code: def reproject(coords, camera, camera_pos, num_frames, bbox=None):
      """Reconstruct points in 3D and reproject them to pixels.
  
      Args:
        coords: Points in 3D.  It has shape [num_points, 3].  If bbox is specified,
          these are assumed to be in local box coordinates (as specified by kubric),
          and bbox will be used to put them into world coordinates; otherwise they
          are assumed to be in world coordinates.
        camera: the camera intrinsic parameters, as returned by kubric.
          'matrix_world' and 'intrinsics' have a leading axis num_frames.
        camera_pos: the camera positions.  It has shape [num_frames, 3]
        num_frames: the number of frames in the video.
        bbox: The kubric bounding box for the object.  Its first axis is num_frames.
  
      Returns:
        Image coordinates in 2D and their respective depths.  For the points,
        the last coordinate is an indicator of whether the point is behind the
        camera.  They are of shape [num_points, num_frames, 3] and
        [num_points, num_frames] respectively.
      """
      # First, reconstruct points in the local object coordinate system.
      if bbox is not None:
          coord_box = list(
              itertools.product([-0.5, 0.5], [-0.5, 0.5], [-0.5, 0.5])
          )
          coord_box = np.array([np.array(x) for x in coord_box])
          coord_box = np.concatenate(
              [coord_box, np.ones_like(coord_box[:, 0:1])], axis=1
          )
          coord_box = tf.tile(
              coord_box[tf.newaxis, ...], [num_frames, 1, 1]
          )
          bbox_homo = tf.concat(
              [bbox, tf.ones_like(bbox[:, :, 0:1])], axis=2
          )
  
          local_to_world = tf.linalg.lstsq(
              tf.cast(coord_box, tf.float32), bbox_homo
          )
          world_coords = tf.matmul(
              tf.cast(
                  tf.concat(
                      [coords, tf.ones_like(coords[:, 0:1])], axis=1
                  ),
                  tf.float32,
              )[tf.newaxis, :, :],
              local_to_world,
          )
          world_coords = (
              world_coords[:, :, 0:3] / world_coords[:, :, 3:]
          )
      else:
          world_coords = tf.tile(
              coords[tf.newaxis, :, :], [num_frames, 1, 1]
          )
  
      # Compute depths by taking the distance between the points and the camera
      # center.
      depths = tf.sqrt(
          tf.reduce_sum(
              tf.square(world_coords - camera_pos[:, np.newaxis, :]),
              axis=2,
          ),
      )
  
      # Project each point back to the image using the camera.
      projections = project_point(camera, world_coords, num_frames)
  
      return (
          tf.transpose(projections, (1, 0, 2)),
          tf.transpose(depths),
          tf.transpose(world_coords, (1, 0, 2)),
      )
  
imports: import functools
  import itertools
  import matplotlib.pyplot
  import mediapy
  import numpy
  import tensorflow.compat.v1
  import tensorflow_datasets
  from tensorflow_graphics.geometry.transformation import rotation_matrix_3d
label_desc: Use image node_id 3 for calling a global function with example usage: reproject(coords, camera, camera_pos, num_frames, bbox) and returns: tf,  tf,  tf