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A Household multimodal environment (HoME) based on the SUNCG indoor scenes dataset

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HoME Platform

HoME is a platform for artificial agents to learn from vision, audio, semantics, physics, and interaction with objects and other agents, all within a realistic context.

Check out the paper on Arxiv for more details: HoME: a Household Multimodal Environment

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Dependencies

Main requirements:

  • Python 2.7+ with Numpy, Scipy and Matplotlib
  • Panda3d game engine for 3D rendering
  • EVERT engine for 3D acoustic ray-tracing
  • PySoundFile for Ogg Vorbis decoding

To install dependencies on Ubuntu operating systems:

sudo apt-get install python-pip python-dev build-essential libsndfile1
sudo pip2 install --upgrade pip numpy scipy matplotlib panda3d pysoundfile resampy nose coverage Pillow

(Packages nose and coverage are for tests only and can be omitted)

Finally you have to install EVERT. In order to do so, please follow the instructions over at https://github.com/sbrodeur/evert

Installing the library

Download the source code from the git repository:

mkdir -p $HOME/work
cd $HOME/work
git clone https://github.com/HoME-Platform/home-platform.git

Note that the library must be in the PYTHONPATH environment variable for Python to be able to find it:

export PYTHONPATH=$HOME/work/home-platform:$PYTHONPATH 

This can also be added at the end of the configuration file $HOME/.bashrc

Running unit tests

To ensure all libraries where correctly installed, it is advised to run the test suite:

cd $HOME/work/home-platform/tests
./run_tests.sh

Note that this can take some time.

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