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Quick start package installation
This guide shows how to download and install the packaged version of CARLA. The package includes the CARLA server and two options for the client library. There are additional assets that can be downloaded and imported into the package. Advanced customization and development options that require use of the Unreal Engine editor are not available but these can be accessed by using the build version of CARLA for either Windows or Linux.
- Before you begin
- CARLA installation
- Import additional assets
- Install client library
- Running CARLA
- Updating CARLA
- Follow-up
Before you begin
The following requirements should be fulfilled before installing CARLA:
- System requirements. CARLA is built for Windows and Linux systems.
- An adequate GPU. CARLA aims for realistic simulations, so the server needs at least a 6 GB GPU although we would recommend 8 GB. A dedicated GPU is highly recommended for machine learning.
- Disk space. CARLA will use about 20 GB of space.
- Python. Python is the main scripting language in CARLA. CARLA supports Python 2.7 and Python 3 on Linux, and Python 3 on Windows.
- Pip. Some installation methods of the CARLA client library require pip or pip3 (depending on your Python version) version 20.3 or higher. To check your pip version:
# For Python 3 pip3 -V
# For Python 2 pip -V
If you need to upgrade:
# For Python 3 pip3 install --upgrade pip
# For Python 2 pip install --upgrade pip
- Two TCP ports and good internet connection. 2000 and 2001 by default. Make sure that these ports are not blocked by firewalls or any other applications.
- Other requirements. CARLA requires some Python dependencies. Install the dependencies according to your operating system:
Windows
pip3 install --user pygame numpy
Linux
pip install --user pygame numpy &&
pip3 install --user pygame numpy
CARLA installation
There are two methods to download and install CARLA as a package:
A) Download the Debian package.
B) Download the package from GitHub.
A. Debian CARLA installation
The Debain package is available for both Ubuntu 18.04 and Ubuntu 20.04, however the officially supported platform is Ubuntu 18.04.
1. Set up the Debian repository in the system:
sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 1AF1527DE64CB8D9
sudo add-apt-repository "deb [arch=amd64] http://dist.carla.org/carla $(lsb_release -sc) main"
2. Install CARLA and check for the installation in the /opt/
folder:
sudo apt-get update # Update the Debian package index
sudo apt-get install carla-simulator # Install the latest CARLA version, or update the current installation
cd /opt/carla-simulator # Open the folder where CARLA is installed
This repository contains CARLA 0.9.10 and later versions. To install a specific version add the version tag to the installation command:
apt-cache madison carla-simulator # List the available versions of Carla
sudo apt-get install carla-simulator=0.9.10-1 # In this case, "0.9.10" refers to a CARLA version, and "1" to the Debian revision
!!! Important To install CARLA versions prior to 0.9.10, change to a previous version of the documentation using the panel in the bottom right corner of the window, and follow the old instructions.
B. Package installation
This repository contains different versions of CARLA. You will find options to download the current release with all the most recent fixes and features, previous releases and a nightly build with all the developmental fixes and features (the nightly build is the most unstable version of CARLA).
The package is a compressed file named CARLA_version.number. Download and extract the release file. It contains a precompiled version of the simulator, the Python API module and some scripts to be used as examples.
Import additional assets
Each release has it's own additional package of extra assets and maps. This additional package includes the maps Town06, Town07, and Town10. These are stored separately to reduce the size of the build, so they can only be imported after the main package has been installed.
1. Download the appropriate package for your desired version of CARLA.
2. Extract the package:
-
On Linux:
- move the package to the Import folder and run the following script to extract the contents:
cd path/to/carla/root
./ImportAssets.sh
-
On Windows:
- Extract the contents directly in the root folder.
Install client library
CARLA versions prior to 0.9.12
Previous versions of CARLA did not require the Python library to be installed, they came with an .egg
file that was ready to use out of the box. CARLA versions 0.9.12+ change this behavior significantly; there are several options available to install the client library. If you are using a version of CARLA prior to 0.9.12, please select that version in the bottom right corner of the screen to see the relevant documentation. Otherwise, read on below about the available options in CARLA 0.9.12+.
CARLA 0.9.12+
There are several options available to install and use the CARLA client library:
- .egg file
- .whl file
- Downloadable Python package
Read more below about the requirements and limitations of each method before deciding which one to use. Please note that mixing the different methods can lead to incompatibilities, so use virtual environments when possible or uninstall a previously installed library before using a new one.
A. .egg files
CARLA provides
.egg
files inPythonAPI/carla/dist/
for different Python versions that are ready to use out of the box. Each of the example scripts inPythonAPI/examples
includes a code snippet that looks for this file automatically. In Linux, you may need to add this file to yourPYTHONPATH
. Read more about.egg
files in CARLA here.
If you have previously installed the client library with
pip
, this will take precedence over the.egg
file. You will need to uninstall the previous library first.
B. .whl files
CARLA provides
.whl
files for different Python versions. You will need to install the.whl
file. The.whl
file is found inPythonAPI/carla/dist/
. There is one file per supported Python version, indicated by the file name (e.g., carla-0.9.12-cp36-cp36m-manylinux_2_27_x86_64.whl indicates Python 3.6).
It is recommended to install the CARLA client library in a virtual environment to avoid conflicts when working with multiple versions.
To install the CARLA client library, run the following command, choosing the file appropriate to your desired Python version. You will need pip/pip3 version 20.3 or above. See the Before you begin section for how to check the version and upgrade pip/pip3:
# Python 3 pip3 install <wheel-file-name>.whl
# Python 2 pip install <wheel-file-name>.whl
If you previously installed the client library, you should uninstall the old one before installing the new one.
C. Downloadable Python package
The CARLA client library can be downloaded from PyPi. This library is compatible with Python versions 2.7, 3.6, 3.7, and 3.8. To install it you will need pip/pip3 version 20.3 or above. See the Before you begin section for how to check the version and upgrade pip/pip3.
It is recommended to install the CARLA client library in a virtual environment to avoid conflicts when working with multiple versions.
To install the client library from PyPi, run the following command:
# Python 3 pip3 install carla
# Python 2 pip install carla
The PyPi download is suitable for use with CARLA packages only (i.e., not with a version built from source). Since the PyPi download only contains the client library, it is most useful in situations where you will be communicating with a remote CARLA server where you do not require downloading a full CARLA package.
Running CARLA
The method to start a CARLA server depends on the installation method you used and your operating system:
- Debian installation:
cd /opt/carla-simulator/bin/
./CarlaUE4.sh
- Linux package installation:
cd path/to/carla/root
./CarlaUE4.sh
- Windows package installation:
cd path/to/carla/root
CarlaUE4.exe
A window containing a view over the city will pop up. This is the spectator view. To fly around the city use the mouse and WASD
keys, holding down the right mouse button to control the direction.
This is the server simulator which is now running and waiting for a client to connect and interact with the world. You can try some of the example scripts to spawn life into the city and drive a car:
# Terminal A
cd PythonAPI\examples
python3 -m pip install -r requirements.txt # Support for Python2 is provided in the CARLA release packages
python3 generate_traffic.py
# Terminal B
cd PythonAPI\examples
python3 manual_control.py
Command-line options
There are some configuration options available when launching CARLA and they can be used as follows:
./CarlaUE4.sh -carla-rpc-port=3000
-carla-rpc-port=N
Listen for client connections at portN
. Streaming port is set toN+1
by default.-carla-streaming-port=N
Specify the port for sensor data streaming. Use 0 to get a random unused port. The second port will be automatically set toN+1
.-quality-level={Low,Epic}
Change graphics quality level. Find out more in rendering options.- List of Unreal Engine 4 command-line arguments. There are a lot of options provided by Unreal Engine however not all of these are available in CARLA.
The script PythonAPI/util/config.py
provides more configuration options and should be run when the server has been started:
./config.py --no-rendering # Disable rendering
./config.py --map Town05 # Change map
./config.py --weather ClearNoon # Change weather
./config.py --help # Check all the available configuration options
Updating CARLA
There is no way to update the packaged version of CARLA. When a new version is released, the repository is updated and you will need to delete the previous version and install the new version.
If you installed the client library using pip/pip3, you should uninstall it by running:
# Python 3
pip3 uninstall carla
# Python 2
pip uninstall carla
Follow-up
By now you should have a packaged version of CARLA up and running. If you came across any difficulties during the installation process, feel free to post in the CARLA forum or in the Discord channel.
The next step is to learn more about the core concepts in CARLA. Read the First steps section to start learning. You can also find all the information about the Python API classes and methods in the Python API reference.