The fertilized forests library is a general purpose, platform independent, easy to extend, Decision Forest library. You can find detailed information including API documentation on http://www.fertilized-forests.org.
The construction branch is unstable
. Only versions that are completely tested
get merged to master
, so master
is always always stable, with all tests
passing and all builds running.
The current status of unstable
is as follows:
Build and tests, core library - Windows
Build and tests, core library and Python interface - Linux & Mac OS
The project has a CMake build system. The series of
mkdir build
cd build
cmake ..
cmake --build . # add `--config Release` for Windows
cmake --build . --target test # run the tests (with `--target run_tests` and `--config Release` on Windows).
cmake --build . --target install # run the installation (... for Windows).
is sufficient to create the project in a Release
configuration on all
platforms.
The build does require Boost
and Eigen
to link against.
Additionally, it offers to have feature extraction with OpenCV, and
to build Python and MATLAB bindings. Hence, the following switches might be
interesting for you:
-DCMAKE_BUILD_TYPE={Release|Debug}
-DWITH_PYTHON={OFF|ON}
-DWITH_MATLAB={OFF|ON}
-DWITH_CAFFE={OFF|ON}
-DBOOST_ROOT=...
-DEIGEN3_INCLUDE_DIR=...
-DCAFFE_ROOT_DIR=...
-DCAFFE_CPU_ONLY={OFF|ON} # Must match the caffe compilation mode.
And there are many more fine-grained options for control. Simply open the
file CMakeCache.txt
after you ran CMake for the first time. You can change
every variable in the file by adding a command line switch -DVARNAME=VALUE
to another CMake call to adjust the configuration.
If you plan to extend or modify the library, please have a look at the dedicated developers guide. There is a fertilized-devtools project that provides a code generator to automatically keep the bindings and the serialization code up-to-date.
There is an FAQ page
on the homepage with many helpful tips. If you want to see how
environment setup in general works, see the files appveyor.yaml
(Windows) or
.travis.yaml
(Linux).
If all this fails or you find a bug, please report it on github to let the community know and get it fixed!
Hint: When building with MATLAB on Linux, you might run into an issue with MATLAB not finding GLIBCXX_X.Y.ZZ. It's a known issue of MATLAB and easy to fix. You can find the solution here.
Hint: When building the Python bindings for Python 3 on Linux, you might have to
cd /usr/lib/x86_64-linux-gnu/
sudo ln -s libboost_python-py3[X].so libboost_python3.so
where [X] must be replaced with the appropriate value. This should solve the
problem that boost_python3
can not be found.