Added a max_cost_assignment python example

python_examples/max_cost_assignment.py

+#!/usr/bin/python
+# The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt
+#
+# 
+# This simple example shows how to call dlib's optimal linear assignment problem solver.
+# It is an implementation of the famous Hungarian algorithm and is quite fast, operating in
+# O(N^3) time.
+#
+# 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
+
+
+import dlib
+
+# Lets imagine you need to assign N people to N jobs.  Additionally, each person will make
+# your company a certain amount of money at each job, but each person has different skills
+# so they are better at some jobs and worse at others.  You would like to find the best way
+# to assign people to these jobs.  In particular, you would like to maximize the amount of
+# money the group makes as a whole.  This is an example of an assignment problem and is
+# what is solved by the dlib.max_cost_assignment() routine.
+
+# So in this example, lets imagine we have 3 people and 3 jobs.  We represent the amount of
+# money each person will produce at each job with a cost matrix.  Each row corresponds to a
+# person and each column corresponds to a job.  So for example, below we are saying that
+# person 0 will make $1 at job 0, $2 at job 1, and $6 at job 2.  
+cost = dlib.matrix([[1, 2, 6],
+                    [5, 3, 6],
+                    [4, 5, 0]])
+
+
+# To find out the best assignment of people to jobs we just need to call this function.
+assignment = dlib.max_cost_assignment(cost)
+
+
+# This prints optimal assignments:  [2, 0, 1]
+# which indicates that we should assign the person from the first row of the cost matrix to
+# job 2, the middle row person to job 0, and the bottom row person to job 1.
+print "optimal assignments: ", assignment
+
+
+# This prints optimal cost:  16.0
+# which is correct since our optimal assignment is 6+5+5.
+print "optimal cost: ", dlib.assignment_cost(cost, assignment)
+
+