forked from vlfeat/vlfeat
-
Notifications
You must be signed in to change notification settings - Fork 0
An open library of computer vision algorithms
License
jun930/vlfeat
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
VisionLab Features Library Andrea Vedaldi and Brian Fulkerson ABOUT The VLFeat open source library implements popular computer vision algorithms including SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, and quick shift. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. It supports Windows, Mac OS X, and Linux. VLFeat is distributed under the BSD license (see the COPYING file). Most of the documentation is available online at http://www.vlfeat.org/index.html or compiled in HTML format in `doc/index.html'. INSTALLING If you downloaded VLFeat binary package, installation is trivial. The binaries are found in the `bin/ARCH' directory, where ARCH depends on the architecture of your machine. VLFeat supports the following ones out of the box: ARCH MEXEXT DESCRIPTION ----------------------------------------------- maci mexmaci Mac OS X Intel maci64 mexmaci64 Mac OS X Intel (64 bit) glnx86 mexglx GNU Linux glnxa64 mexa64 GNU Linux (64 bit) win32 mexw32 Windows win64 mexw64 Windows (64 bit) The `bin' directory contains also a copy of the VLFeat DLL (and of the appropriate C runtime DLL in the case of Windows). The VLFeat MATLAB toolbox can be found in the `toolbox' directory. To use it with MATLAB, run the VL_SETUP command as > cd VLFEATROOT/toolbox ; vl_setup or > run VLFEATROOT/toolbox/vl_setup You can make this permanent by adding the line to MATLAB startup.m file. An HTML copy of the documentation can be found in `doc/index.html'. The same documentation is available online at http://www.vlfeat.org/index.html. COMPILING If you downloaded VLFeat source package or just want to compile your own version, all you need is a standard compiler setup. UNIX. In Mac OS X and Linux you will need GNU GCC and GNU Make. In fact, most C-90 compilers will do, although a few C-99 features are used. To compile MATLAB support, MATLAB should also be installed and the MATLAB MEX command should be available from the command line. In general, issuing > make should be enough to compile VLFeat. Type > make help or refer to http://www.vlfeat.org for further instructions. WINDOWS. In Windows you will need Visual Studio 2008 or 2010. VLFeat includes a Microsoft NMAKE Makefile (Makefile.mak). Open the Visual C command prompty (make sure you run the 64 bit version if your host is 64 bit), into the VLFeat directory and issue. > nmake /f Makefile.mak ARCH=win32 or > nmake /f Makefile.mak ARCH=win64 depending on your architecture. CREATING THE DOCUMENTATION Creating the documentation requires a UNIX platform (either Linux or Mac OS X) and the following tools - fig2dev (part of transfig) - a modern LaTeX with + pdflatex + dvips + htlatex (possibily part of TeX4ht) + dvipng (possibily a separated package) - doxygen (a recent version) FIGURES. Figures are preprocessed by typing > make -C doc/figures However, you need to run MATLAB programs to generate most of the figures to start with. To this end, load MATLAB and (provided that everything is compiled and installed correctly) type > vl_demo TUTORIALS. To create the figures for the tutorials, issue > make doc-deep > make doc SOURCE CODE DOCUMENTATION. To compile the source code documentation issue > make doc-api The start of the documentation is the file `doc/index.html'. APPENDIX CODE COMPATIBILITY. In addition to the C-90 standard, the C compiler is supposed to support the following common features: - long int (64 bit integer) support - variadic macro support The SSE accelerated code requires the compiler to support Intel intrisic. GCC and Visual C satisfy all the requirements. CHANGES 0.9.14 Added SLIC superpixels and VL_ALPHANUM(). Improved Windows binary package and added support for Visual Studio 2010. Improved the documentation layout and added a proper bibliography. Bugfixes and other minor improvements. Moved from the GPL to the less restrictive BSD license. 0.9.13 Fixes Windows binary package. 0.9.12 Fixes vl_compile and the architecture string on Linux 32 bit. 0.9.11 Fixes a compatibility problem on older Mac OS X versions. A few bugfixes are included too. 0.9.10 Improves the homogeneous kernel map. Plenty of small tweaks and improvements. Make maci64 the default architecture on the Mac. 0.9.9 Added: sift matching example. Extended Caltech-101 classification example to use kd-trees. 0.9.8 Added: image distance transform, PEGASOS, floating point K-means, homogeneous kernel maps, a Caltech-101 classification example. Improved documentation. 0.9.7 Changed the Mac OS X binary distribution to require a less recent version of Mac OS X (10.5). 0.9.6 Changed the GNU/Linux binary distribution to require a less recent version of the C library. 0.9.5 Added kd-tree and new SSE-accelerated vector/histogram comparison code. Improved dense SIFT (dsift) implementation. Added Snow Leopard and MATLAB R2009b support. 0.9.4 Added quick shift. Renamed dhog to dsift and improved implementation and documentation. Improved tutorials. Added 64 bit Windows binaries. Many other small changes. 0.9.3 Namespace change (everything begins with a vl_ prefix now). Many other changes to provide compilation support on Windows with MATLAB 7. beta-3 Completions to the ikmeans code. beta-2 Many completions. beta-1 Initial public release.
About
An open library of computer vision algorithms
Resources
License
Stars
Watchers
Forks
Packages 0
No packages published
Languages
- C 71.5%
- MATLAB 23.0%
- Python 5.2%
- Other 0.3%