title: Tensorflow Object Detection API with GPU on Windows and real-time detection
body: <p>I am testing the new <strong>Tensorflow Object Detection API</strong> in Python, and I succeeded in installing it on Windows using docker. However, my trained model (Faster RCNN resnet101 COCO) <strong>takes up to 15 seconds to make a prediction</strong> (with very good accuracy though), probably because I only use Tensorflow CPU.</p>
  
  <p>My three questions are:</p>
  
  <ul>
  <li>Considering the latency, where is the problem? I heard Faster RCNN was a good model for low latency visual detection, is it because of the CPU-only execution?</li>
  <li>With such latency, is it possible to make efficient realtime video processing by using tensorflow GPU, or should I use a more popular model like YOLO?</li>
  <li>The popular mean to use tensorflow GPU in docker is nvidia-docker but is not supported on windows. Should I continue to look for a docker (or conda) solution for local prediction, or should I deploy my model directly to a virtual instance with GPU (I am comfortable with Google Cloud Platform)?</li>
  </ul>
  
  <p>Any advice and/or good practice concerning real-time video processing with Tensorflow is very welcome!</p>