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51 lines
2.3 KiB
Python
Executable File
51 lines
2.3 KiB
Python
Executable File
#!/usr/bin/python
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# The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt
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#
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#
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# This simple example shows how to call dlib's optimal linear assignment problem solver.
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# It is an implementation of the famous Hungarian algorithm and is quite fast, operating in
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# O(N^3) time.
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#
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# COMPILING THE DLIB PYTHON INTERFACE
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# Dlib comes with a compiled python interface for python 2.7 on MS Windows. If
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# you are using another python version or operating system then you need to
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# compile the dlib python interface before you can use this file. To do this,
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# run compile_dlib_python_module.bat. This should work on any operating system
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# so long as you have CMake and boost-python installed. On Ubuntu, this can be
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# done easily by running the command: sudo apt-get install libboost-python-dev cmake
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import dlib
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# Let's imagine you need to assign N people to N jobs. Additionally, each person will make
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# your company a certain amount of money at each job, but each person has different skills
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# so they are better at some jobs and worse at others. You would like to find the best way
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# to assign people to these jobs. In particular, you would like to maximize the amount of
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# money the group makes as a whole. This is an example of an assignment problem and is
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# what is solved by the dlib.max_cost_assignment() routine.
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# So in this example, let's imagine we have 3 people and 3 jobs. We represent the amount of
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# money each person will produce at each job with a cost matrix. Each row corresponds to a
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# person and each column corresponds to a job. So for example, below we are saying that
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# person 0 will make $1 at job 0, $2 at job 1, and $6 at job 2.
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cost = dlib.matrix([[1, 2, 6],
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[5, 3, 6],
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[4, 5, 0]])
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# To find out the best assignment of people to jobs we just need to call this function.
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assignment = dlib.max_cost_assignment(cost)
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# This prints optimal assignments: [2, 0, 1]
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# which indicates that we should assign the person from the first row of the cost matrix to
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# job 2, the middle row person to job 0, and the bottom row person to job 1.
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print "optimal assignments: ", assignment
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# This prints optimal cost: 16.0
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# which is correct since our optimal assignment is 6+5+5.
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print "optimal cost: ", dlib.assignment_cost(cost, assignment)
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