function buildNewHead(inputShape) {
  const newHead = tf.sequential();
  newHead.add(tf.layers.flatten({inputShape}));
  newHead.add(tf.layers.dense({units: 200, activation: 'relu'}));
  // Five output units:
  //   - The first is a shape indictor: predicts whether the target
  //     shape is a triangle or a rectangle.
  //   - The remaining four units are for bounding-box prediction:
  //     [left, right, top, bottom] in the unit of pixels.
  newHead.add(tf.layers.dense({units: 5}));
  return newHead;
}
Build a new head (i.e., output sub-model) that will be connected to
the top of the truncated base for object detection.

@param {tf.Shape} inputShape Input shape of the new model.
@returns {tf.Model} The new head model.