code: def scale_boxes_to_pixel_coordinates(image, boxes, keypoints=None):
      """Scales boxes from normalized to pixel coordinates.
  
      Args:
        image: A 3D float32 tensor of shape [height, width, channels].
        boxes: A 2D float32 tensor of shape [num_boxes, 4] containing the bounding
          boxes in normalized coordinates. Each row is of the form
          [ymin, xmin, ymax, xmax].
        keypoints: (optional) rank 3 float32 tensor with shape
          [num_instances, num_keypoints, 2]. The keypoints are in y-x normalized
          coordinates.
  
      Returns:
        image: unchanged input image.
        scaled_boxes: a 2D float32 tensor of shape [num_boxes, 4] containing the
          bounding boxes in pixel coordinates.
        scaled_keypoints: a 3D float32 tensor with shape
          [num_instances, num_keypoints, 2] containing the keypoints in pixel
          coordinates.
      """
      boxlist = box_list.BoxList(boxes)
      image_height = tf.shape(image)[0]
      image_width = tf.shape(image)[1]
      scaled_boxes = box_list_scale(
          boxlist, image_height, image_width
      ).get()
      result = [image, scaled_boxes]
      if keypoints is not None:
          scaled_keypoints = keypoint_scale(
              keypoints, image_height, image_width
          )
          result.append(scaled_keypoints)
      return tuple(result)
  
file_path: DALI/docs/examples/use_cases/tensorflow/efficientdet/pipeline/tf/preprocessor.py
imports: import tensorflow.compat.v1
  from pipeline.anchors_utils import box_list
label_desc: Use image node_id 11 for calling a global function with example usage: scale_boxes_to_pixel_coordinates(image, boxes, keypoints) and returns: tuple