diff --git a/python_examples/correlation_tracker.py b/python_examples/correlation_tracker.py
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+#!/usr/bin/python
+# The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt
+#
+# This example shows how to use the correlation_tracker from the dlib Python
+# library.  This object lets you track the position of an object as it moves
+# from frame to frame in a video sequence.  To use it, you give the
+# correlation_tracker the bounding box of the object you want to track in the
+# current video frame.  Then it will identify the location of the object in
+# subsequent frames.
+#
+# In this particular example, we are going to run on the
+# video sequence that comes with dlib, which can be found in the
+# examples/video_frames folder.  This video shows a juice box sitting on a table
+# and someone is waving the camera around.  The task is to track the position of
+# the juice box as the camera moves around.
+#
+# COMPILING THE DLIB PYTHON INTERFACE
+#   Dlib comes with a compiled python interface for python 2.7 on MS Windows. If
+#   you are using another python version or operating system then you need to
+#   compile the dlib python interface before you can use this file.  To do this,
+#   run compile_dlib_python_module.bat.  This should work on any operating
+#   system so long as you have CMake and boost-python installed.
+#   On Ubuntu, this can be done easily by running the command:
+#       sudo apt-get install libboost-python-dev cmake
+#
+#   Also note that this example requires scikit-image which can be installed
+#   via the command:
+#       pip install -U scikit-image
+#   Or downloaded from http://scikit-image.org/download.html. 
+
+import os
+import glob
+
+import dlib
+from skimage import io
+
+# Path to the video frames
+video_folder = os.path.join("..", "examples", "video_frames")
+
+# Create the correlation tracker - the object needs to be initialized
+# before it can be used
+tracker = dlib.correlation_tracker()
+
+win = dlib.image_window()
+# We will track the frames as we load them off of disk
+for k, f in enumerate(sorted(glob.glob(os.path.join(video_folder, "*.jpg")))):
+    print("Processing Frame {}".format(k))
+    img = io.imread(f)
+
+    # We need to initialize the tracker on the first frame
+    if k == 0:
+        # Start a track on the juice box. If you look at the first frame you
+        # will see that the juice box is contained within the bounding
+        # box (74, 67, 112, 153).
+        tracker.start_track(img, dlib.rectangle(74, 67, 112, 153))
+    else:
+        # Else we just attempt to track from the previous frame
+        tracker.update(img)
+
+    win.clear_overlay()
+    win.set_image(img)
+    win.add_overlay(tracker.get_position())
+    dlib.hit_enter_to_continue()