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release/4.3a0
dellaert 2014-12-03 19:57:16 +01:00
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README - Georgia Tech Smoothing and Mapping library
===================================================
What is GTSAM?
--------------
GTSAM is a library of C++ classes that implement smoothing and
mapping (SAM) in robotics and vision, using factor graphs and Bayes
networks as the underlying computing paradigm rather than sparse
matrices.
On top of the C++ library, GTSAM includes a MATLAB interface (enable
GTSAM_INSTALL_MATLAB_TOOLBOX in CMake to build it). A Python interface
is under development.
Quickstart
----------
In the root library folder execute:
```
#!bash
$ mkdir build
$ cd build
$ cmake ..
$ make check (optional, runs unit tests)
$ make install
```
Prerequisites:
- [Boost](http://www.boost.org/users/download/) >= 1.43 (Ubuntu: `sudo apt-get install libboost-all-dev`)
- [CMake](http://www.cmake.org/cmake/resources/software.html) >= 2.6 (Ubuntu: `sudo apt-get install cmake`)
Optional prerequisites - used automatically if findable by CMake:
- [Intel Threaded Building Blocks (TBB)](http://www.threadingbuildingblocks.org/) (Ubuntu: `sudo apt-get install libtbb-dev`)
- [Intel Math Kernel Library (MKL)](http://software.intel.com/en-us/intel-mkl)
Additional Information
----------------------
See the [`INSTALL`](https://bitbucket.org/gtborg/gtsam/src/develop/INSTALL) file for more detailed installation instructions.
GTSAM is open source under the BSD license, see the [`LICENSE`](https://bitbucket.org/gtborg/gtsam/src/develop/LICENSE) and [`LICENSE.BSD`](https://bitbucket.org/gtborg/gtsam/src/develop/LICENSE.BSD) files.
Please see the [`examples/`](https://bitbucket.org/gtborg/gtsam/src/develop/examples) directory and the [`USAGE`](https://bitbucket.org/gtborg/gtsam/src/develop/USAGE) file for examples on how to use GTSAM.
README - Georgia Tech Smoothing and Mapping library
===================================================
What is GTSAM?
--------------
GTSAM is a library of C++ classes that implement smoothing and
mapping (SAM) in robotics and vision, using factor graphs and Bayes
networks as the underlying computing paradigm rather than sparse
matrices.
On top of the C++ library, GTSAM includes a MATLAB interface (enable
GTSAM_INSTALL_MATLAB_TOOLBOX in CMake to build it). A Python interface
is under development.
Quickstart
----------
In the root library folder execute:
```
#!bash
$ mkdir build
$ cd build
$ cmake ..
$ make check (optional, runs unit tests)
$ make install
```
Prerequisites:
- [Boost](http://www.boost.org/users/download/) >= 1.43 (Ubuntu: `sudo apt-get install libboost-all-dev`)
- [CMake](http://www.cmake.org/cmake/resources/software.html) >= 2.6 (Ubuntu: `sudo apt-get install cmake`)
Optional prerequisites - used automatically if findable by CMake:
- [Intel Threaded Building Blocks (TBB)](http://www.threadingbuildingblocks.org/) (Ubuntu: `sudo apt-get install libtbb-dev`)
- [Intel Math Kernel Library (MKL)](http://software.intel.com/en-us/intel-mkl)
Additional Information
----------------------
Read about important [`GTSAM-Concepts`] here.
See the [`INSTALL`] file for more detailed installation instructions.
GTSAM is open source under the BSD license, see the [`LICENSE`](https://bitbucket.org/gtborg/gtsam/src/develop/LICENSE) and [`LICENSE.BSD`](https://bitbucket.org/gtborg/gtsam/src/develop/LICENSE.BSD) files.
Please see the [`examples/`](examples) directory and the [`USAGE`] file for examples on how to use GTSAM.