to the APT project at the end of the training. The files <code>traindata.json</code> and <code>deepnet-*</code> are constantly polled by APT front-end in order to update the user about training's status.
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During tracking, <code>APT_interface.py</code> calls <code>get_pred_fn</code> after initilializing the <code>Pose_mynet</code> object. This function should return a handle to <i>prediction</i> function which when given a batch of input images as numpy array as input   returns the landmark predictions as