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Installation
########################
1. Conda Environment
~~~~~~~~~~~~~~~~~~~~~~~~
The ScenarioNet repo contains tools for converting scenarios and building database from various data sources.
We recommend to create a new conda environment and install Python>=3.8,<=3.9::
conda create -n scenarionet python==3.9
conda activate scenarionet
2. Make a New Folder (Optional)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In addition, the operations in ScenarioNet are executed as Python module ``python -m``, and thus we have to make sure
the working directory contains NO folders named ``metadrive`` or ``scenarionet``.
Therefore, we strongly recommend creating a new folder under your routine working directory.
For example, supposing you prefer working at ``/home/lee``,
it would be greate to have a new folder ``mdsn`` created under this path.
And the ``git clone`` and package installation should happen in this new directory.
As a result, the directory tree should look like this::
/home/lee/
├──mdsn
├──metadrive
├──scenarionet
├──...
In this way, you can freely run the dataset operations at any places other than ``/home/lee/mdsn``.
Now, let's move to this new directory for further installation with ``cd mdsn``.
.. note::
This step is optional. One can still ``git clone`` and ``pip install`` the following two packages at any places.
If any ``python -m scenarionet.[command]`` fails to run, please check if there is a folder called `metadrive`
or `scenarionet` contained in the current directory. If so, please switch to a new directory to avoid this issue.
3. Install MetaDrive
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The simulation part is maintained in `MetaDrive <https://github.com/metadriverse/metadrive>`_ repo, and let's install MetaDrive first.
**1. Install MetaDrive**
The installation of MetaDrive on different platforms is straightforward and easy!
We recommend to install from Github in the following two ways::
We recommend to install in the following ways::
# Method 1 (Recommend, if you don't want to access the source code)
pip install git+https://github.com/metadriverse/metadrive.git
# Method 2
# Method 1 (Recommend, latest version, source code exposed)
git clone git@github.com:metadriverse/metadrive.git
cd metadrive
pip install -e.
A more stable version of MetaDrive can be installed from PyPI by::
# More stable version than installing from Github
# Method 2 (Stable version, source code hidden)
pip install "metadrive-simulator>=0.4.1.1"
To check whether MetaDrive is successfully installed, please run::
python -m metadrive.examples.profile_metadrive
.. note:: Please do not run the above command in the folder that has a sub-folder called :code:`./metadrive`.
.. note:: Please do not run the above command at a directory that has a sub-folder called :code:`./metadrive`.
**2. Install ScenarioNet**
4. Install ScenarioNet
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
For ScenarioNet, we only provide Github installation. Likewise, there are two ways to install from Github::
For ScenarioNet, we only provide Github installation::
# Method 1 (Recommend, if you don't want to access the source code)
pip install git+https://github.com/metadriverse/scenarionet.git
# Method 2
git clone git@github.com:metadriverse/scenarionet.git
cd scenarionet
Anyone of the following commands will automatically install basic requirements with additional requirements
for specific datasets::
# Install basic requirement only
pip install -e .
# Install Waymo official toolkit
pip install -e .[waymo]
# Install nuScenes development tookit
pip install -e .[nuscenes]
# Install nuPlan development tookit
pip install -e .[nuplan]
# Install all toolkit for all datasets
pip install -e .[all]
.. note::
If you don't wanna access the source code, you can install these two packages with
``pip install git+https://github.com/metadriverse/scenarionet.git``
and ``pip install git+https://github.com/metadriverse/metadrive.git``.
Though it is more straightforward, one has to install additional requirements, like development
toolkits, manually.