      orientations and a cubic spline to interpolate the camera positions.
  
      Args:
        cameras: the input cameras to interpolate.
        num_samples: the number of output cameras.
  
      Returns:
        (List[vision_sfm.Camera]): a list of interpolated cameras.
      """
      rotations = []
      positions = []
      for camera in cameras:
          rotations.append(camera.orientation)
          positions.append(camera.position)
  
      in_times = np.linspace(0, 1, len(rotations))
      slerp = scipy_transform.Slerp(
          in_times, scipy_transform.Rotation.from_dcm(rotations)
      )
      spline = interpolate.CubicSpline(in_times, positions)
  
      out_times = np.linspace(0, 1, num_samples)
      out_rots = slerp(out_times).as_dcm()
      out_positions = spline(out_times)
  
      ref_camera = cameras[0]
      out_cameras = []
      for out_rot, out_pos in zip(out_rots, out_positions):
          out_camera = ref_camera.copy()
          out_camera.orientation = out_rot
          out_camera.position = out_pos
          out_cameras.append(out_camera)
      return out_cameras
  
imports: import collections
  from concurrent import futures
  import contextlib
  import functools
  import time
  from typing import List, Union
  import jax
  from jax import tree_util
  import jax.numpy
  import numpy
  from scipy import interpolate
  from scipy.spatial import transform
  import tqdm
label_desc: Use image node_id 8 for calling a global function with example usage: interpolate_cameras(cameras, num_samples) and returns: out_cameras