Download and Setup

April 5, 2017 ยท View on GitHub

Installing libvot requires minimal efforts. To use its full functionality, you need to install some additional dependencies.

Additional Dependencies

Required: gflags, glog and gtest (if test is enabled)

gflags is a handy library to parse command-line options. glog is a logging utility. Together with gtest, a unit test suite, they are made public by google to facilitate the development of modern C++ software.
To install them on Mac:

brew update
brew glog gflags gtest

To install them on Linux (e.g. ubuntu):

sudo apt-get install libgoogle-glog-dev libgflags-dev libgtest-dev

Note: However, apt-get mysteriously doesn't install gtest lib even if you run sudo apt-get install libgtest-dev. To make things work, you have to manually build gtest from source (apt-get does ship source code in /usr/src/gtest). See this post for details.

Optional: Boost (>1.55)

Boost is a set of powerful C++ libraries. However, it also has a huge code base and takes a long time to build. If you haven't done so, you can consult the following pages for your platform:

Note that if you would like to build the python export, you also need to install boost-python. On Mac, boost and boost-python can be easily installed via brew:

brew update
brew install boost
brew install boost-python --with-python

On Linux, specifically ubuntu, you can use apt-get:

sudo apt-get install libboost-all-dev

Optional: OpenCV (>2.4)

Several modules of libvot depends on OpenCV. Though it is not required, we highly recommend you to build libvot with OpenCV.

See the installation guide of OpenCV here.

Optional: Install CUDA

In order to build or run libvot with GPU support, both NVIDIA's Cuda Toolkit (>7.5) and cuDNN (>v5) need to be installed.

Check NVIDIA Compute Capability of your GPU card

Check compute capability here.

Download and install Cuda Toolkit

Install Cuda Toolkit

Install the toolkit into e.g. /usr/local/cuda

Download and install cuDNN

Download cuDNN

Uncompress and copy the cuDNN files into the toolkit directory. Assuming the toolkit is installed in /usr/local/cuda, run the following commands (edited to reflect the cuDNN version (e.g., 7.5) you downloaded):

tar xvzf cudnn-7.5-<platform>-x64-v5.0.tgz
sudo cp cudnn-7.5-<platform>-x64-v5.0/cudnn.h /usr/local/cuda/include
sudo cp cudnn-7.5-<platform>-x64-v5.0/libcudnn* /usr/local/cuda/lib
sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib/libcudnn*

You may also put cuDNN libs and includes in another folder. Then you have to change the CMake configurations to reflect this path.

Install from Source

The build system of libvot is based on CMake. To take full advantages of the new features in C++11, we require the version of CMake to be 2.8.12 or above. Current we have tested our project under Linux (Ubuntu 14.04, CentOS 7) and MacOS (10.10 - 10.12) using gcc. The common steps to build the library are:

  1. Extract source files.
  2. Create build directory and change to it.
  3. Run CMake to configure the build tree.
  4. Build the software using selected build tool.
  5. Run "make test"
  6. See src/example for some demo programs of this library.

On Unix-like systems with GNU Make as the build tool, the following sequence of commands can be used to compile the source code.

$ cd libvot
$ git submodule init & git submodule update  
$ mkdir build && cd build
$ cmake ..
$ make && make test