diff --git a/Docs/core_sensors.md b/Docs/core_sensors.md index f9c6fa305..2db6866e6 100644 --- a/Docs/core_sensors.md +++ b/Docs/core_sensors.md @@ -67,7 +67,7 @@ sensor.listen(lambda data: do_something(data)) ... -# This supposed collision sensor would print everytime a collision is detected. +# This collision sensor would print everytime a collision is detected. def callback(event): for actor_id in event: vehicle = world_ref().get_actor(actor_id) @@ -95,14 +95,14 @@ Sensor data differs a lot between sensor types, but it is always tagged with:

Cameras

-These sensors take a shot of the world from their point of view and then use the helper class to alter this image and provide different types of information. +These sensors take a shot of the world from their point of view and then use the helper class to alter this image and provide different types of information. __Retrieve data:__ every simulation step. | Sensor | Output | Overview | | ---------- | ---------- | ---------- | -| Depth | [carla.Image](python_api.md#carla.Image) | Combines the photo with the distance of the elements on scene to provide with a gray-scale depth map. | +| Depth | [carla.Image](python_api.md#carla.Image) | Renders the depth of the elements in the field of view in a gray-scale depth map. | | RGB | [carla.Image](python_api.md#carla.Image) | Provides clear vision of the surroundings. Looks like a normal photo of the scene. | -| Semantic segmentation | [carla.Image](python_api.md#carla.Image) | Uses the tags of the different actors in the photo to group the elements by color. | +| Semantic segmentation | [carla.Image](python_api.md#carla.Image) | Renders elements in the field of view with a specific color according to their tags. |

Detectors

@@ -128,7 +128,7 @@ __Retrieve data:__ every simulation step. | Radar | [carla.RadarMeasurement](python_api.md#carla.RadarMeasurement) | 2D point map that models elements in sight and their movement regarding the sensor. | --------------- -That is a wrap on sensors and how do these retrieve simulation data and thus, the introduction to CARLA is finished. However there is yet a lot to learn. Here are some different paths opened at the moment: +That is a wrap on sensors and how do these retrieve simulation data and thus, the introduction to CARLA is finished. However there is yet a lot to learn. Some of the different paths to follow now are listed here: * __Gain some practise__: if diving alone in CARLA is still frightening, it may be a good idea to try some of the code recipes provided in this documentation and combine them with the example scripts or some ideas of your own.