forked from clementfarabet/xLearn
A Lua-based framework for vision.
Johnson13/xLearn
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
================================================================================ What's in this package ?? Torch 5 Torch5 provides a Matlab-like environment for state-of-the-art machine learning algorithms. It is easy to use and provides a very efficient implementation, thanks to an easy and fast scripting language (Lua) and a underlying C implementation. The Torch 5 library is re-distributed here for simplicity of installation. The original package can be found here: http://torch5.sourceforge.net The distribution has been slightly modified, in particular, the original Lua kernel has been patched for multi-threaded applications. Torch is licensed under a BSD license: http://torch5.sourceforge.net/manual/License.html xLearn xLearn is an extension library for torch. It provides dozens of tools/modules for vision, image processing, and machine learning for vision luaFlow luaFlow is a unified flow-graph description environment for [beta] vision / image-processing types of applications. One of its primary objectives is to abstract computing platforms, by providing a unified, high-level description flow. xFlow a serializing language for luaFlow, that allows algorithms to [beta] be imported/exported from/to other software frameworks neuFlow neuFlow is the compiler toolkit for the neuFlow processor, developped at New York University / Yale University. The neuFlow processor is dataflow computer optimized for vision and bio-inspired models of vision. The neuFlow compiler currently converts xLearn/torch algorithms to native neuFlow's bytecode. Soon to appear is a luaFlow>neuFlow compiler, which would simplify retargetting. It is quite important to have access to a neuFlow device to be able to experiment with it: for more info/support, to get a neuFlow-enabled board, please contact clement.farabet@gmail.com thread the Lua core is patched with LuaThread to allow multithreaded apps LuaJIT the entire framework can be built against LuaJIT for improved performance opencv a wrapper for OpenCV, for now just a couple of functions, super easy to extend debugger the open-source debugger framework for Lua (activated by requiring 'debug') camiface a wrapper for libcamiface, to interface webcams on MacOS video4linux a wrapper for libv4l2, to interface webcams in Linux mstsegm a wrapper around P. Felzenszwalb’s image segmentation lib powerwatersegm a wrapper around C. Couprie’s Powerwatershed lib stereo a wrapper around P. Felzenszwalb’s BP-based stereo code opticalFlow a wrapper around C. Liu’s great optical-flow estimator kinect a wrapper around Microsoft's kinect device pink a wrapper around M. Couprie's Morphology library ================================================================================ INSTALL (1-LINUX) install dependencies (compilation tools, cmake, QT4): $ sudo apt-get install binutils gcc g++ cmake libqt4-core libqt4-dev libqt4-gui libreadline5-dev libpcap-dev optionally, install OpenCV 2.x, to get access to extra packages: http://sourceforge.net/projects/opencvlibrary/files/opencv-unix/2.1/ (1-MACOS) install dependencies (readline, cmake, QT4) $ sudo port install readline-5 cmake qt4-mac-devel you might want to use a prebuilt version of QT4, to avoid the 2 hour build time... (I still don't understand why MacPort relies on sources rather than binaries...) I'm keeping a working version here (installs in 5mins): http://data.clement.farabet.net/qt/qt-mac-cocoa-opensource-4.5.3.dmg optionally, install OpenCV 2.x, to get access to extra packages on Snow Leopard, that works: sudo port install opencv +sl_64bit (2-COMMON) once the dependencies are installed, just run: $ make $ [sudo] make install for the default install or just $ make help for more info about the options/submodules example of a local install: $ make install INSTALL_PREFIX=~/local ================================================================================ DOC The documentation is built and installed, and then available at: /usr/local/share/torch/html/index.html or INSTALL_PREFIX/share/torch/html/index.html All details about installation are available there.
About
A Lua-based framework for vision.
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published
Languages
- C 82.4%
- Lua 9.9%
- C++ 5.9%
- HTML 0.7%
- CMake 0.7%
- Objective-C 0.2%
- Other 0.2%