### Install CARLA Qt Example Plugin and Tool

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Examples/QtClient/CMakeLists.txt

Installs the Qt example plugin and standalone tool to their respective locations within the CARLA installation directory, making them discoverable by CARLA Studio or runnable directly.

```cmake
include (GNUInstallDirs)
install (
  TARGETS carla_studio_example_plugin
  LIBRARY DESTINATION "${CMAKE_INSTALL_LIBDIR}/carla-studio/plugins"
  RUNTIME DESTINATION "${CMAKE_INSTALL_LIBDIR}/carla-studio/plugins"
  OPTIONAL
)

install (
  TARGETS carla_studio_example_tool
  RUNTIME DESTINATION "${CMAKE_INSTALL_BINDIR}"
  OPTIONAL
)
```

--------------------------------

### Install Dependencies and Run Example Scripts

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/start_quickstart.md

Install necessary Python packages and run example scripts for traffic generation and manual control in separate terminals.

```shell
# Terminal A 
cd PythonAPI\examples

pip3 install -r requirements.txt

python3 generate_traffic.py  

# Terminal B
cd PythonAPI\examples

python3 manual_control.py
```

--------------------------------

### Run Interactive CARLA Setup

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/build_linux_ue5.md

Execute the CARLA setup script interactively to install prerequisites, download Unreal Engine, and build CARLA. This script prompts for sudo password and GitHub credentials.

```sh
cd CarlaUE5
./CarlaSetup.sh --interactive
```

--------------------------------

### Define C++ Example Client Project

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Examples/CMakeLists.txt

Initializes the C++ example client project with its name, C++ language support, and version. This is a standard CMake project setup.

```cmake
project (
  carla-example-cpp-client
  LANGUAGES
    CXX
  VERSION
    ${CARLA_VERSION}
)
```

--------------------------------

### Add Qt Client Subdirectory

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Examples/CMakeLists.txt

Includes the Qt-based community tool example, which builds a dockable plugin and a standalone executable. This step is conditional on Qt being installed.

```cmake
add_subdirectory (${CARLA_WORKSPACE_PATH}/Examples/QtClient QtClient)
```

--------------------------------

### Run CARLA Setup Script

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/build_windows_ue5.md

Execute the CarlaSetup.bat script to install all necessary dependencies, including Visual Studio 2022, CMake, Python 3.8, and Unreal Engine 5.5. This script also downloads CARLA content and builds the project, which can take a significant amount of time.

```sh
cd CarlaUE5
CarlaSetup.bat
```

--------------------------------

### Build CARLA Example Client

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/tuto_cpp.md

Builds the example C++ client for CARLA. This is the first step to running client-side logic.

```sh
cmake --build Build --target carla-example-client
```

--------------------------------

### Run CARLA Example Client

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/tuto_cpp.md

Runs the example C++ client. It can connect to the default CARLA endpoint or a custom one.

```sh
./Build/Examples/carla-example-client
```

```sh
./Build/Examples/carla-example-client 192.168.1.100 3000
```

--------------------------------

### Run CARLA Setup Script (Linux Unattended)

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/README.md

Run the CARLA setup script unattended on Linux by storing Git credentials in the .bashrc file. This automates the download and installation of Unreal Engine and CARLA.

```sh
export GIT_LOCAL_CREDENTIALS=username@github_token
cd CarlaUE5
sudo -E ./CarlaSetup.sh
```

--------------------------------

### CARLA Fundamentals Tutorial Code

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/tutorials.md

Code examples for the CARLA Fundamentals video tutorial. This notebook covers basic concepts and starting your first script.

```Python
# This is a placeholder for the actual code from the Fundamentals.ipynb file.
# The content of the notebook is not directly available in the provided text.
# Please refer to the linked "Fundamentals.ipynb" for the complete code.

# Example structure of what might be in the notebook:
# import carla
# 
# # Connect to the CARLA simulator
# client = carla.Client('localhost', 2000)
# world = client.get_world()
# 
# # Get vehicle information
# blueprint_library = world.get_blueprint_library()
# vehicle_bp = blueprint_library.filter('vehicle.tesla.model3')[0]
# 
# # Spawn a vehicle
# spawn_point = carla.Transform(carla.Location(x=0.0, y=0.0, z=0.5), carla.Rotation(yaw=0.0))
# vehicle = world.spawn_actor(vehicle_bp, spawn_point)
# 
# print(f"Spawned vehicle: {vehicle.id}")

```

--------------------------------

### Launch RViz for Sensor Data Visualization

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/PythonAPI/examples/ros2/README.md

Start RViz using this script to visualize the sensor data being published by CARLA. Docker must be installed and running.

```bash
./run_rviz.sh
```

--------------------------------

### Run Basic Agent Example

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/adv_agents.md

Execute the automatic_control.py script using a Basic Agent. This requires navigating to the examples directory.

```shell
python3 automatic_control.py --agent=Basic
```

--------------------------------

### Installation Configuration

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Util/DockerUtils/fbx/CMakeLists.txt

Specifies the installation destination for the built executable relative to the current source directory.

```cmake
# install location
install(TARGETS FBX2OBJ DESTINATION "${CMAKE_CURRENT_SOURCE_DIR}/../dist")
```

--------------------------------

### Link CARLA Client Library to Example Client

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Examples/CMakeLists.txt

Links the 'carla-client' library to the 'carla-example-client' executable. This makes the CARLA client API available to the example.

```cmake
target_link_libraries (
  carla-example-client PUBLIC
  carla-client
)
```

--------------------------------

### Run Unattended CARLA Setup

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/build_linux_ue5.md

Execute the CARLA setup script in unattended mode after caching sudo password and setting Git credentials. This downloads and installs all necessary components.

```sh
cd CarlaUE5
./CarlaSetup.sh
```

--------------------------------

### Build Standalone Qt Example Tool

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Examples/QtClient/CMakeLists.txt

Configures a standalone executable for the CARLA Studio community example tool. It sets include directories, links against the Qt Widgets library, and enables AUTOMOC.

```cmake
carla_add_executable (
  carla_studio_example_tool
  "Build the CARLA Studio community example tool (standalone)."
  WIN32
  ${CARLA_QT_EXAMPLE_SOURCE}
)

set_target_properties (
  carla_studio_example_tool PROPERTIES
  AUTOMOC ON
)

target_include_directories (
  carla_studio_example_tool PRIVATE
  ${CARLA_QT_EXAMPLE_INCLUDE}
)

target_link_libraries (
  carla_studio_example_tool PRIVATE
  ${CARLA_QT_WIDGETS}
)
```

--------------------------------

### Install CARLA Python Client Library

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/start_quickstart.md

Install the CARLA client library using pip from the wheel file provided in the CARLA package distribution. It is recommended to do this within a virtual environment.

```shell
cd CARLA_ROOT/PythonAPI/dist/

pip3 install carla-*.*.*-cp3**-linux_x86_64.whl
```

--------------------------------

### Build Qt Example Plugin Library

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Examples/QtClient/CMakeLists.txt

Configures a shared library plugin for the CARLA Studio example. It customizes the output name to match CARLA's plugin convention, sets visibility to hidden, and links against Qt Widgets.

```cmake
add_library (
  carla_studio_example_plugin MODULE
  ${CARLA_QT_EXAMPLE_SOURCE}
)

set_target_properties (
  carla_studio_example_plugin PROPERTIES
  AUTOMOC ON
  PREFIX ""
  OUTPUT_NAME "qt-carla-studio-example"
  CXX_VISIBILITY_PRESET hidden
)

target_compile_definitions (
  carla_studio_example_plugin PRIVATE
  CARLA_STUDIO_BUILD_AS_PLUGIN
)

target_include_directories (
  carla_studio_example_plugin PRIVATE
  ${CARLA_QT_EXAMPLE_INCLUDE}
)

target_link_libraries (
  carla_studio_example_plugin PRIVATE
  ${CARLA_QT_WIDGETS}
)
```

--------------------------------

### Install Benchmarking Dependencies

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/adv_benchmarking.md

Install the required Python packages for the benchmarking script. Ensure you are using the specified version for py-cpuinfo.

```python
python -m pip install -U py-cpuinfo==5.0.0 psutil python-tr gpuinfo GPUtil
```

--------------------------------

### Install MkDocs for Documentation

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/cont_contribution_guidelines.md

Installs MkDocs, a static site generator used for building CARLA's documentation. Ensure pip is available and updated.

```sh
sudo pip install mkdocs
```

--------------------------------

### Install CARLA Client Library and Headers

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/LibCarla/CMakeLists.txt

Installs the CARLA client library archive and public headers to the appropriate system directories. This makes the client available for external use.

```cmake
install (
    TARGETS carla-client
    ARCHIVE DESTINATION ${CMAKE_INSTALL_LIBDIR}
    LIBRARY DESTINATION ${CMAKE_INSTALL_LIBDIR}
  )

  install (
    DIRECTORY   ${LIBCARLA_SOURCE_PATH}/carla
    DESTINATION ${CMAKE_INSTALL_INCLUDEDIR}
    FILES_MATCHING
      PATTERN "*.h"
      PATTERN "*.hpp"
      PATTERN "*.inl"
  )
```

--------------------------------

### Install CARLA with C++ Client Enabled

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Examples/CppClient/Standalone/README.md

Build CARLA from source, enabling the C++ client and installing it to a specified prefix. This makes the client library and CMake configuration files available for external projects.

```bash
cd /path/to/carla
cmake -B Build -DBUILD_CARLA_CLIENT=ON -DBUILD_PYTHON_API=OFF
cmake --build Build --target carla-client -j
cmake --install Build --prefix /opt/carla
```

--------------------------------

### Load World and Start Recorder

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/foundations.md

Use the client object to load a specific map into the simulation and start recording simulation data to a log file.

```python
client.load_world('Town07')

client.start_recorder('recording.log')
```

--------------------------------

### Start CARLA Simulator

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/adv_benchmarking.md

Use these commands to launch the CARLA simulator on Linux, Windows, or from source.

```shell
# Linux:
./CarlaUnreal.sh
```

```shell
# Windows:
CarlaUnreal.exe
```

```shell
# Source:
cmake --build Build --target launch
```

--------------------------------

### Build and Install Python API

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/build_windows_ue5.md

Build and install the Python API for CARLA. This command ensures that the Python bindings are compiled and installed, making the CARLA Python client available. Ensure you are in the CarlaUE5 directory and have the x64 Native Tools Command Prompt for VS 2022 open.

```sh
cmake --build Build --target carla-python-api-install
```

--------------------------------

### Install Doxygen and Graphviz

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/ref_cpp.md

Installs the necessary tools for generating C++ documentation on Linux systems.

```sh
# linux
> sudo apt-get install doxygen graphviz
```

--------------------------------

### Run Behavior Agent Example

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/adv_agents.md

Execute the automatic_control.py script using a Behavior Agent with an 'aggressive' profile. This requires navigating to the examples directory.

```shell
python3 automatic_control.py --agent=Behavior --behavior=aggressive
```

--------------------------------

### Install CARLA Python API from Package

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/build_linux_ue5.md

Installs the Python API for the built CARLA package. Replace '***' with the specific version number of the package.

```sh
pip3 install PythonAPI/dist/carla-***.whl
```

--------------------------------

### Start Recording with Additional Data

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/adv_recorder.md

Starts recording simulation data and includes additional information such as velocities, traffic light timings, and physics controls. Set the second argument to True to enable this.

```python
client.start_recorder("/home/carla/recording01.log", True)
```

--------------------------------

### Start Recording

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/adv_recorder.md

Starts the recorder. The file name can be an absolute path. If not specified, the file is saved in CarlaUnreal/Saved. An optional boolean argument 'additional_data' can be set to True to store more detailed information.

```APIDOC
## Start Recording

### Description
Starts the recorder to save simulation data to a specified file.

### Method
`client.start_recorder(filename, additional_data=False)`

### Parameters
*   **filename** (string) - Required - The path and name of the file to save the recording.
*   **additional_data** (boolean) - Optional - If True, stores additional data such as velocities, trigger boxes, and physics controls. Defaults to False.

### Request Example
```python
client.start_recorder("/home/carla/recording01.log")
client.start_recorder("/home/carla/recording01.log", True)
```
```

--------------------------------

### Define CARLA Example C++ Client Source Path

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Examples/CMakeLists.txt

Sets the variable CARLA_EXAMPLE_CPP_CLIENT_SOURCE_PATH to the location of the C++ client example sources. This is a prerequisite for subsequent build steps.

```cmake
set (
  CARLA_EXAMPLE_CPP_CLIENT_SOURCE_PATH
  ${CARLA_WORKSPACE_PATH}/Examples/CppClient
)
```

--------------------------------

### Install CARLA Prerequisites on Linux

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/build_linux_ue5.md

Installs essential build tools and libraries required for compiling CARLA on a Debian-based Linux distribution. Run this command before proceeding with the CARLA build.

```sh
sudo apt update
sudo apt install build-essential ninja-build libvulkan1 python3 python3-dev python3-pip git git-lfs
```

--------------------------------

### CMake Project Setup

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Util/DockerUtils/fbx/CMakeLists.txt

Sets the minimum CMake version and project name. Specifies the generator platform for building.

```cmake
cmake_minimum_required(VERSION 2.8.9)
project(FBX2OBJ)

set(CMAKE_GENERATOR_PLATFORM x64)
```

--------------------------------

### Install and Link CARLA C++ Client

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/tuto_cpp.md

Shows how to build, install, and link the CARLA C++ client library into an external CMake project. This enables using CARLA's C++ API in your own applications.

```bash
# in CARLA's source tree
cmake -B Build -DBUILD_CARLA_CLIENT=ON -DBUILD_PYTHON_API=OFF
cmake --build Build --target carla-client -j
cmake --install Build --prefix /opt/carla
```

```cmake
find_package(Carla CONFIG REQUIRED)
add_executable(myapp main.cpp)
target_link_libraries(myapp PRIVATE Carla::carla-client)
```

```bash
cmake -B build -DCMAKE_PREFIX_PATH=/opt/carla
cmake --build build -j
```

--------------------------------

### Run CARLA Setup Script (Linux Unattended with Terminal Credentials)

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/README.md

Execute the CARLA setup script unattended on Linux by providing Git credentials directly in the terminal command. This method avoids modifying the .bashrc file.

```sh
cd CarlaUE5
sudo -E env GIT_LOCAL_CREDENTIALS=github_username@github_token ./CarlaSetup.sh
```

--------------------------------

### Include and Library Directories

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Util/DockerUtils/fbx/CMakeLists.txt

Configures include paths for source files and library paths for dependencies. Ensure LibXml2 is installed if uncommented.

```cmake
# find_package (LibXml2 REQUIRED)

# include folders
include_directories(src)
include_directories(dependencies/include)

# library folders
link_directories(dependencies/lib/gcc/x64/release)
```

--------------------------------

### client.replay_file

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/foundations.md

Starts a simulation playback from a specified point in a log file. Allows control over playback duration and camera focus.

```APIDOC
## client.replay_file

### Description
Starts a simulation playback from a specified point in a log file. Allows control over playback duration and camera focus.

### Method
```python
client.replay_file(start, duration, camera)
```

### Parameters
#### Path Parameters
- **start** (int) - Required - Recording time in seconds to start the simulation at. If positive, time will be considered from the beginning of the recording. If negative, it will be considered from the end.
- **duration** (int) - Required - Seconds to playback. 0 is all the recording. By the end of the playback, vehicles will be set to autopilot and pedestrians will stop.
- **camera** (int) - Required - ID of the actor that the camera will focus on. Set it to `0` to let the spectator move freely.

### Request Example
```python
client.replay_file("recording01.log", 10, 60, 0)
```

### Response
This method does not return a value, but initiates a simulation playback.
```

--------------------------------

### Serve Documentation Locally with MkDocs

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/cont_contribution_guidelines.md

Starts a local development server to preview documentation changes. Access the live preview via the provided URL.

```sh
mkdocs serve
```

--------------------------------

### Build CARLA Components

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/build_devcontainer.md

Use CMake build targets to install the Python API, launch the Unreal Editor, or package the project.

```bash
cmake --build Build --target carla-python-api-install
```

```bash
cmake --build Build --target launch
```

```bash
cmake --build Build --target package
```

--------------------------------

### Get Waypoints within a Junction

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/core_map.md

Fetch pairs of waypoints marking the start and end boundaries of lanes within a CARLA junction.

```python
waypoints_junc = my_junction.get_waypoints()
```

--------------------------------

### Setup CARLA Simulator and Utilities

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/tuto_G_pedestrian_bones.md

Connect to the CARLA client, retrieve the world object, and enable synchronous mode for controlled simulation time progression. Imports necessary libraries for math, random operations, queues, and image processing.

```python
import carla
import random
import numpy as np
import math
import queue
import cv2 #OpenCV to manipulate and save the images

# Connect to the client and retrieve the world object
client = carla.Client('localhost', 2000)
world = client.get_world()

# Set up the simulator in synchronous mode
settings = world.get_settings()
settings.synchronous_mode = True # Enables synchronous mode
settings.fixed_delta_seconds = 0.05
world.apply_settings(settings)

# We will aslo set up the spectator so we can see what we do
spectator = world.get_spectator()

```

--------------------------------

### Build and Launch Editor with Preset

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/build_windows_ue5.md

After setting up a preset, use this command to build the project and launch the editor, directing build artifacts to the preset-specific folder.

```bash
cmake --build Build/Linux-Development/ --target launch
```

--------------------------------

### Install CARLA Simulator

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/foundations.md

Install the CARLA simulator Python module using pip. Use 'pip install' for Python 2 and 'pip3 install' for Python 3.

```sh
pip install carla-simulator # Python 2
pip3 install carla-simulator # Python 3
```

--------------------------------

### Install Pygame and Numpy on Windows

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/start_quickstart.md

Install the required Python packages, pygame and numpy, for CARLA on Windows. This command installs them for the current user.

```shell
pip3 install --user pygame numpy
```

--------------------------------

### Setting Options

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Unreal/CMakeLists.txt

Initializes the options list for the build.

```cmake
set (CARLA_UNREAL_OPTIONS)
```

--------------------------------

### Traffic Manager Initialization and Autopilot Setup in Batch

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/adv_traffic_manager.md

Demonstrates creating a Traffic Manager instance with a specified port and setting autopilot for spawned actors in a batch process. It also shows how to set a global speed difference for all vehicles managed by the TM.

```python
traffic_manager = client.get_trafficmanager(args.tm-port)
tm_port = traffic_manager.get_port()
...
batch.append(SpawnActor(blueprint, transform).then(SetAutopilot(FutureActor, True,tm_port)))
...
traffic_manager.global_percentage_speed_difference(30.0)
```

--------------------------------

### Set Up and Spawn Instance Segmentation Camera

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/tuto_G_instance_segmentation_sensor.md

Configures the camera's position and rotation in the world and spawns the instance segmentation sensor.

```python
# Get the map spawn points and the spectator
spawn_points = world.get_map().get_spawn_points()
spectator = world.get_spectator()

# Set the camera to some location in the map
cam_location = carla.Location(x=-46., y=152, z=18)
cam_rotation = carla.Rotation(pitch=-21, yaw=-93.4, roll=0)
camera_transform = carla.Transform(location=cam_location, rotation=cam_rotation)
spectator.set_transform(camera_transform)

# Retrieve the semantic camera blueprint and spawn the camera
instance_camera_bp = world.get_blueprint_library().find('sensor.camera.instance_segmentation')
instance_camera = world.try_spawn_actor(instance_camera_bp, camera_transform)
```

--------------------------------

### Multi-Client Simulation Setup

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/adv_traffic_manager.md

Sets up a multi-client simulation where multiple TMs connect to the same port. The first TM acts as a TM-Server, controlling the behavior of subsequent TM-Clients.

```bash
terminal 1: ./CarlaUnreal.sh -carla-rpc-port=4000
terminal 2: python3 generate_traffic.py --port 4000 --tm-port 4050 # TM-Server
terminal 3: python3 generate_traffic.py --port 4000 --tm-port 4050 # TM-Client
```

--------------------------------

### Set Git Credentials for Unattended Setup

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/build_linux_ue5.md

Set the GIT_LOCAL_CREDENTIALS environment variable with your GitHub username and token for unattended CARLA setup.

```sh
export GIT_LOCAL_CREDENTIALS=github_username@github_token
```

--------------------------------

### CARLA Simulator Setup

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/tuto_G_bounding_boxes.md

Boilerplate code to initialize the CARLA client, world, spawn a vehicle and camera, and set up synchronous mode. The camera is attached to the vehicle and its sensor data is streamed to a queue.

```python
import carla
import math
import random
import time
import queue
import numpy as np
import cv2

client = carla.Client('localhost', 2000)
world  = client.get_world()
bp_lib = world.get_blueprint_library()

# spawn vehicle
vehicle_bp =bp_lib.find('vehicle.lincoln.mkz_2020')
vehicle = world.try_spawn_actor(vehicle_bp, random.choice(spawn_points))

# spawn camera
camera_bp = bp_lib.find('sensor.camera.rgb')
camera_init_trans = carla.Transform(carla.Location(z=2))
camera = world.spawn_actor(camera_bp, camera_init_trans, attach_to=vehicle)
vehicle.set_autopilot(True)

# Set up the simulator in synchronous mode
settings = world.get_settings()
settings.synchronous_mode = True # Enables synchronous mode
settings.fixed_delta_seconds = 0.05
world.apply_settings(settings)

# Get the map spawn points
spawn_points = world.get_map().get_spawn_points()

# Create a queue to store and retrieve the sensor data
image_queue = queue.Queue()
camera.listen(image_queue.put)
```

--------------------------------

### Multi-TM Simulation Setup

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/adv_traffic_manager.md

Sets up a multi-TM simulation where multiple TM instances are created on distinct ports. Each TM instance manages its own behavior independently.

```bash
terminal 1: ./CarlaUnreal.sh -carla-rpc-port=4000
terminal 2: python3 generate_traffic.py --port 4000 --tm-port 4050 # TM-Server A
terminal 3: python3 generate_traffic.py --port 4000 --tm-port 4550 # TM-Server B
```

--------------------------------

### Cache Sudo Password for Unattended Setup

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/build_linux_ue5.md

Cache the sudo password for 15 minutes to enable unattended execution of the CARLA setup script.

```sh
sudo -v
```

--------------------------------

### carla.WorldSettings.__init__

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/python_api.md

Creates an object containing desired settings that could later be applied through carla.World and its method apply_settings().

```APIDOC
## carla.WorldSettings.__init__

### Description
Creates an object containing desired settings that could later be applied through `carla.World` and its method `apply_settings()`.

### Method
__init__

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
- **synchronous_mode** (bool) - Optional - Set this to true to enable client-server synchrony.
- **no_rendering_mode** (bool) - Optional - Set this to true to completely disable rendering in the simulation.
- **fixed_delta_seconds** (float) - Optional - Set a fixed time-step in between frames. `0.0` means variable time-step and it is the default mode.
- **max_culling_distance** (float) - Optional - Configure the max draw distance for each mesh of the level.
- **deterministic_ragdolls** (bool) - Optional - Defines wether to use deterministic physics or ragdoll simulation for pedestrian deaths.
- **tile_stream_distance** (float) - Optional - Used for large maps only. Configures the maximum distance from the hero vehicle to stream tiled maps.
- **actor_active_distance** (float) - Optional - Used for large maps only. Configures the distance from the hero vehicle to convert actors to dormant.
- **spectator_as_ego** (bool) - Optional - Used for large maps only. Defines the influence of the spectator on tile loading in Large Maps.

### Request Example
```json
{
  "synchronous_mode": false,
  "no_rendering_mode": false,
  "fixed_delta_seconds": 0.0,
  "max_culling_distance": 0.0,
  "deterministic_ragdolls": false,
  "tile_stream_distance": 3000,
  "actor_active_distance": 2000,
  "spectator_as_ego": true
}
```

### Response
#### Success Response (200)
This method does not return a value, it initializes the object.

#### Response Example
None
```

--------------------------------

### Initialize CARLA Client, World, and Traffic Manager

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/tuto_G_traffic_manager.md

Connects to the CARLA client, retrieves the world object, and sets up both the simulator and the Traffic Manager in synchronous mode. Also sets a random seed for reproducibility.

```python
import carla
import random

# Connect to the client and retrieve the world object
client = carla.Client('localhost', 2000)
world = client.get_world()

# Set up the simulator in synchronous mode
settings = world.get_settings()
settings.synchronous_mode = True # Enables synchronous mode
settings.fixed_delta_seconds = 0.05
world.apply_settings(settings)

# Set up the TM in synchronous mode
traffic_manager = client.get_trafficmanager()
traffic_manager.set_synchronous_mode(True)

# Set a seed so behaviour can be repeated if necessary
traffic_manager.set_random_device_seed(0)
random.seed(0)

# We will aslo set up the spectator so we can see what we do
spectator = world.get_spectator()

```

--------------------------------

### List Available Scenarios

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/adv_benchmarking.md

Use the --show_scenarios flag to list all available scenario parameters without running the benchmark. This helps in understanding the testable configurations.

```bash
python3 performance_benchmark.py --show_scenarios
```

--------------------------------

### Replay File with Specific Start Time

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/adv_recorder.md

Replay a recorded file starting from a specific time and frame. This is useful for re-enacting specific events like collisions.

```python
client.replay_file("col2.log", 13, 0, 122)
```

--------------------------------

### Add Dependencies for Python API Install Target

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/PythonAPI/CMakeLists.txt

Establishes a dependency chain where 'carla-python-api-install' requires 'carla-python-api' to be built first. This ensures the API is built before attempting to install it.

```cmake
add_dependencies (
  carla-python-api-install
  carla-python-api
)
```

--------------------------------

### Create Custom Target for CARLA Python API Installation

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/PythonAPI/CMakeLists.txt

Defines a CMake custom target 'carla-python-api-install' for installing the Python API in editable mode. This is useful for development and testing.

```cmake
carla_add_custom_target (
  carla-python-api-install
  "Build & install the CARLA Python API"
  COMMAND
    ${Python3_EXECUTABLE}
      -m pip install
      -e ${CARLA_PYTHON_API_CARLA_PATH}
  WORKING_DIRECTORY
    ${CARLA_PYTHON_API_CARLA_PATH}
  VERBATIM
  USES_TERMINAL
)
```

--------------------------------

### Spawn and Start AI Walker Controller

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/tuto_G_pedestrian_bones.md

Spawns an AI controller for a pedestrian, starts it, and assigns a random navigation point. This code is used to make pedestrians move autonomously.

```python
controller_bp = world.get_blueprint_library().find('controller.ai.walker')
controller = world.spawn_actor(controller_bp, pedestrian.get_transform(), pedestrian)
controller.start()
controller.go_to_location(world.get_random_location_from_navigation())
```

--------------------------------

### Initialize CARLA Simulator and Traffic Manager

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/tuto_G_pygame.md

Connects to the CARLA client, retrieves the world object, and sets up the simulator and traffic manager in synchronous mode. Also sets a random seed for reproducibility.

```python
import carla
import random
import pygame
import numpy as np

# Connect to the client and retrieve the world object
client = carla.Client('localhost', 2000)
world = client.get_world()

# Set up the simulator in synchronous mode
settings = world.get_settings()
settings.synchronous_mode = True # Enables synchronous mode
settings.fixed_delta_seconds = 0.05
world.apply_settings(settings)

# Set up the TM in synchronous mode
traffic_manager = client.get_trafficmanager()
traffic_manager.set_synchronous_mode(True)

# Set a seed so behaviour can be repeated if necessary
traffic_manager.set_random_device_seed(0)
random.seed(0)

# We will aslo set up the spectator so we can see what we do
spectator = world.get_spectator()

```

--------------------------------

### Run CARLA Benchmark with Custom Settings

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/adv_benchmarking.md

Customize the benchmark by specifying the host, port, output file, number of ticks, and rendering mode. This example also includes Traffic Manager.

```bash
python3 performance_benchmark.py --host=<IP_ADDRESS> --port=<PORT> --file=benchmark.md --tm --ticks=200 --render_mode
```

--------------------------------

### Test Deterministic Mode with generate_traffic.py

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/adv_traffic_manager.md

An example command to test deterministic mode by populating a map with autopilot actors and setting a specific seed. This requires navigating to the example script directory.

```bash
cd PythonAPI/examples
python3 generate_traffic.py -n 50 --seed 9
```

--------------------------------

### Example PASCAL VOC XML Annotation File

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/tuto_G_bounding_boxes.md

This is an example of an XML file generated in the PASCAL VOC format. It includes image details and bounding box information for detected objects.

```xml
<!-- Example PASCAL VOC format file-->
<annotation>
    <folder>output</folder>
    <filename>023235.png</filename>
    <path>/home/matt/Documents/temp/output/023235.png</path>
    <source>
        <database>Unknown</database>
    </source>
    <size>
        <width>800</width>
        <height>600</height>
        <depth>3</depth>
    </size>
    <segmented>0</segmented>
    <object>
        <name>vehicle</name>
        <pose>Unspecified</pose>
        <truncated>0</truncated>
        <difficult>0</difficult>
        <bndbox>
            <xmin>503</xmin>
            <ymin>310</ymin>
            <xmax>511</xmax>
            <ymax>321</ymax>
        </bndbox>
    </object>    <object>
        <name>vehicle</name>
        <pose>Unspecified</pose>
        <truncated>0</truncated>
        <difficult>0</difficult>
        <bndbox>
            <xmin>490</xmin>
            <ymin>310</ymin>
            <xmax>498</xmax>
            <ymax>321</ymax>
        </bndbox>
    </object>
</annotation>
```

--------------------------------

### Run CARLA Docker Container

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/build_devcontainer.md

Starts the CARLA development container, mounting the Unreal Engine and CARLA repository from the host. Use --rebuild to force image rebuild before running.

```sh
export CARLA_UNREAL_ENGINE_PATH=/path/to/UnrealEngine5_carla
Util/Docker/run.sh --dev
```

```sh
Util/Docker/run.sh --dev --rebuild
```

--------------------------------

### Get Closest Waypoint

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/core_map.md

Finds the closest waypoint to a given location, optionally projecting to the road and specifying lane types. Also shows how to get a waypoint using OpenDRIVE parameters.

```python
# Nearest waypoint in the center of a Driving or Sidewalk lane.
waypoint01 = map.get_waypoint(vehicle.get_location(),project_to_road=True, lane_type=(carla.LaneType.Driving | carla.LaneType.Sidewalk))

#Nearest waypoint but specifying OpenDRIVE parameters. 
waypoint02 = map.get_waypoint_xodr(road_id,lane_id,s)
```

--------------------------------

### carla.Client.__init__

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/python_api.md

Initializes a connection to the CARLA simulator. It allows specifying the host, port, and number of worker threads for background updates.

```APIDOC
## carla.Client.__init__

### Description
Client constructor. Establishes a connection to the CARLA simulator server.

### Method
__init__

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters
- **host** (_str_) - IP address where a CARLA Simulator instance is running. Default is localhost (127.0.0.1).
- **port** (_int_) - TCP port where the CARLA Simulator instance is running. Default are 2000 and the subsequent 2001.
- **worker_threads** (_int_) - Number of working threads used for background updates. If 0, use all available concurrency.
```

--------------------------------

### Run ROS 2 Native Example Script

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/PythonAPI/examples/ros2/README.md

This command executes the Python script that interfaces with CARLA using ROS 2. The `--file` argument specifies the sensor configuration.

```python
python3 ros2_native.py --file stack.json
```

--------------------------------

### Qt Package Discovery and Configuration

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Examples/QtClient/CMakeLists.txt

Finds either Qt6 or Qt5 and sets up the necessary variables for linking against the Widgets component. If neither is found, it issues a warning and skips the Qt example target.

```cmake
find_package (Qt6 COMPONENTS Widgets QUIET)

if (NOT Qt6_FOUND)
  find_package (Qt5 COMPONENTS Widgets QUIET)
  if (NOT Qt5_FOUND)
    carla_warning ("Qt6 or Qt5 not found. Skipping Qt example target.")
    return ()
  endif ()
  set (Qt_VERSION 5)
  set (CARLA_QT_WIDGETS Qt5::Widgets)
else ()
  set (Qt_VERSION 6)
  set (CARLA_QT_WIDGETS Qt6::Widgets)
endif ()
```

--------------------------------

### Connect to CARLA Client

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/tuto_G_texture_streaming.md

Establishes a connection to the CARLA simulator. Ensure the simulator is running before executing.

```python
import carla
from PIL import Image

# Connect to client
client = carla.Client('127.0.0.1', 2000)
client.set_timeout(2.0)
```

--------------------------------

### carla.World.remove_on_tick

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/python_api.md

Stops the callback for a given callback ID that was previously started with on_tick().

```APIDOC
## carla.World.remove_on_tick

### Description
Stops the callback for `callback_id` started with __on_tick()__.

### Parameters
#### Path Parameters
- **callback_id** (callback) - Required - The callback to be removed. The ID is returned when creating the callback.

```

--------------------------------

### Setting Definitions

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Unreal/CMakeLists.txt

Defines build-time preprocessor macros, starting with RecastBuilder path.

```cmake
set (
  CARLA_UNREAL_DEFINITIONS
  RECASTBUILDER_PATH="$<TARGET_FILE:RecastBuilder>"
)
```

--------------------------------

### Set up CMake Development Preset

Source: https://github.com/carla-simulator/carla/blob/ue5-dev/Docs/build_windows_ue5.md

Use this command to set up a development preset for your build. This creates a specific folder for the build artifacts.

```bash
cmake --preset Linux-Development
```