===============================================================================
            Dynamic and Iterative Spanning Forest Framework (DISF)

        Felipe C. Belém, Silvio J. F. Guimarães and Alexandre X. Falcão
===============================================================================

This is an implementation of the Dynamic and Iterative Spanning Forest (DISF)
framework. Its strategy consists on oversampling the input image and, through
the iterations, generates superpixels and removes those considered as irrelevant,
by a certain criterion, until the desired quantity of superpixels is achieved.
See http://viplab.icei.pucminas.br/projects/disf/ for more information 
about this work.

1) Papers & Citation:
    This work was published at [1] and [2]... 
        [1] - https://arxiv.org/abs/2007.04257
        [2] - https://ieeexplore.ieee.org/document/9165122/
    ...and if you're interested in using our code, we appreciate if you cite this work in your project. 
        F. Belem, S. Guimaraes and A. X. Falcao, "Superpixel Segmentation using Dynamic and Iterative Spanning Forest," in IEEE Signal Processing Letters, doi: 10.1109/LSP.2020.3015433.

2) Languages Supported:
    C/C++ (Implementation), Python3 (Wrapper), Octave (Wrapper) and MATLAB (Wrapper)

3) Compiling & Cleaning:
    In order to compile the necessary files for executing in C, Python3, Octave or MATLAB environment, one can execute their respective rules...
        make c
        make python3
        make octave
        make matlab
    ... or one of the following for compiling them all:
        make    
        make all
    For removing all generated files from source, simply run:
        make clean

4) Running:
    In this folder, there are three demo files, one for each language supported (i.e., C, 
    Python3 and MATLAB/Octave). After compiling and assuring the generation of the 
    necessary files, one can execute each demo within its own environment. As an example,
    for a terminal located at this folder, one can run the following commands:
        C: ./bin/DISF_demo
        Python3: python3 DISF_demo.py
        Octave: octave 
                DISF_demo
        MATLAB: matlab
                DISF_demo

5) Hardware & Requirements:
    This code was implemented and evaluated in computers with the following 
    specifications:
        Acer Chromebook C720P
        Order: Little-Endian
        OS: GalliumOS v4.16.18 x86_64
        CPU: 4x Dual-core Intel(R) Core(TM) i3-4005U CPU @ 1.70GHz
        Memory: 4GB RAM ; 32GB SSD

        Gigabyte Technology H170M-D3H
        Order: Little-Endian
        OS: Ubuntu v4.15.0 x86_64
        CPU: 8x Quad-core Intel(R) Core(TM) i7-7700 CPU @ 3.60GHz
        Memory: 64GB RAM ; 1TB SSD

    Moreover, it was compiled and executed using the following programs:
        GNU Make: v4.1
        GNU GCC: v5.4.0 v7.5.0
        Python: v3.5.2 v3.6.9 
        Numpy: v1.12.1 v1.19.1
        Octave: v4.2.2
        MATLAB: R2019a v9.6.0.1150989 Update 4

    Therefore, it is >>>NOT<<< guaranteed that this code will compile/execute properly in any
    other operational system (e.g., Windows and MacOS) or programs (e.g., MinGW and Clang).

6) Optional Libraries:
    In each demo, it was considered a library for manipulating images, which are not 
    mandatory. Thus, one can alter such to its preferred one, but maintaining the conversion
    to the mandatory object types (e.g., Int32 Mex Array, Int32 Numpy Array and Graph*).
    The optional libraries used at each demo are presented below:
        Octave Image Package: v2.12.0
        Matplotlib: v2.0.2 v3.2.1
        Python Imaging Library (PIL): v5.1.0 v5.3.0
        STB Image: v2.23

7) License:
    This code is licensed under Open Software License ("OSL") v.3.0. Please, see LICENSE for
    more details.

8) Acknowledgments
    This work was developed during Felipe's M.Sc. and Ph.D. studies at the University of Campinas (UNICAMP), in São Paulo, Brazil, with the cooperation of the Pontifical Catholic University of Minas Gerais (PUC-MG), in Minas Gerais, Brazil. Moreover, it was financially supported by CNPq, FAPESP, FAPEMIG and CAPES --- all brazilian research funding agencies.

9) Contact:
    Please, feel free to contact the authors for any unexpected behavior you might face (e.g., bugs):
        Felipe C. Belém: [email protected]
        Silvio J. F. Guimarães: [email protected]
        Alexandre X. Falcão: [email protected]