Installation

There are two steps to install iGibson, the Interactive Gibson Environment, on your computer.

First, you need to install the simulation environment. Then, you need to download the assets: models of the robotic agents, the interactive objects and 3D reconstructed real-world large environments for your agents to train.

System Requirements

The minimum system requirements are the following:

  • Linux

    • Ubuntu 16.04

    • Nvidia GPU with VRAM > 6.0GB

    • Nvidia driver >= 384

    • CUDA >= 9.0, CuDNN >= v7

    • CMake >= 2.8.12 (can install with pip install cmake)

  • Mac OS X

    • Tested on 10.15

    • PBR features not supported

    • CMake >= 2.8.12 (can install with pip install cmake)

  • Windows

    • Coming soon

Other system configurations may work, but we haven’t tested them extensively and we probably won’t be able to provide as much support as we want.

Installing the Environment

We provide 3 methods to install the simulator.

1. pip

iGibson’s simulator can be installed as a python package using pip:

pip install igibson  # This step takes about 4 minutes
# run the demo
python -m igibson.examples.demo.demo_static

Note: we support using a custom pybullet version to speed up the physics in iGibson, if you want to have the speed up, you would need to do the following steps after installation:

pip uninstall pybullet
pip install https://github.com/StanfordVL/bullet3/archive/master.zip

2. Docker image

Docker provides an easy way to reproduce the development environment across platforms without manually installing the software dependencies. We have prepared docker images that contain everything you need to get started with iGibson.

First, install Docker from the official website. Please make sure that the docker version is at least v19.0 to enable native GPU support.

Next, download our pre-built images with the script in the iGibson repo:

cd iGibson
./docker/pull-images.sh

Two images will be downloaded:

  • igibson/igibson:latest: smaller image, but does not support GUI.

  • igibson/igibson-gui:latest: supports GUI and remote desktop access via VNC.

We also provide scripts to build the images from scratch:

# image without GUI:
cd iGibson/docker/base
./build.sh

# image with GUI and VNC:
cd iGibson/docker/headless-gui
./build.sh

3. Compile from source

Alternatively, iGibson can be compiled from source: iGibson GitHub Repo. First, you need to install anaconda following the guide on their website.

git clone https://github.com/StanfordVL/iGibson --recursive
cd iGibson

conda create -n py3-igibson python=3.6 anaconda # we support python 2.7, 3.5, 3.6, 3.7, 3.8
source activate py3-igibson
pip install -e . # This step takes about 4 minutes

Note: we support using a custom pybullet version to speed up the physics in iGibson, if you want to have the speed up, you would need to do the following steps after installation:

pip uninstall pybullet
pip install https://github.com/StanfordVL/bullet3/archive/master.zip

We recommend the third method if you plan to modify iGibson in your project. If you plan to use it as it is to train navigation and manipulation agents, the pip installation or docker image should meet your requirements.

Downloading the Assets

First, configure where iGibson’s assets (robotic agents, objects, 3D environments, etc.) is going to be stored. It is configured in your_installation_path/igibson/global_config.yaml

To make things easier, the default place to store the data is:

assets_path: your_installation_path/igibson/data/assets 
g_dataset_path: your_installation_path/igibson/data/g_dataset
ig_dataset_path: your_installation_path/igibson/data/ig_dataset
threedfront_dataset_path: your_installation_path/igibson/data/threedfront_dataset 
cubicasa_dataset_path: your_installation_path/igibson/data/assetscubicasa_dataset

If you are happy with the default path, you don’t have to do anything, otherwise you can run this script:

python -m igibson.utils.assets_utils --change_data_path

Second, you can download our robot models and objects from here and unpack it in the assets folder, or simply run this download script:

python -m igibson.utils.assets_utils --download_assets

Third, you need to download some large 3D reconstructed real-world environments (e.g. houses and offices) from our dataset for your agents to be trained in. Create a new folder for those environments and set the path in your_installation_path/igibson/global_config.yaml (default and recommended: your_installation_path/igibson/data/g_dataset and your_installation_path/igibson/data/ig_dataset). You can get access and download the Gibson dataset (after filling up the following license agreement) and the iGibson dataset (following the guide here or following the instructions below). In addition, you can download a single high quality small environment R’s for demo purposes.

To download the demo data, run:

python -m igibson.utils.assets_utils --download_demo_data

The full Gibson and iGibson dataset can be downloaded using the following command, this script automatically downloads, decompresses, and puts the dataset to correct place. You will get URL after filling in the agreement form.

Download iGibson dataset

python -m igibson.utils.assets_utils --download_ig_dataset

Download Gibson dataset (agreement signing required to get URL)

python -m igibson.utils.assets_utils --download_dataset URL

Testing

To test igibson is properly installed, you can run

python
>> import igibson

For a full suite of tests and benchmarks, you can refer to tests for more details.

Uninstalling

Uninstalling iGibson is easy: pip uninstall igibson