BUILD_FROM_SOURCE.md

Build from Source

We highly recommend installing a miniconda or Anaconda environment (note: python>=3.6 is required). Once you have Anaconda installed, here are the instructions.

1. Clone this github repository.

   # Checkout the latest stable release
   git clone --branch stable https://github.com/facebookresearch/habitat-sim.git
   cd habitat-sim

   List of stable releases is available here. Master branch contains 'bleeding edge' code and under active development.

2. Install Dependencies

   Common

   # We require python>=3.6 and cmake>=3.10
   conda create -n habitat python=3.6 cmake=3.14.0
   conda activate habitat
   pip install -r requirements.txt

   Linux (Tested with Ubuntu 18.04 with gcc 7.4.0)

   sudo apt-get update || true
   # These are fairly ubiquitous packages and your system likely has them already,
   # but if not, let's get the essentials for EGL support:
   sudo apt-get install -y --no-install-recommends \
        libjpeg-dev libglm-dev libgl1-mesa-glx libegl1-mesa-dev mesa-utils xorg-dev freeglut3-dev

   See this configuration for a full list of dependencies that our CI installs on a clean Ubuntu VM. If you run into build errors later, this is a good place to check if all dependencies are installed.

3. Build Habitat-Sim

   Default build (for machines with a display attached)

   # Assuming we're still within habitat conda environment
   python setup.py install

   For headless systems (i.e. without an attached display, e.g. in a cluster) and multiple GPU systems

   python setup.py install --headless

   For systems with CUDA (to build CUDA features)

   python setup.py install --with-cuda

   With physics simulation via Bullet Physics SDK: First, install Bullet Physics using your system's package manager.

   Mac

   brew install bullet

   Linux

   sudo apt-get install libbullet-dev

   Next, enable bullet physics build via:

   python setup.py install --bullet    # build habitat with bullet physics

   Note1: Build flags stack, e.g. to build in headless mode, with CUDA, and bullet, one would use --headless --with-cuda --bullet.

   Note2: some Linux distributions might require an additional --user flag to deal with permission issues.

   Note3: for active development in Habitat, you might find ./build.sh instead of python setup.py install more useful.

4. [Only if using build.sh] For use with Habitat Lab and your own python code, add habitat-sim to your PYTHONPATH. For example modify your .bashrc (or .bash_profile in Mac OS X) file by adding the line:

   export PYTHONPATH=$PYTHONPATH:/path/to/habitat-sim/

Common build issues

• If your machine has a custom installation location for the nvidia OpenGL and EGL drivers, you may need to manually provide the EGL_LIBRARY path to cmake as follows. Add -DEGL_LIBRARY=/usr/lib/x86_64-linux-gnu/nvidia-opengl/libEGL.so to the build.sh command line invoking cmake. When running any executable adjust the environment as follows: LD_LIBRARY_PATH=/usr/lib/x86_64-linux-gnu/nvidia-opengl:${LD_LIBRARY_PATH} examples/example.py.

• By default, the build process uses all cores available on the system to parallelize. On some virtual machines, this might result in running out of memory. You can serialize the build process via:

  python setup.py build_ext --parallel 1 install

• Build is tested on Tested with Ubuntu 18.04 with gcc 7.4.0 and MacOS 10.13.6 with Xcode 10 and clang-1000.10.25.5. If you experience compilation issues, please open an issue with the details of your OS and compiler versions.

  We also have a dev slack channel, please follow this link to get added to the channel.