code: def project_landmarks_to_shape_model(landmarks):
      final = []
  
      for lms in landmarks:
          lms = PointCloud(lms)
          similarity = AlignmentSimilarity(
              pca.global_transform.source, lms
          )
          projected_target = similarity.pseudoinverse().apply(lms)
          target = pca.model.reconstruct(projected_target)
          target = similarity.apply(target)
          final.append(target.points)
  
      return np.array(final).astype(np.float32)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  import menpo.io
  from menpo.image import Image
  from menpo.shape import PointCloud
  import cv2
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.contrib.framework.python.ops import variables
  from tensorflow.python.training import optimizer
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import variables
  from menpo.transform import Translation, Scale
  from menpo.shape import PointCloud
label_desc: Use image node_id 3 for calling a global function with example usage: project_landmarks_to_shape_model(landmarks) and returns: np