#!/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/INSTALLING THE DLIB PYTHON INTERFACE | |
# You can install dlib using the command: | |
# pip install dlib | |
# | |
# Alternatively, if you want to compile dlib yourself then go into the dlib | |
# root folder and run: | |
# python setup.py install | |
# | |
# Compiling dlib should work on any operating system so long as you have | |
# CMake installed. On Ubuntu, this can be done easily by running the | |
# command: | |
# sudo apt-get install 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: {}".format(assignment)) | |
# This prints optimal cost: 16.0 | |
# which is correct since our optimal assignment is 6+5+5. | |
print("Optimal cost: {}".format(dlib.assignment_cost(cost, assignment))) | |