157 lines
7.2 KiB
Markdown
157 lines
7.2 KiB
Markdown
# carlaviz
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The carlaviz plugin is used to visualize the simulation in a web browser. A windows with some basic representation of the scene is created. Actors are updated on-the-fly, sensor data can be retrieved, and additional text, lines and polylines can be drawn in the scene.
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* [__General information__](#general-information)
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* [Support](#support)
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* [__Get carlaviz__](#get-carlaviz)
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* [Prerequisites](#prerequisites)
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* [Download the plugin](#download-the-plugin)
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* [__Utilities__](#utilities)
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---
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## General information
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* __Contributor__ — Minjun Xu, also known as [wx9698](https://github.com/wx9698).
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* __License__ — [MIT](https://en.wikipedia.org/wiki/MIT_License).
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### Support
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* __Linux__ — CARLA 0.9.6, 0.9.7, 0.9.8, 0.9.9, 0.9.10.
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* __Windows__ — CARLA 0.9.9, 0.9.10.
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* __Build from source__ — Latest updates.
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---
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## Get carlaviz
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### Prerequisites
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* __Docker__ — Visit the docs and [install Docker](https://docs.docker.com/get-docker/).
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* __Operative system__ — Any OS able to run CARLA should work.
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* __Websocket-client__ — ```pip3 install websocket_client```. Install [pip](https://pip.pypa.io/en/stable/installing/) if it is not already in the system.
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### Download the plugin
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Open a terminal and pull the Docker image of carlaviz, based on the CARLA version to be run.
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```bash
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# Pull only the image that matches the CARLA package being used
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docker pull mjxu96/carlaviz:0.9.6
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docker pull mjxu96/carlaviz:0.9.7
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docker pull mjxu96/carlaviz:0.9.8
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docker pull mjxu96/carlaviz:0.9.9
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docker pull mjxu96/carlaviz:0.9.10
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# Pull this image if working on a CARLA build from source
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docker pull mjxu96/carlaviz:latest
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```
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!!! Important
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Currently in Windows there is only support for 0.9.9 and 0.9.10.
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CARLA up to 0.9.9 (included) is set to be single-stream. For later versions, multi-streaming for sensors is implemented.
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* __In single-stream__, a sensor can only be heard by one client. When a sensor is already being heard by another client, for example when running `manual_control.py`, carlaviz is forced to duplicate the sensor in order to retrieve the data, and performance may suffer.
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* __In multi-stream__, a sensor can be heard by multiple clients. carlaviz has no need to duplicate these and performance does not suffer.
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!!! Note
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Alternatively on Linux, users can build carlaviz following the instructions [here](https://github.com/carla-simulator/carlaviz/blob/master/docs/build.md), but using a Docker image will make things much easier.
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---
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## Run carlaviz
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__1. Run CARLA.__
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* __a) In a CARLA package__ — Go to the CARLA folder and start the simulation with `CarlaUE4.exe` (Windows) or `./CarlaUE4.sh` (Linux).
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* __b) In a build from source__ — Go to the CARLA folder, run the UE editor with `make launch` and press `Play`.
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__2. Run carlaviz.__ In another terminal run the following command according to the Docker image that has been downloaded.
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Change `<name_of_Docker_image>` for the name of the image previously downloaded, e.g. `mjxu96/carlaviz:latest` or `mjxu96/carlaviz:0.9.10`.
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```sh
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# On Linux system
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docker run -it --network="host" -e CARLAVIZ_HOST_IP=localhost -e CARLA_SERVER_IP=localhost -e CARLA_SERVER_PORT=2000 <name_of_Docker_image>
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# On Windows/MacOS system
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docker run -it -e CARLAVIZ_HOST_IP=localhost -e CARLA_SERVER_IP=host.docker.internal -e CARLA_SERVER_PORT=2000 -p 8080-8081:8080-8081 -p 8089:8089 <name_of_Docker_image>
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```
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If the everything has been properly set, carlaviz will show a successful message similar to the following.
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!!! Warning
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Remember to edit the previous command to match the Docker image being used.
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__3. Open the localhost__ Open your web browser and go to `http://127.0.0.1:8080/`. carlaviz runs by default in port `8080`. The output should be similar to the following.
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---
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## Utilities
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Once the plugin is operative, it can be used to visualize the simulation, the actors that live in it, and the data the sensors retrieve. The plugin shows a visualization window on the right, were the scene is updated in real-tme, and a sidebar on the left with a list of items to be shown. Some of these items will appear in the visualization window, others (mainly sensor and game data) appear just above the items list.
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Here is a list of options available for visualization. Additional elements may show, such as
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* __View Mode__ — Change the point of view in the visualization window.
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* `Top Down` — Aerial point of view.
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* `Perspective` — Free point of view.
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* `Driver` — First person point of view.
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* __/vehicle__ — Show properties of the ego vehicle. Includes a speedometer and accelerometer in the visualization window, and the data retrieved by IMU, GNSS and collision detector sensors.
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* `/velocity` — Velocity of the ego vehicle.
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* `/acceleration` — Acceleration of the ego vehicle.
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* __/drawing__ — Show additional elements in the visualization window drawn with [CarlaPainter](https://github.com/wx9698/carlaviz/blob/master/examples/carla_painter.py).
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* `/texts` — Text elements.
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* `/points` — Point elements.
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* `/polylines` — Polyline elements.
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* __/objects__ — Show actors in the visualization window.
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* `/walkers` — Update walkers.
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* `/vehicles` — Update vehicles.
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* __/game__ — Show game data.
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* `/time` — Current simulation time and frame.
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* __/lidar__ — LIDAR sensor data.
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* `/points` — Cloud of points detected by a LIDAR sensor.
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* __/radar__ — LIDAR sensor data.
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* `/points` — Cloud of points detected by a RADAR sensor.
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* __/traffic__ — Landmark data.
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* `/traffic_light` — Show the map's traffic lights in the visualization window.
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* `/stop_sign` — Show the map's stop signs in the visualization window.
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Try to spawn some actors. These will be automatically updated in the visualization window.
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```sh
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cd PythonAPI/examples
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# Spawns actors in a synchronous mode simulation
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python3 generate_traffic.py -n 10 -w 5
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```
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Spawn an ego vehicle with manual control and move around, to see how the plugin updates sensor data.
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```sh
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cd PythonAPI/examples
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python3 manual_control.py
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```
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The contributor ([wx9698](https://github.com/wx9698)), created an additional class, [CarlaPainter](https://github.com/wx9698/carlaviz/blob/master/examples/carla_painter.py), that allows the user to draw elements to be shown in the visualization window. These include text, points and polylines. Follow [this example](https://github.com/carla-simulator/carlaviz/blob/master/examples/example.py) to spawn an ego vehicle with a LIDAR, and draw the LIDAR data, the trajectory and velocity of the vehicle.
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---
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That is all there is to know about the carlaviz plugin. If there are any doubts, feel free to post these in the forum.
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<div class="build-buttons">
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<p>
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<a href="https://github.com/carla-simulator/carla/discussions/" target="_blank" class="btn btn-neutral" title="Go to the CARLA forum">
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CARLA forum</a>
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</p>
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</div>
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