深蓝基于图像的三维重建代码C++源码+文档说明(高分项目)

/************************************************************************************** GCO_MATLAB - a Matlab wrapper for Olga Veksler's C++ graph-cut optimization library GCO_MATLAB Author(s): Andrew Delong <firstname.lastname@gmail.com> Anton Osokin <lastname.firstname@gmail.com> We're especially grateful to Lena Gorelick for helpful suggestions and for tracking down so many bugs! GCoptimization Author(s): Olga Veksler <firstname@csd.uwo.ca> Description: This download provides a Matlab wrapper for the latest version of 'GCoptimization', Olga Veksler's multi-label optimization library written in C++. Note: A wrapper for an earlier version GCoptimization was authored by Shai Bagon and is available at http://www.wisdom.weizmann.ac.il/~bagon/matlab.html Revision History: Oct 14, 2014; - Added GCO_ENERGYTERM and GCO_ENERGYTERMTYPE macros to make float/double terms easier. Please note that float/double energy terms can cause expansion/swap steps to report a very small increase in energy due to accumulated rounding error inside the maxflow library. If Inf or NaN values appear in the energy terms, behaviour is undefined. May 18, 2014; - Support Matlab R2014a by removing use of mxCreateReference Jan 15, 2014; - Compiles with gcc 4.6+ even without -fpermissive Apr 12, 2011; - Fixed bug when sparse data costs had a dense bucket (thanks Joseph Tighe!) Nov 25, 2010; - Detect MACI64 correctly (thanks Francis Lauzon) Aug 31, 2010; - Compiles with gcc 4.4.1 on opensuse 11.2 (thanks Wei Liu) Aug 7, 2010; - Fixed bug when data costs are computed in a callback (thanks Evan Herbst!) - Fixed bug where setAllNeighbours didn't apply neighbourhood (Evan Herbst again) Jul 22, 2010; - Compiles with gcc 4.4.1 (thanks Julius Ziegler for the patch!) Jul 8, 2010; - Fixed crash in greedy code path when all labels get added (thanks Yangyan Li!) Apr 25, 2010; - Faster code path for sparse data costs; fixed related bug in higher-order labels Apr 21, 2010; - Added basic "verbose" mode (print cycle, energy, timings etc) - Expansion cycles now focus on labels for which the energy decreased (faster) Apr 19, 2010; - Added sparse datacost support - Allow GCO_SetLabelOrder to specify exact label order Apr 13, 2010; - Potts model is now the default if SetNeighbors is called without SetSmoothCost - Fixed bug in higher-order label costs - Expansion is now interruptable from MATLAB; temporary memory is freed - Added GCO_ListHandles and allow GCO_Delete to accept multiple handles - Better error message if a bad handle is passed to GCO_* Nov 17, 2009; - Fixed integer overflow in label-cost construction - Fixed bug where greedy algorithm would sometimes skip a label Nov 6, 2009; - Fixed bug in re-setting label costs after Expansion - Fixed bug in GCO_LoadLib Oct 27, 2009; - Removed support for arbitrary smoothcost (too slow, hard to maintain) - Added support for re-setting data, smooth, and label costs after Expansion - Added support for label subset costs - Changed build process to directly use MEX command - Added integer overflow checks into GCoptimization - GCoptimization now uses maxflow-3.0 library Sep 12, 2009; - Added support for arbitrary smoothcost from Matlab via a function_handle - Added GCO_UnitTest - Build script now handles spaces in paths properly Aug 23, 2009; - First version for internal testing ***************************************************************************************/ 0. System Requirements - Matlab 7.4.0 (R2007a) or above for 32-bit. Matlab 7.6.0 (R2008) or above for 64-bit. - Mex must be pre-configured to use a C++ compiler. (Run "mex -setup" if you have not already.) The C++ code requires at least Visual C++ 2005 (VC8). ---------------------------------------------------------------------------------------- 1. Installation - The package should contain the following files: GCO_MATLAB files: gco\matlab\GCO_*.m ; the Matlab commands that you can run gco\matlab\gco_matlab.cpp ; the library that links Matlab to GCoptimization GCoptimization files: gco\*.{h,cpp} ; the GCoptimization C++ library - Start Matlab, and make gco\matlab your working directory or add it to your path. - To test your installation of GCO_MATLAB, run the GCO_UnitTest command. You should hopefully see output like below. >> GCO_UnitTest BuildLib PASSED LoadLib PASSED Create/Delete PASSED ... >> - ---------------------------------------------------------------------------------------- 2. Getting Started -- A basic example, and important usage notes Once GCO_UnitTest passes, you should be able run the example sequence of commands below. >> h = GCO_Create(4,3); % Create new object with NumSites=4, NumLabels=3 >> GCO_SetDataCost(h,[ 0 9 2 0; % Sites 1,4 prefer label 1 3 0 3 3; % Site 2 prefers label 2 (strongly) 5 9 0 5; % Site 3 prefers label 3 ]); >> GCO_SetSmoothCost(h,[ 0 1 2; % 1 0 1; % Linear (Total Variation) pairwise cost 2 1 0; % ]); >> GCO_SetNeighbors(h,[ 0 1 0 0; % Sites 1 and 2 connected with weight 1 0 0 1 0; % Sites 2 and 3 connected with weight 1 0 0 0 2; % Sites 3 and 4 connected with weight 2 0 0 0 0; ]); >> GCO_Expansion(h); % Compute optimal labeling via alpha-expansion >> GCO_GetLabeling(h) ans = 1 % Optimal labeling is (1,2,1,1) 2 1 1 >> [E D S] = GCO_ComputeEnergy(h) % Energy = Data Energy + Smooth Energy E = 4 D = 2 S = 2 >> GCO_Delete(h); % Delete the GCoptimization object when finished *** Before using the MATLAB wrapper, please note the following: *** - Sites and labels are identified with 1-based indices (i.e. 1..N and *not* 0..N-1) - By default, all numeric costs should be int32, not single or double! To use single/double energy terms with the library, please type "help GCO_BuildLib" at the MATLAB command prompt. You'll receive a conversion warning if you pass in a large matrix of the wrong type. The only function that accepts double is GCO_SetNeighbors, because it needs a sparse matrix and sparse matrices only support double in MATLAB. ** The weights themselves must still be integer valued!! ** (1.0, 17.0, 42.0 etc) ---------------------------------------------------------------------------------------- 3. GCO_MATLAB functions Run 'help' in MATLAB to see the documentation of each function, e.g. >> help GCO_SetSmoothCost Most of the GCO_MATLAB functions are one-to-one with the C++ methods in the GCoptimization library. For more detailed documentation, please refer to the C++ library itself. Relevant files are: GCO_README.TXT example.cpp GCoptimization.h