mirror of https://github.com/davisking/dlib.git
51 lines
2.3 KiB
Python
Executable File
51 lines
2.3 KiB
Python
Executable File
#!/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
|
|
|
|
# Let's 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, let's 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)
|
|
|
|
|