MumfordShahCuda

This repository contains an implementation based on the paper:
Real-Time Minimization of the Piecewise Smooth Mumford-Shah Functional, E. Strekalovskiy, D. Cremers, European Conference on Computer Vision (ECCV), 2014. (pdf) (video)

Generalization

The proposed variational model in the above paper is:

min_u {sum_{x in Omega} |u(x)-f(x)|^2 + min(alpha*|nabla u|^2,lambda)}

The proposed model has been adapted to an additional scalar operator a(x) to solve a variational model of the form

min_u {sum_{x in Omega} |a(x)u(x)-f(x)|^2 + min(alpha*|nabla u|^2,lambda)}

Features

• GPU implementation using CUDA, and a CPU implementation. Either implementation can be chosen at compile time using CMake.
• Wrapper for quick prototyping.

Requirements

CUDA:

To use the GPU implementation, CUDA must be installed and nvcc must be in the current PATH. The code is generated for NVIDIA GPUs of compute capability.

Note: You can still compile and use the CPU version, even if CUDA is not available. Just set CUDAF=FALSE in the CMakeLists.txt file

OpenCV

OpenCV is only used for the executable (NOT Matlab/Mex) usages of the algorithm (./main). So you should have it installed in order to run the executable.

Note: If OpenCV is not available and you do not want to run the executable but use only the Matlab version, then just set EXEF=FALSE in the CMakeLists.txt file

MATLAB

If you want to use the provided MATLAB wrapper, MATLAB must be installed, and MEXF=TRUE in the CMakeLists.txt file as to be set. Additionally, you have to set an environment variable MATLAB_ROOT pointing to the Matlab installation directory. In Ubuntu for Matlab R2018a type in Terminal or add the following line to your .bashrc file before running CMake:

export MATLAB_ROOT='/usr/local/MATLAB/matlab-R2018a'

Notes

This code has been tested with the following setup

• Ubuntu 16.04 with gcc 5.4
• [optional] CUDA 8.0 and CUDA 9.1(CUDAF=FALSE must be set in CMakeLists.txt to build without CUDA support)
• [optional] Matlab R2017b and R2018a (MEXF=FALSE must be set in CMakeLists.txt to build without Matlab/Mex support.)
• [optional] OpenCV 2.4.9.1 (EXEF=FALSE must be set in CMakeLists.txt to build without executable and thus no OpenCV is needed.)

Installation

Install: In Terminal type

    git clone https://github.com/BjoernHaefner/MumfordShahCuda.git

    cd MumfordShahCuda

    mkdir build && cd build
	
	cmake ..
	
	make

Usage

Run the code from command line (located in build/bin)

    ./mumfordShah -i <img.png> [-s <scalar_op.png>] [-m <mask.png>] [-o <output.png>]
	              [-p path/to/files/] [-l <float>] [-a <float>] [-iter <int>]
				  [-tol <float>] [-verbose <bool>] [-showall <bool>] [-show <bool>]
				  [-gamma <float>] [-sigma <float>] [-tau <float>]

All Parameters

-i <string>
	(path to) image file}
	
-s <string> (optional)
	(path to) scalar_operator file.
	Default: identity

-m <string> (optional)
	(path to) mask file.
	Default: ones matrix
	
-o <string> (optional)
	output filename (will be stored in 'data').
	Default: no output is stored

-p <string> (optional)
	absolute path to data folder.
	Default: path/to/mumfordShah/data/
	
-l <float> (optional)
	trade-off parameter lambda.
	Default 0.1f
	
-a <float> (optional)
	parameter controlling the smoothness. alpha=infinity means piecewise constant result (can be triggered with alpha=-1).
	Default 10

-iter <int> (optional)
	number of iterations.
	Default 5000

-tol <float> (optional)
	Tolerance of stopping criterion.
	Default 1e-5f

-verbose <bool> (optional)
	Verbose output during algorithm.
	Default 1

-showall <bool> (optional)
	Show results on the fly after each iteration.
	Default 0

-show <bool> (optional)
	Show final result.
	Default 1

-gamma <float> (optional)
	Default 2

-sigma <float> (optional)
	Initial step size of dual variable
	Default 0.5f

-tau <float> (optional)
	Initial step size of primal variable
	Default 0.25f

Examples

We provide examples for running the executable as well as how to run the code in matlab. Have a look in MumfordShahCuda/examples/

• For the executable run in Terminal

    bash MumfordShahCuda/examples/example.sh
  

• For the Matlab code run in Matlab

    MumfordShahCuda/examples/example.m
  

• If you want to run the algorithm from command line, you can for example run

    ./mumfordShah -i intensity.png -m mask.png -s shading.png -o result.png -a -1
  

Tips and troubleshooting

• If Matlab throws an error like

  /MATLAB/R2016b/bin/glnxa64/../../sys/os/glnxa64/libstdc++.so.6: version `GLIBCXX_3.4.21' not found (required by /mumfordshah/build/lib/mumfordShahMEX.mexa64)```
  
  then start Matlab from terminal and preload the `/usr/lib/x86_64-linux-gnu/libstdc++.so.6` library:
  
  ```LD_PRELOAD="/usr/lib/x86_64-linux-gnu/libstdc++.so.6" matlab```
  
  

• If Matlab throws an error like

  /usr/wiss/haefner/Documents/coding/cpp/mumfordshah/build/lib/mumfordShahMEX.mexa64: undefined symbol: _ZN2cv8fastFreeEPv```
  
  then build the mex file with the `EXEF=FALSE` option.
  
  

• If Matlab keeps crashing: Check if you use clear all somewhere in your Matlab code. Exchange it with clear.

Citation

If you make use of the library in any form in a scientific publication, please refer to https://github.com/BjoernHaefner/MumfordShahCuda and cite following papers

@inproceedings{strekalovskiy2014realtime,
 author = {E. Strekalovskiy and D. Cremers},
 title = {{Real-Time Minimization of the Piecewise Smooth Mumford-Shah Functional}},
 booktitle = {European Conference on Computer Vision (ECCV)},
 year = {2014},
 pages = {127-141},
 keywords = {convex-relaxation},
}

@inproceedings{haefner2018fight,
 title = {{Fight ill-posedness with ill-posedness: Single-shot variational depth super-resolution from shading}},
 author = {B. Haefner and Y. Quéau and T. Möllenhoff and D. Cremers},
 booktitle = {I{EEE}/{CVF} {C}onference on {C}omputer {V}ision and {P}attern {R}ecognition (CVPR)},
 year = {2018},
 keywords = {rgb-d,reconstruction,3d-reconstruction,photometry,variational,super-resolution,photometricdepthsr},
}