title: Best practice on containerize tensorflow iPython notebook application
body: <p>After playing ther <a href="https://colab.research.google.com/github/tensorflow/models/blob/master/research/object_detection/colab_tutorials/object_detection_tutorial.ipynb" rel="nofollow noreferrer">Tensorflow Object Detection API Demo</a> in Google Colab, I would like to containerize this iPython notebook. As the iPython notebook include all the envoirnment initialization, package installation, model loading. I would like to optimize the application processing time so I would like to pre-install the package and model loading stage on the container image preparation stage. I have successfully pull out the package installation and model downloading stage into the docker image.</p>
  <p>I would like to know if the <strong>Loading label map</strong> stage could be pulled into Dockerfile.</p>