Welcome to the home of Deep MDP - a fast, modular and parallelized Python implementation of the MDP framework for Multi-Object Tracking with added support for deep learning.

• Python dependencies
• Installation in Linux
  • imbalanced-dataset-sampler
  • libsvm
  • C_modules
• Installation in Windows

Python dependencies

pip3 install xlwt

Installation in Linux

imbalanced-dataset-sampler

cd models/thirdparty/imbalanced-dataset-sampler && python3 setup.py install

libsvm

• install libsvm:

cd models/thirdparty/libsvm-3.23/python

make

cp ../libsvm.so.2 /usr/local/lib
mkdir ../../../libsvm
mkdir ../../../libsvm/linux
cp ../libsvm.so.2 ../../../libsvm/linux

mkdir ../../../libsvm
mkdir ../../../libsvm/linux
cp ../libsvm.so.2 ../../../libsvm/linux/libsvm.so.2

cd -

C_modules

cd cmodules && mkdir build && cd build
 
cmake ..
 
sudo make install

Installation in Windows

• install libsvm by following the instructions here and here

• install cmake

• install Visual Studio 2015 by following instructions here

• install OpenCV by following the instructions here

• installation using pre built binaries is not guaranteed to work so build from source if cmake does not find OpenCV in the next step

• create an environment variable called OpenCV_DIR pointing to the OpenCV installation or build folder containing the OpenCVConfig.cmake file

• create folder tracking_module/cmodules/build and run cmake .. from there

• Open MDP.sln in Visual Studio, change build type to Release from Debug, right click on All Build in the Solution Explorer and select Build

• Once this completes, right click on INSTALL in the Solution Explorer and select Build