Document cameras and sensors
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Cameras and sensors
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===================
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Cameras and sensors can be added to the player vehicle by defining them in the
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settings file sent by the client on every new episode. Check out the examples at
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[CARLA Settings example][settingslink].
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This document describes the details of the different cameras/sensors currently
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available as well as the resulting images produced by them.
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Although we plan to extend the sensor suite of CARLA in the near future, at the
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moment there are three different sensors available. These three sensors are
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implemented as different post-processing effects applied to scene capture
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cameras.
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* [Scene final](#Scene final)
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* [Depth map](#Depth map)
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* [Semantic segmentation](#Semantic segmentation)
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!!! note
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The images are sent by the server as a BGRA array of bytes. The provided
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Python client retrieves the images in this format, it's up to the users to
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parse the images and convert them to the desired format. There are some
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examples in the PythonClient folder showing how to parse the images.
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There is a fourth post-processing effect available, _None_, which provides a
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view with of the scene with no effect, not even lens effects like flares or DOF;
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we will skip this one in the following descriptions.
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We provide a tool to convert raw depth and semantic segmentation images to a
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more human readable palette of colors. It can be found at
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["Util/ImageConverter"][imgconvlink].
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[settingslink]: https://github.com/carla-simulator/carla/blob/master/Docs/Example.CarlaSettings.ini
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[imgconvlink]: https://github.com/carla-simulator/carla/tree/master/Util/ImageConverter
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Scene final
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-----------
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The "scene final" camera provides a view of the scene after applying some
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post-processing effects to create a more realistic feel.
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Depth map
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---------
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Semantic segmentation
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---------------------
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The "semantic segmentation" camera classifies every object in the view by
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displaying it in a different color according to the object class. E.g.,
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pedestrians appear in a different color than vehicles.
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The server provides an image with the tag information encoded in the red
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channel. A pixel with a red value of x displays an object with tag x. The
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following tags are currently available
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Value | Tag
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-----:|:-----
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0 | None
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1 | Buildings
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2 | Fences
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3 | Other
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4 | Pedestrians
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5 | Poles
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6 | RoadLines
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7 | Roads
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8 | Sidewalks
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9 | Vegetation
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10 | Vehicles
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11 | Walls
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12 | TrafficSigns
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This is implemented by tagging every object in the scene before hand (either at
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begin play or on spawn). The objects are classified by their relative file
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system path in the project. E.g., every mesh stored in the "pedestrians" folder
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it's tagged as pedestrian.
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@ -4,8 +4,9 @@ CARLA Documentation
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#### Using CARLA
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* [How to run CARLA server and client](how_to_run.md)
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* [CARLA Settings](carla_settings.md)
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* [CARLA settings](carla_settings.md)
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* [Measurements](measurements.md)
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* [Cameras and sensors](cameras_and_sensors.md)
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* [Troubleshooting](troubleshooting.md)
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#### Building from source
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@ -39,7 +39,7 @@ ai_control | Control | Vehicle's AI control that would apply t
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The transform contains two Vector3D objects, location and orientation.
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Currently, the orientation is represented as the Cartesian coordinates X, Y, Z.
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_We will probably change this in the future to Roll, Pitch, and Yaw_
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_We will probably change this in the future to Roll, Pitch, and Yaw._
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###### Collision
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@ -8,6 +8,7 @@ pages:
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- 'How to run CARLA server and client': 'how_to_run.md'
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- 'CARLA Settings': 'carla_settings.md'
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- 'Measurements': 'measurements.md'
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- 'Cameras and sensors': 'cameras_and_sensors.md'
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- 'Troubleshooting': 'troubleshooting.md'
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- Building from source:
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- 'How to build on Linux': 'how_to_build_on_linux.md'
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